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➴➴➴Æ🜔Ɲ.Ƈꭚ⍴𝔥єɼ👩🏻‍💻<p>People continue to think about <a href="https://lgbtqia.space/tags/AI" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>AI</span></a> in terms of <a href="https://lgbtqia.space/tags/2010s" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>2010s</span></a> computing, which is part of the reason everyone gets it wrong whether they're <a href="https://lgbtqia.space/tags/antiAI" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>antiAI</span></a> or <a href="https://lgbtqia.space/tags/tech" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>tech</span></a> bros.</p><p>Look, we had 8GB of <a href="https://lgbtqia.space/tags/ram" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ram</span></a> as the standard for a decade. The standard was set in 2014, and in 2015 <a href="https://lgbtqia.space/tags/AlphaGo" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>AlphaGo</span></a> beat a human at <a href="https://lgbtqia.space/tags/Go" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Go</span></a>. </p><p>Why? Because, <a href="https://lgbtqia.space/tags/hardware" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>hardware</span></a> lags <a href="https://lgbtqia.space/tags/software" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>software</span></a> - in <a href="https://lgbtqia.space/tags/economic" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>economic</span></a> terms: supply follows demand, but demand can not create its own supply.</p><p>It takes 3 years for a new chip to go through the <a href="https://lgbtqia.space/tags/technological" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>technological</span></a> readiness levels and be released.</p><p>It takes 5 years for a new <a href="https://lgbtqia.space/tags/chip" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>chip</span></a> architecture. E.g. the <a href="https://lgbtqia.space/tags/Zen" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Zen</span></a> architecture was conceived in 2012, and released in 2017.</p><p>It takes 10 years for a new type of technology, like a <a href="https://lgbtqia.space/tags/GPU" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>GPU</span></a>.</p><p>Now, AlphaGo needed a lot of RAM, so how did it stagnate for a decade after doubling every two years before that?</p><p>In 2007 the <a href="https://lgbtqia.space/tags/Iphone" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Iphone</span></a> was released. <a href="https://lgbtqia.space/tags/Computers" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Computers</span></a> were all becoming smaller, <a href="https://lgbtqia.space/tags/energy" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>energy</span></a> <a href="https://lgbtqia.space/tags/efficiency" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>efficiency</span></a> was becoming paramount, and everything was moving to the <a href="https://lgbtqia.space/tags/cloud" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>cloud</span></a>. </p><p>In 2017, most people used their computer for a few applications and a web browser. But also in 2017, companies were starting to build <a href="https://lgbtqia.space/tags/technology" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>technology</span></a> for AI, as it was becoming increasingly important.</p><p>Five years after that, we're in the <a href="https://lgbtqia.space/tags/pandemic" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>pandemic</span></a> lockdowns, and people are buying more powerful computers, we have <a href="https://lgbtqia.space/tags/LLM" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>LLM</span></a>, and companies are beginning to jack up the const of cloud services.</p><p><a href="https://lgbtqia.space/tags/Apple" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Apple</span></a> releases chips with large amounts of unified <a href="https://lgbtqia.space/tags/memory" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>memory</span></a>, <a href="https://lgbtqia.space/tags/ChatGPT" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ChatGPT</span></a> starts to break the internet, and in 2025, GPU growth continues to outpace CPU growth, and in 2025 you have a competitor to Apple's unified memory.</p><p>The era of cloud computing and surfing the <a href="https://lgbtqia.space/tags/web" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>web</span></a> is dead.</p><p>The hype of multi-trillion parameter <a href="https://lgbtqia.space/tags/LLMs" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>LLMs</span></a> making <a href="https://lgbtqia.space/tags/AGI" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>AGI</span></a> is a fantasy. There isn't enough power to do that, there aren't enough chips, it's already too expensive.</p><p>What _is_ coming is AI tech performing well and running locally without the cloud. AI Tech is _not_ just chatbots and <a href="https://lgbtqia.space/tags/aiart" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>aiart</span></a>. It's going to change what you can do with your <a href="https://lgbtqia.space/tags/computer" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>computer</span></a>.</p>
Jan :rust: :ferris:<p>Oops, I think I've gone a bit too deep into the <a href="https://floss.social/tags/AI" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>AI</span></a> rabbit hole today 😳 (a thread 🧵):</p><p>Did you know why AI systems like <a href="https://floss.social/tags/AlphaGo" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>AlphaGo</span></a> or <a href="https://floss.social/tags/AlphaZero" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>AlphaZero</span></a> performed so well?<br>It was because of their _objective function_:<br>-1 for loosing, +1 for winning ¯\_(ツ)_/¯</p><p>Why Artificial Intelligence Like AlphaZero Has Trouble With the Real World (February 2018)</p><p><a href="https://www.quantamagazine.org/why-artificial-intelligence-like-alphazero-has-trouble-with-the-real-world-20180221/" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://www.</span><span class="ellipsis">quantamagazine.org/why-artific</span><span class="invisible">ial-intelligence-like-alphazero-has-trouble-with-the-real-world-20180221/</span></a></p><p>Try to design an objective function for a self-driving car...</p><p>1/3</p><p><a href="https://floss.social/tags/ArtificialIntelligence" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ArtificialIntelligence</span></a> <a href="https://floss.social/tags/RabbitHole" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>RabbitHole</span></a></p>
