➴➴➴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>
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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 & 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>-> <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>
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>-> No neural nets.<br>-> 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>
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>
Hacker News<p>Reflection – AlphaGo / Gemini team building superintelligent coding agents — <a href="https://www.reflection.ai/superintelligence/" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://www.</span><span class="ellipsis">reflection.ai/superintelligenc</span><span class="invisible">e/</span></a><br><a href="https://mastodon.social/tags/HackerNews" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>HackerNews</span></a> <a href="https://mastodon.social/tags/Reflection" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Reflection</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/Gemini" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Gemini</span></a> <a href="https://mastodon.social/tags/Superintelligence" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Superintelligence</span></a> <a href="https://mastodon.social/tags/CodingAgents" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>CodingAgents</span></a> <a href="https://mastodon.social/tags/AIResearch" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>AIResearch</span></a></p>
Socied@d Reticular<p><strong>