Sarah Lea<p>What do a baby learning to walk and AlphaGo’s legendary Move 37 have in common?<br>They both learn by doing — not by being told.<br>That’s the essence of Reinforcement Learning.</p><p>It's great to see that my article on Q-learning &amp; Python agents was helpful to many readers and was featured in this week's Top 5 by Towards Data Science. Thanks! :blobcoffee: And make sure to check out the other four great reads too.</p><p>-&gt; <a href="https://www.linkedin.com/pulse/whats-our-reading-list-week-towards-data-science-dcihe" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://www.</span><span class="ellipsis">linkedin.com/pulse/whats-our-r</span><span class="invisible">eading-list-week-towards-data-science-dcihe</span></a></p><p><a href="https://techhub.social/tags/Reinforcementlearning" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Reinforcementlearning</span></a> <a href="https://techhub.social/tags/AI" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>AI</span></a> <a href="https://techhub.social/tags/Python" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Python</span></a> <a href="https://techhub.social/tags/DataScience" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>DataScience</span></a> <a href="https://techhub.social/tags/KI" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>KI</span></a> <a href="https://techhub.social/tags/alphago" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>alphago</span></a> <a href="https://techhub.social/tags/google" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>google</span></a> <a href="https://techhub.social/tags/googleai" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>googleai</span></a> <a href="https://techhub.social/tags/ArtificialIntelligence" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ArtificialIntelligence</span></a></p>
Jessica Bennet<p>Did you know machine learning algorithms can teach themselves to play video games just by practicing? AI like DeepMind’s AlphaGo and OpenAI’s Dota 2 bot have even beaten top human players by learning and adapting on their own—showing how powerful and creative AI can be!</p><p><a href="https://mastodon.social/tags/MachineLearning" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>MachineLearning</span></a> <a href="https://mastodon.social/tags/AI" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>AI</span></a> <a href="https://mastodon.social/tags/ArtificialIntelligence" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ArtificialIntelligence</span></a> <a href="https://mastodon.social/tags/DeepLearning" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>DeepLearning</span></a> <a href="https://mastodon.social/tags/TechFun" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>TechFun</span></a> <a href="https://mastodon.social/tags/AIgaming" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>AIgaming</span></a> <a href="https://mastodon.social/tags/AlphaGo" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>AlphaGo</span></a> <a href="https://mastodon.social/tags/Innovation" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Innovation</span></a> <a href="https://mastodon.social/tags/FutureTech" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>FutureTech</span></a> <a href="https://mastodon.social/tags/DataScience" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>DataScience</span></a> <a href="https://mastodon.social/tags/SmartTech" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>SmartTech</span></a> <a href="https://mastodon.social/tags/AIRevolution" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>AIRevolution</span></a> <a href="https://mastodon.social/tags/TechFacts" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>TechFacts</span></a> <a href="https://mastodon.social/tags/GamingAI" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>GamingAI</span></a></p>
Sarah Lea<p>What does a baby learning to walk have in common with AlphaGo’s Move 37?</p><p>Both learn by doing — not by being told.</p><p>That’s the essence of Reinforcement Learning.</p><p>In my latest article, I explain Q-learning with a bit Python and the world’s simplest game: Tic Tac Toe.</p><p>-&gt; No neural nets.<br>-&gt; Just some simple states, actions, rewards.</p><p>The result? A learning agent in under 100 lines of code.</p><p>Perfect if you are curious about how RL really works, before diving into more complex projects.</p><p>Concepts covered:<br>:blobcoffee: ε-greedy policy<br>:blobcoffee: Reward shaping<br>:blobcoffee: Value estimation<br>:blobcoffee: Exploration vs. exploitation</p><p>Read the full article on Towards Data Science → <a href="https://towardsdatascience.com/reinforcement-learning-made-simple-build-a-q-learning-agent-in-python/" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">towardsdatascience.com/reinfor</span><span class="invisible">cement-learning-made-simple-build-a-q-learning-agent-in-python/</span></a></p><p><a href="https://techhub.social/tags/Python" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Python</span></a> <a href="https://techhub.social/tags/ReinforcementLearning" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ReinforcementLearning</span></a> <a href="https://techhub.social/tags/ML" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ML</span></a> <a href="https://techhub.social/tags/KI" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>KI</span></a> <a href="https://techhub.social/tags/Technology" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Technology</span></a> <a href="https://techhub.social/tags/AI" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>AI</span></a> <a href="https://techhub.social/tags/AlphaGo" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>AlphaGo</span></a> <a href="https://techhub.social/tags/Google" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Google</span></a> <a href="https://techhub.social/tags/GoogleAI" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>GoogleAI</span></a> <a href="https://techhub.social/tags/DataScience" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>DataScience</span></a> <a href="https://techhub.social/tags/MachineLearning" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>MachineLearning</span></a> <a href="https://techhub.social/tags/Coding" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Coding</span></a> <a href="https://techhub.social/tags/Datascientist" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Datascientist</span></a> <a href="https://techhub.social/tags/programming" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>programming</span></a> <a href="https://techhub.social/tags/data" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>data</span></a></p>
Habr<p>Ведущий разработчик ChatGPT и его новый проект — Безопасный Сверхинтеллект</p><p>Многие знают об Илье Суцкевере только то, что он выдающийся учёный и программист, родился в СССР, соосновал OpenAI и входит в число тех, кто в 2023 году изгнал из компании менеджера Сэма Альтмана. А когда того вернули, Суцкевер уволился по собственному желанию в новый стартап Safe Superintelligence («Безопасный Сверхинтеллект»). Илья Суцкевер действительно организовал OpenAI вместе с Маском, Брокманом, Альтманом и другими единомышленниками, причём был главным техническим гением в компании. Ведущий учёный OpenAI сыграл ключевую роль в разработке ChatGPT и других продуктов. Сейчас Илье всего 38 лет — совсем немного для звезды мировой величины.</p><p><a href="https://habr.com/ru/companies/ruvds/articles/892646/" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">habr.com/ru/companies/ruvds/ar</span><span class="invisible">ticles/892646/</span></a></p><p><a href="https://zhub.link/tags/%D0%98%D0%BB%D1%8C%D1%8F_%D0%A1%D1%83%D1%86%D0%BA%D0%B5%D0%B2%D0%B5%D1%80" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Илья_Суцкевер</span></a> <a href="https://zhub.link/tags/Ilya_Sutskever" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Ilya_Sutskever</span></a> <a href="https://zhub.link/tags/OpenAI" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>OpenAI</span></a> <a href="https://zhub.link/tags/10x_engineer" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>10x_engineer</span></a> <a href="https://zhub.link/tags/AlexNet" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>AlexNet</span></a> <a href="https://zhub.link/tags/Safe_Superintelligence" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Safe_Superintelligence</span></a> <a href="https://zhub.link/tags/ImageNet" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ImageNet</span></a> <a href="https://zhub.link/tags/%D0%BD%D0%B5%D0%BE%D0%BA%D0%BE%D0%B3%D0%BD%D0%B8%D1%82%D1%80%D0%BE%D0%BD" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>неокогнитрон</span></a> <a href="https://zhub.link/tags/GPU" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>GPU</span></a> <a href="https://zhub.link/tags/GPGPU" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>GPGPU</span></a> <a href="https://zhub.link/tags/CUDA" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>CUDA</span></a> <a href="https://zhub.link/tags/%D0%BA%D0%BE%D0%BC%D0%BF%D1%8C%D1%8E%D1%82%D0%B5%D1%80%D0%BD%D0%BE%D0%B5_%D0%B7%D1%80%D0%B5%D0%BD%D0%B8%D0%B5" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>компьютерное_зрение</span></a> <a href="https://zhub.link/tags/LeNet" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>LeNet</span></a> <a href="https://zhub.link/tags/Nvidia_GTX" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Nvidia_GTX</span></a>&nbsp;580 <a href="https://zhub.link/tags/DNNResearch" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>DNNResearch</span></a> <a href="https://zhub.link/tags/Google_Brain" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Google_Brain</span></a> <a href="https://zhub.link/tags/%D0%90%D0%BB%D0%B5%D0%BA%D1%81_%D0%9A%D1%80%D0%B8%D0%B6%D0%B5%D0%B2%D1%81%D0%BA%D0%B8" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Алекс_Крижевски</span></a> <a href="https://zhub.link/tags/%D0%94%D0%B6%D0%B5%D1%84%D1%84%D1%80%D0%B8_%D0%A5%D0%B8%D0%BD%D1%82%D0%BE%D0%BD" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Джеффри_Хинтон</span></a> <a href="https://zhub.link/tags/Seq2seq" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Seq2seq</span></a> <a href="https://zhub.link/tags/TensorFlow" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>TensorFlow</span></a> <a href="https://zhub.link/tags/AlphaGo" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>AlphaGo</span></a> <a href="https://zhub.link/tags/%D0%A2%D0%BE%D0%BC%D0%B0%D1%88_%D0%9C%D0%B8%D0%BA%D0%BE%D0%BB%D0%BE%D0%B2" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Томаш_Миколов</span></a> <a href="https://zhub.link/tags/Word2vec" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Word2vec</span></a> <a href="https://zhub.link/tags/fewshot_learning" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>fewshot_learning</span></a> <a href="https://zhub.link/tags/%D0%BC%D0%B0%D1%88%D0%B8%D0%BD%D0%B0_%D0%91%D0%BE%D0%BB%D1%8C%D1%86%D0%BC%D0%B0%D0%BD%D0%B0" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>машина_Больцмана</span></a> <a href="https://zhub.link/tags/%D1%81%D0%B2%D0%B5%D1%80%D1%85%D0%B8%D0%BD%D1%82%D0%B5%D0%BB%D0%BB%D0%B5%D0%BA%D1%82" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>сверхинтеллект</span></a> <a href="https://zhub.link/tags/GPT" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>GPT</span></a> <a href="https://zhub.link/tags/ChatGPT" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ChatGPT</span></a> <a href="https://zhub.link/tags/ruvds_%D1%81%D1%82%D0%B0%D1%82%D1%8C%D0%B8" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ruvds_статьи</span></a></p>
Teixi<p><a href="https://mastodon.social/tags/ACMPrize" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ACMPrize</span></a><br><a href="https://mastodon.social/tags/2024ACMPrize" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>2024ACMPrize</span></a><br><a href="https://mastodon.social/tags/ACMTuringAward" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ACMTuringAward</span></a></p><p><a href="https://mastodon.social/tags/AndrewBarto" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>AndrewBarto</span></a><br><a href="https://mastodon.social/tags/RichardSutton" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>RichardSutton</span></a> </p><p>» <a href="https://mastodon.social/tags/ReinforcementLearning" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ReinforcementLearning</span></a><br>An Introduction<br>1998<br>standard reference...cited over 75,000<br>...<br>prominent example of <a href="https://mastodon.social/tags/RL" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>RL</span></a><br><a href="https://mastodon.social/tags/AlphaGo" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>AlphaGo</span></a> victory<br>over best human <a href="https://mastodon.social/tags/Go" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Go</span></a> players<br>2016 2017<br>....<br>recently has been the development of the chatbot <a href="https://mastodon.social/tags/ChatGPT" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ChatGPT</span></a><br>...<br>large language model <a href="https://mastodon.social/tags/LLM" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>LLM</span></a> trained in two phases ...employs a technique called<br>reinforcement learning from human feedback <a href="https://mastodon.social/tags/RLHF" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>RLHF</span></a> «</p><p>aka cheap labor unnamed in papers</p><p><a href="https://awards.acm.org/about/2024-turing" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">awards.acm.org/about/2024-turi</span><span class="invisible">ng</span></a></p><p>2/2</p>
Vaughn<p><span class="h-card" translate="no"><a href="https://twit.social/@leo" class="u-url mention" rel="nofollow noopener" target="_blank">@<span>leo</span></a></span> I love that you keep mentioning move 37 that AlphaGo made against Lee Sedol. The most poetic thing is that Lee made a similar move in the very next game (the only one he won) that the pros thought was a mistake and that seemed to confuse AlphaGo. <a href="https://m.socialyeti.club/tags/go" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>go</span></a> <a href="https://m.socialyeti.club/tags/alphago" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>alphago</span></a> <a href="https://m.socialyeti.club/tags/baduk" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>baduk</span></a> <a href="https://m.socialyeti.club/tags/weiqi" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>weiqi</span></a></p>
Socied@d Reticular<p><strong>Pequeños y grandes pasos hacia el imperio de la inteligencia&nbsp;artificial</strong></p><a href="https://mas.to/@echo_xc@mastodon.social/113971286060501063" rel="nofollow noopener" target="_blank"></a>Fuente: Open Tech<p><strong>Traducción de la infografía:</strong></p><ul><li><strong>1943</strong> – McCullock y Pitts publican un artículo titulado <em>Un cálculo lógico de ideas inmanentes en la actividad nerviosa</em>, en el que proponen las bases para las redes neuronales.</li></ul><ul><li><strong>1950</strong> – Turing publica <em>Computing Machinery and Intelligence</em>, proponiendo el Test de Turing como forma de medir la capacidad de una máquina.</li></ul><ul><li><strong>1951</strong> – Marvin Minsky y Dean Edmonds construyen SNAR, la primera computadora de red neuronal.</li></ul><ul><li><strong>1956</strong> – Se celebra la Conferencia de Dartmouth (organizada por McCarthy, Minsky, Rochester y Shannon), que marca el nacimiento de la IA como campo de estudio.</li></ul><ul><li><strong>1957</strong> – Rosenblatt desarrolla el Perceptrón: la primera red neuronal artificial capaz de aprender.</li></ul><p><strong>(!!)</strong> <strong><em>Test de Turing</em></strong>: donde un evaluador humano entabla una conversación en lenguaje natural con una máquina y un humano.</p><ul><li><strong>1965</strong> – Weizenbaum desarrolla ELIZA: un programa de procesamiento del lenguaje natural que simula una conversación.</li></ul><ul><li><strong>1967</strong> – Newell y Simon desarrollan el Solucionador General de Problemas (GPS), uno de los primeros programas de IA que demuestra una capacidad de resolución de problemas similar a la humana.</li></ul><ul><li><strong>1974</strong> – Comienza el primer invierno de la IA, marcado por una disminución de la financiación y del interés en la investigación en IA debido a expectativas poco realistas y a un progreso limitado.</li></ul><ul><li><strong>1980</strong> – Los sistemas expertos ganan popularidad y las empresas los utilizan para realizar previsiones financieras y diagnósticos médicos.</li></ul><ul><li><strong>1986</strong> – Hinton, Rumelhart y Williams publican <em>Aprendizaje de representaciones mediante retropropagación de errores</em>, que permite entrenar redes neuronales mucho más profundas.</li></ul><p><strong>(!!)</strong> <strong><em>Redes neuronales</em></strong>: modelos de aprendizaje automático que imitan el cerebro y aprenden a reconocer patrones y hacer predicciones a través de conexiones neuronales artificiales.</p><ul><li><strong>1997</strong> – Deep Blue de IBM derrota al campeón mundial de ajedrez Kasparov, siendo la primera vez que una computadora vence a un campeón mundial en un juego complejo.</li></ul><ul><li><strong>2002</strong> – iRobot presenta Roomba, el primer robot aspirador doméstico producido en serie con un sistema de navegación impulsado por IA.</li></ul><ul><li><strong>2011</strong> – Watson de IBM derrota a dos ex campeones de Jeopardy!.</li></ul><ul><li><strong>2012</strong> – La startup de inteligencia artificial DeepMind desarrolla una red neuronal profunda que puede reconocer gatos en vídeos de YouTube.</li></ul><ul><li><strong>2014</strong> – Facebook crea DeepFace, un sistema de reconocimiento facial que puede reconocer rostros con una precisión casi humana.</li></ul><p><strong>(!!) <em>DeepMind</em></strong> fue adquirida por Google en 2014 por 500 millones de dólares.</p><ul><li><strong>2015</strong> – AlphaGo, desarrollado por DeepMind, derrota al campeón mundial Lee Sedol en el juego de Go.</li></ul><ul><li><strong>2017</strong> – AlphaZero de Google derrota a los mejores motores de ajedrez y shogi del mundo en una serie de partidas.</li></ul><ul><li><strong>2020</strong> – OpenAI lanza GPT-3, lo que marca un avance significativo en el procesamiento del lenguaje natural.</li></ul><p><strong>(!!) <em>Procesamiento del lenguaje natural</em></strong>: enseña a las computadoras a comprender y utilizar el lenguaje humano mediante técnicas como el aprendizaje automático.</p><ul><li><strong>2021</strong> – AlphaFold2 de DeepMind resuelve el problema del plegamiento de proteínas, allanando el camino para nuevos descubrimientos de fármacos y avances médicos.</li></ul><ul><li><strong>2022</strong> – Google despide al ingeniero Blake Lemoine por sus afirmaciones de que el modelo de lenguaje para aplicaciones de diálogo (LaMDA) de Google era sensible.</li></ul><ul><li><strong>2023</strong> – Artistas presentaron una demanda colectiva contra Stability AI, DeviantArt y Mid-journey por usar Stable Diffusion para remezclar las obras protegidas por derechos de autor de millones de artistas.</li></ul><p><em><strong>Gráfico:</strong> <a href="https://mas.to/@echo_xc@mastodon.social/113971286060501063" rel="nofollow noopener" target="_blank">Open Tech</a> / <a href="https://www.genuineimpact.io/" rel="nofollow noopener" target="_blank">Genuine Impact</a></em></p><p>Entradas relacionadas</p><ul><li><a href="https://anselmolucio.wordpress.com/2025/01/31/como-definir-la-credibilidad-algoritmica-deepseek-da-en-el-clavo/" rel="nofollow noopener" target="_blank">¿Cómo definir la «credibilidad algorítmica»? 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rel="nofollow noopener" class="hashtag u-tag u-category" href="https://anselmolucio.wordpress.com/tag/alphazero/" target="_blank">#AlphaZero</a> <a rel="nofollow noopener" class="hashtag u-tag u-category" href="https://anselmolucio.wordpress.com/tag/aprendizaje-automatico/" target="_blank">#aprendizajeAutomático</a> <a rel="nofollow noopener" class="hashtag u-tag u-category" href="https://anselmolucio.wordpress.com/tag/articulo/" target="_blank">#artículo</a> <a rel="nofollow noopener" class="hashtag u-tag u-category" href="https://anselmolucio.wordpress.com/tag/artistas/" target="_blank">#artistas</a> <a rel="nofollow noopener" class="hashtag u-tag u-category" href="https://anselmolucio.wordpress.com/tag/aspirador/" target="_blank">#aspirador</a> <a rel="nofollow noopener" class="hashtag u-tag u-category" href="https://anselmolucio.wordpress.com/tag/blake-lemoine/" target="_blank">#BlakeLemoine</a> <a rel="nofollow noopener" class="hashtag u-tag u-category" href="https://anselmolucio.wordpress.com/tag/conferencia-de-dartmouth/" target="_blank">#ConferenciaDeDartmouth</a> <a rel="nofollow noopener" class="hashtag u-tag u-category" href="https://anselmolucio.wordpress.com/tag/copyright/" target="_blank">#copyright</a> <a rel="nofollow noopener" class="hashtag u-tag u-category" href="https://anselmolucio.wordpress.com/tag/dean-edmonds/" target="_blank">#DeanEdmonds</a> <a rel="nofollow noopener" class="hashtag u-tag u-category" href="https://anselmolucio.wordpress.com/tag/deep-blue/" target="_blank">#DeepBlue</a> <a rel="nofollow noopener" class="hashtag u-tag u-category" href="https://anselmolucio.wordpress.com/tag/deepface/" target="_blank">#DeepFace</a> <a rel="nofollow noopener" class="hashtag u-tag u-category" href="https://anselmolucio.wordpress.com/tag/deepmind/" target="_blank">#DeepMind</a> <a rel="nofollow noopener" class="hashtag u-tag u-category" href="https://anselmolucio.wordpress.com/tag/deviantart/" 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Rod2ik 🇪🇺 🇨🇵 🇪🇸 🇺🇦 🇨🇦 🇩🇰 🇬🇱<p>Le moment <a href="https://mastodon.social/tags/DeepSeek" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>DeepSeek</span></a> (2025) est la conséquence du moment <a href="https://mastodon.social/tags/AlphaGo" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>AlphaGo</span></a> (2010) de <a href="https://mastodon.social/tags/Google" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Google</span></a> <a href="https://mastodon.social/tags/Deepmind" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Deepmind</span></a> : il a été vécu comme le moment <a href="https://mastodon.social/tags/Spoutnik" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Spoutnik</span></a> (1957) de la <a href="https://mastodon.social/tags/Chine" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Chine</span></a> pour l' <a href="https://mastodon.social/tags/IA" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>IA</span></a> <a href="https://mastodon.social/tags/AI" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>AI</span></a></p><p><a href="https://www.numerama.com/tech/1894778-alphago-comment-la-raclee-subie-par-la-chine-au-go-explique-deepseek-aujourdhui.html" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://www.</span><span class="ellipsis">numerama.com/tech/1894778-alph</span><span class="invisible">ago-comment-la-raclee-subie-par-la-chine-au-go-explique-deepseek-aujourdhui.html</span></a></p>
Rod2ik 🇪🇺 🇨🇵 🇪🇸 🇺🇦 🇨🇦 🇩🇰 🇬🇱<p>Le moment <a href="https://bsky.app/search?q=%23DeepSeek" rel="nofollow noopener" target="_blank">#DeepSeek</a> (2025) est la conséquence du moment <a href="https://bsky.app/search?q=%23AlphaGo" rel="nofollow noopener" target="_blank">#AlphaGo</a> (2010) de <a href="https://bsky.app/search?q=%23Google" rel="nofollow noopener" target="_blank">#Google</a> <a href="https://bsky.app/search?q=%23Deepmind" rel="nofollow noopener" target="_blank">#Deepmind</a> : il a été vécu comme le moment <a href="https://bsky.app/search?q=%23Spoutnik" rel="nofollow noopener" target="_blank">#Spoutnik</a> (1957) de la <a href="https://bsky.app/search?q=%23Chine" rel="nofollow noopener" target="_blank">#Chine</a> pour l' <a href="https://bsky.app/search?q=%23IA" rel="nofollow noopener" target="_blank">#IA</a> <a href="https://bsky.app/search?q=%23AI" rel="nofollow noopener" target="_blank">#AI</a> <a href="https://www.numerama.com/tech/1894778-alphago-comment-la-raclee-subie-par-la-chine-au-go-explique-deepseek-aujourdhui.html" rel="nofollow noopener" target="_blank">www.numerama.com/tech/1894778...</a><br><br><a href="https://www.numerama.com/tech/1894778-alphago-comment-la-raclee-subie-par-la-chine-au-go-explique-deepseek-aujourdhui.html" rel="nofollow noopener" target="_blank">Comment AlphaGo a joué un rôle...</a></p>
rexi<p><a href="https://techxplore.com/news/2024-12-ai-human-general-intelligence.html" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">techxplore.com/news/2024-12-ai</span><span class="invisible">-human-general-intelligence.html</span></a></p><p><a href="https://mastodon.social/tags/OpenAI" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>OpenAI</span></a> started with a general-purpose version of the <a href="https://mastodon.social/tags/o3system" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>o3system</span></a> (which…can spend more time "thinking" about difficult questions) and then trained it specifically for the ARC-AGI test.</p><p>French <a href="https://mastodon.social/tags/AI" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>AI</span></a> researcher Francois Chollet…believes o3 searches through different "chains of thought" describing steps to solve the task. It would then choose the "best"…"not dissimilar" to how <a href="https://mastodon.social/tags/Google" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Google</span></a> <a href="https://mastodon.social/tags/AlphaGo" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>AlphaGo</span></a> system…beat the world Go champion.</p>
:rss: Hacker News<p>ChatGPT Learned to Reason [video]<br><a href="https://www.youtube.com/watch?v=PvDaPeQjxOE" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://www.</span><span class="ellipsis">youtube.com/watch?v=PvDaPeQjxO</span><span class="invisible">E</span></a><br><a href="https://rss-mstdn.studiofreesia.com/tags/ycombinator" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ycombinator</span></a> <a href="https://rss-mstdn.studiofreesia.com/tags/AI_reasoning" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>AI_reasoning</span></a> <a href="https://rss-mstdn.studiofreesia.com/tags/ChatGPT_explained" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ChatGPT_explained</span></a> <a href="https://rss-mstdn.studiofreesia.com/tags/artificial_intelligence" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>artificial_intelligence</span></a> <a href="https://rss-mstdn.studiofreesia.com/tags/neural_networks" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>neural_networks</span></a> <a href="https://rss-mstdn.studiofreesia.com/tags/Monte_Carlo_Tree_Search" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Monte_Carlo_Tree_Search</span></a> <a href="https://rss-mstdn.studiofreesia.com/tags/DeepMind" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>DeepMind</span></a> <a href="https://rss-mstdn.studiofreesia.com/tags/AlphaGo" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>AlphaGo</span></a> <a href="https://rss-mstdn.studiofreesia.com/tags/chess_AI" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>chess_AI</span></a> <a href="https://rss-mstdn.studiofreesia.com/tags/language_models" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>language_models</span></a> <a href="https://rss-mstdn.studiofreesia.com/tags/machine_learning" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>machine_learning</span></a> <a href="https://rss-mstdn.studiofreesia.com/tags/reinforcement_learning" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>reinforcement_learning</span></a> <a href="https://rss-mstdn.studiofreesia.com/tags/deep_learning" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>deep_learning</span></a> <a href="https://rss-mstdn.studiofreesia.com/tags/AI_history" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>AI_history</span></a> <a href="https://rss-mstdn.studiofreesia.com/tags/GPT_training" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>GPT_training</span></a> <a href="https://rss-mstdn.studiofreesia.com/tags/chain_of_thought" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>chain_of_thought</span></a> <a href="https://rss-mstdn.studiofreesia.com/tags/AI_breakthrough" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>AI_breakthrough</span></a> <a href="https://rss-mstdn.studiofreesia.com/tags/game_AI" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>game_AI</span></a> <a href="https://rss-mstdn.studiofreesia.com/tags/TD_Gammon" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>TD_Gammon</span></a> <a href="https://rss-mstdn.studiofreesia.com/tags/MuZero" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>MuZero</span></a> <a href="https://rss-mstdn.studiofreesia.com/tags/Claude_AI" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Claude_AI</span></a> <a href="https://rss-mstdn.studiofreesia.com/tags/O1_AI" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>O1_AI</span></a> <a href="https://rss-mstdn.studiofreesia.com/tags/AI_algorithms" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>AI_algorithms</span></a> <a href="https://rss-mstdn.studiofreesia.com/tags/AI_development" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>AI_development</span></a> <a href="https://rss-mstdn.studiofreesia.com/tags/computer_reasoning" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>computer_reasoning</span></a> <a href="https://rss-mstdn.studiofreesia.com/tags/AI_evolution" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>AI_evolution</span></a> <a href="https://rss-mstdn.studiofreesia.com/tags/future_AI" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>future_AI</span></a></p>
🅴🆁🆄🅰 🇷🇺Странное чувство при осознании того, что видео-карта приобретена не только ради нормальной картинки в играх. Что эта вычислительная мощность активно используется и во время других игр, но где нужны обдуманные и взвешенные ходы, а не обсчёт задачек ради 3d-графики.<br><br>Например, игра в #<a class="" href="https://hub.hubzilla.de/search?tag=%D0%93%D0%BE" rel="nofollow noopener" target="_blank">Го</a> — движки способные заменить людей выполняют неслабые такие нейросети в комбинации с #<a class="" href="https://hub.hubzilla.de/search?tag=MCTS" rel="nofollow noopener" target="_blank">MCTS</a> (Monte-Carlo Tree Search).<br><br>Сперва это был #<a class="" href="https://hub.hubzilla.de/search?tag=LeelaZero" rel="nofollow noopener" target="_blank">LeelaZero</a>, являющийся повторением #<a class="" href="https://hub.hubzilla.de/search?tag=AlphaGo" rel="nofollow noopener" target="_blank">AlphaGo</a> Zero согласно его <a href="https://discovery.ucl.ac.uk/id/eprint/10045895/1/agz_unformatted_nature.pdf" rel="nofollow noopener" target="_blank">оригинальному описанию</a>.<br><br>Теперь это #<a class="" href="https://hub.hubzilla.de/search?tag=KataGo" rel="nofollow noopener" target="_blank">KataGo</a>, в целом аналогичная, но с <a href="https://arxiv.org/abs/1902.10565" rel="nofollow noopener" target="_blank">рядом доработок</a> заточенных под игру #<a class="" href="https://hub.hubzilla.de/search?tag=%D0%93%D0%BE" rel="nofollow noopener" target="_blank">Го</a> и активно развиваемая/тренируемая, в то время как, работы над #<a class="" href="https://hub.hubzilla.de/search?tag=LeelaZero" rel="nofollow noopener" target="_blank">LeelaZero</a> прекратились в районе 2021 года.<br><br>Очень может быть, что в скором времени, компьютерам нужна будет видеокарта как универсальный ускоритель общего назначения. Используемый и в локальных системах представления и анализа данных — самое элементарное создания динамических отчётов (dashboard'ов) заточенных под конкретного пользователя. Например, это могут быть различные «ассистенты», выполняющиеся на компьютере пользователя, к которым человек обращается с поручениями что-то узнать или выяснить.<br><br>Ускорять специфичным «железом» (#<a class="" href="https://hub.hubzilla.de/search?tag=VLIW" rel="nofollow noopener" target="_blank">VLIW</a> #<a class="" href="https://hub.hubzilla.de/search?tag=TensorFlow%29" rel="nofollow noopener" target="_blank">TensorFlow)</a> надо будет не только парсинг/разбор запросов от человека на естественно языке (голосом, текстом), но и всю ту работу, которая должна быть проведена при создании запрошенного.<br><br>#<a class="" href="https://hub.hubzilla.de/search?tag=OpenCL" rel="nofollow noopener" target="_blank">OpenCL</a> #<a class="" href="https://hub.hubzilla.de/search?tag=hardware" rel="nofollow noopener" target="_blank">hardware</a> #<a class="" href="https://hub.hubzilla.de/search?tag=lang_ru" rel="nofollow noopener" target="_blank">lang_ru</a>
🅴🆁🆄🅰 🇷🇺Попробовал как играют современные нейронки в #<a class="" href="https://hub.hubzilla.de/search?tag=%D0%93%D0%BE" rel="nofollow noopener" target="_blank">Го</a> на домашнем десктопе с простенькой видяхой, open source варианты, свободные.<br><br>Затем, что современные значимые и серьёзные успехи «искусственного интеллекта» пошли в массы с эпопеи вокруг #<a class="" href="https://hub.hubzilla.de/search?tag=AlphaGo" rel="nofollow noopener" target="_blank">AlphaGo</a>, которое за три-четыре года развития изменилось сильно и в размерах и скорости работы, хорошо задокументированно и всячески изучено.<br>Так вот, прошло изрядно лет уже с тех пор как AlphaGo остановилось в развитии, достигнув апогея (AlphaGo Zero), и где свободные аналоги? Пусть и заточенные именно для игры в Го и только для неё.<br><br>Отыскался <a href="https://github.com/lightvector/KataGo?tab=readme-ov-file#" rel="nofollow noopener" target="_blank">движок KataGo</a>, вроде по тем же принципам, что и последние варианты AlphaGo, с уже обученными сетками, которые регулярно обновляются дообучаясь.<br><br>#<a class="" href="https://hub.hubzilla.de/search?tag=KataGo" rel="nofollow noopener" target="_blank">KataGo</a> вариант использующий видеокарту, #<a class="" href="https://hub.hubzilla.de/search?tag=OpenCL" rel="nofollow noopener" target="_blank">OpenCL</a>, сходу не завёлся — пришлось погонять сперва вариант для #<a class="" href="https://hub.hubzilla.de/search?tag=CPU" rel="nofollow noopener" target="_blank">CPU</a>, чтобы подобрать GUI для использования движка: #<a class="" href="https://hub.hubzilla.de/search?tag=Sabaki" rel="nofollow noopener" target="_blank">Sabaki</a>, #<a class="" href="https://hub.hubzilla.de/search?tag=q5Go" rel="nofollow noopener" target="_blank">q5Go</a>.<br>Заценив работу движка и шум системы охлаждения процессора — уже переключился на OpenCL-вариант. Для чего пришлось сносить из системы всё про #<a class="" href="https://hub.hubzilla.de/search?tag=Mesa" rel="nofollow noopener" target="_blank">Mesa</a> и ставить «opencl-amd» на #<a class="" href="https://hub.hubzilla.de/search?tag=ArchLinux" rel="nofollow noopener" target="_blank">ArchLinux</a>.<br><br>И оно того стоит, не только потому что реально быстрее работает в плане ходов да подсчёта всякой аналитики, но главное комп перестал надрываться работой системы охлаждения. Памяти на видяхе KataGo отжирает порядка гигабайта, может полутора. Однако, у меня и режим работы выбран с дополнительной нейронкой для подражания человеку в плане манеры игры, ссылки на этот вариант работы движка есть в readme.<br><br><strong>Планшеты и мобильники?</strong><br>Для #<a class="" href="https://hub.hubzilla.de/search?tag=android" rel="nofollow noopener" target="_blank">android</a> тоже есть вариант KataGo — зовётся #<a class="" href="https://hub.hubzilla.de/search?tag=BadukAI" rel="nofollow noopener" target="_blank">BadukAI</a>, доступен и в Google'ом и Amazon'овском маркете <a href="https://play.google.com/store/apps/details?id=net.kir.baduk_ai&amp;hl=en-US" rel="nofollow noopener" target="_blank">ссылка</a>, а так же через альтернативные клиенты. Если в #<a class="" href="https://hub.hubzilla.de/search?tag=Aurora" rel="nofollow noopener" target="_blank">Aurora</a> не работает вдруг поиск, то ссылку ту можно открыть/отправить в #<a class="" href="https://hub.hubzilla.de/search?tag=Aurora" rel="nofollow noopener" target="_blank">Aurora</a> и откроет спокойно.<br><br><strong>Что на счёт GUI?</strong><br>Прежде чем гонять движки разные, имеет смысл опробовать <a href="https://www.gnu.org/software/gnugo/" rel="nofollow noopener" target="_blank">GNU Go</a> — это который про игру в #<a class="" href="https://hub.hubzilla.de/search?tag=%D0%93%D0%BE" rel="nofollow noopener" target="_blank">Го</a> с компьютером, оно же «Бадук» у корейцев и «Вэйци» у китайцев (откуда якобы и пришло). GNU Go есть у всех линухов в репозиториях и доступен любому желающему поиграть в Го через #<a class="" href="https://hub.hubzilla.de/search?tag=Kigo" rel="nofollow noopener" target="_blank">Kigo</a>, #<a class="" href="https://hub.hubzilla.de/search?tag=qGo" rel="nofollow noopener" target="_blank">qGo</a>, #<a class="" href="https://hub.hubzilla.de/search?tag=q5Go" rel="nofollow noopener" target="_blank">q5Go</a>, #<a class="" href="https://hub.hubzilla.de/search?tag=Sabaki" rel="nofollow noopener" target="_blank">Sabaki</a>, #<a class="" href="https://hub.hubzilla.de/search?tag=KaTrain" rel="nofollow noopener" target="_blank">KaTrain</a>, #<a class="" href="https://hub.hubzilla.de/search?tag=Lizzie" rel="nofollow noopener" target="_blank">Lizzie</a>.<br>Если выбранная GUI'шная софтина работает с GNU Go, то будет работать (должны) и со всякими другими движками для игры в Го, потому что используется gtp режим.<br><br>Сложность лишь в том, что порой GNU Go путают с GNU'шным компилятором Golang — который называется иначе: <a href="https://go.dev/doc/install/gccgo" rel="nofollow noopener" target="_blank">GCC Go</a>.<br><br><strong>Альтернативы нейронкам?</strong><br>Есть вариант сугубо на базе #<a class="" href="https://hub.hubzilla.de/search?tag=MCTS" rel="nofollow noopener" target="_blank">MCTS</a> (который Monte Carlo tree search) — ощутимо получше GNU Go и более относительно современное — #<a class="" href="https://hub.hubzilla.de/search?tag=Pachi" rel="nofollow noopener" target="_blank">Pachi</a> <br>Работает на десктопе серьёзно нагружая систему, имеет кучу заморочек на тему подключения движка дополнительного для #<a class="" href="https://hub.hubzilla.de/search?tag=joseki" rel="nofollow noopener" target="_blank">joseki</a>, не сказать чтобы весёлый вариант.<br>Однако, если ставить на android-устройство, то существует небольшой <a href="https://play.google.com/store/apps/details?id=net.lrstudios.android.pachi" rel="nofollow noopener" target="_blank">вариант</a>, размером менее трёх мегабайт, который вполне шустро работает.<br><br>#<a class="" href="https://hub.hubzilla.de/search?tag=AI" rel="nofollow noopener" target="_blank">AI</a> #<a class="" href="https://hub.hubzilla.de/search?tag=%D0%98%D0%98" rel="nofollow noopener" target="_blank">ИИ</a> #<a class="" href="https://hub.hubzilla.de/search?tag=games" rel="nofollow noopener" target="_blank">games</a> #<a class="" href="https://hub.hubzilla.de/search?tag=gaming" rel="nofollow noopener" target="_blank">gaming</a> #<a class="" href="https://hub.hubzilla.de/search?tag=%D0%B3%D0%BE" rel="nofollow noopener" target="_blank">го</a> #<a class="" href="https://hub.hubzilla.de/search?tag=igo" rel="nofollow noopener" target="_blank">igo</a> #<a class="" href="https://hub.hubzilla.de/search?tag=baduk" rel="nofollow noopener" target="_blank">baduk</a> #<a class="" href="https://hub.hubzilla.de/search?tag=%D0%B1%D0%B0%D0%B4%D1%83%D0%BA" rel="nofollow noopener" target="_blank">бадук</a> #<a class="" href="https://hub.hubzilla.de/search?tag=weiqi" rel="nofollow noopener" target="_blank">weiqi</a> #<a class="" href="https://hub.hubzilla.de/search?tag=%D0%B2%D1%8D%D0%B9%D1%86%D0%B8" rel="nofollow noopener" target="_blank">вэйци</a> #<a class="" href="https://hub.hubzilla.de/search?tag=lang_ru" rel="nofollow noopener" target="_blank">lang_ru</a> @<a href="https://3zi.ru/@Russia" rel="nofollow noopener" target="_blank">Russia</a>
Matthias MProve<p><span class="h-card" translate="no"><a href="https://recsys.social/@alansaid" class="u-url mention" rel="nofollow noopener" target="_blank">@<span>alansaid</span></a></span> <span class="h-card" translate="no"><a href="https://sigmoid.social/@Riedl" class="u-url mention" rel="nofollow noopener" target="_blank">@<span>Riedl</span></a></span> à propos <a href="https://hci.social/tags/AlphaGo" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>AlphaGo</span></a> &gt;&gt; <a href="https://hci.social/@mprove/111866463222208721" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">hci.social/@mprove/11186646322</span><span class="invisible">2208721</span></a></p>
Arne Babenhauserheide<p>When <a href="https://rollenspiel.social/tags/AlphaGo" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>AlphaGo</span></a> cracked <a href="https://rollenspiel.social/tags/Go" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Go</span></a>, the holy grail of game <a href="https://rollenspiel.social/tags/AI" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>AI</span></a>, it proved that there are problems that we can currently only solve via a machine learning approach.</p><p>Other approaches never managed more than mediocre play, AlphaGo beat the world class.</p><p>Nine years later there are two types of AI:</p><p>- Type 1 solves such problems.<br>- Type 2 is <a href="https://rollenspiel.social/tags/bullshit" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>bullshit</span></a>.</p><p><a href="https://www.draketo.de/zitate#alpha-go-nine-years-later" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://www.</span><span class="ellipsis">draketo.de/zitate#alpha-go-nin</span><span class="invisible">e-years-later</span></a></p>
Altreconomia<p>Scatole oscure o intelligenze aliene? Il caso del software AlphaGo e i fantasmi di Italo Calvino <a href="https://altreconomia.it/scatole-oscure-o-intelligenze-aliene-il-caso-del-software-alphago-e-i-fantasmi-di-italo-calvino/" rel="nofollow noopener" target="_blank"><span class="invisible">https://</span><span class="ellipsis">altreconomia.it/scatole-oscure</span><span class="invisible">-o-intelligenze-aliene-il-caso-del-software-alphago-e-i-fantasmi-di-italo-calvino/</span></a> <a href="https://sociale.network/tags/Intelligenzaartificiale" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Intelligenzaartificiale</span></a> <a href="https://sociale.network/tags/reinforcementlearning" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>reinforcementlearning</span></a> <a href="https://sociale.network/tags/scatoleoscure" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>scatoleoscure</span></a> <a href="https://sociale.network/tags/deeplearning" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>deeplearning</span></a> <a href="https://sociale.network/tags/italocalvino" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>italocalvino</span></a> <a href="https://sociale.network/tags/alanturing" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>alanturing</span></a> <a href="https://sociale.network/tags/samaltman" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>samaltman</span></a> <a href="https://sociale.network/tags/Opinioni" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Opinioni</span></a> <a href="https://sociale.network/tags/deepmind" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>deepmind</span></a> <a href="https://sociale.network/tags/alphago" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>alphago</span></a> <a href="https://sociale.network/tags/chatgpt" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>chatgpt</span></a> <a href="https://sociale.network/tags/Harari" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Harari</span></a> <a href="https://sociale.network/tags/go" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>go</span></a></p>
goldfishlaser<p>I had long procrastinated listening to Lex Fridman's interview with David Silver about <a href="https://fosstodon.org/tags/alphago" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>alphago</span></a> Linking below to my favorite part of the conversation, where he discusses self play and why there is no ceiling to improvements with increased computing power...</p><p><a href="https://youtu.be/uPUEq8d73JI?t=4512&amp;si=GROx0rqS9YS3PAVO" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">youtu.be/uPUEq8d73JI?t=4512&amp;si</span><span class="invisible">=GROx0rqS9YS3PAVO</span></a></p>
Michael Gisiger :mastodon:<p><a href="https://nerdculture.de/tags/OpenAI" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>OpenAI</span></a> calls the <a href="https://nerdculture.de/tags/CoT" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>CoT</span></a> <a href="https://nerdculture.de/tags/LLM" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>LLM</span></a> like GPT-o1 ”reasoning models“. But are they really reasoning?</p><p>"'Reasoning' is a semantic thing in my opinion," Kang [assistant professor in the computer science department at University of Illinois Urbana-Champaign] told The Register. "They are doing test-time scaling, which is roughly similar to what <a href="https://nerdculture.de/tags/AlphaGo" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>AlphaGo</span></a> does. I don't know how to adjudicate semantic arguments, but I would anticipate that most people would consider this reasoning."</p><p><a href="https://www.theregister.com/2024/09/13/openai_rolls_out_reasoning_o1/" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://www.</span><span class="ellipsis">theregister.com/2024/09/13/ope</span><span class="invisible">nai_rolls_out_reasoning_o1/</span></a></p><p><a href="https://nerdculture.de/tags/ChatGPT" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ChatGPT</span></a> <a href="https://nerdculture.de/tags/AI" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>AI</span></a></p>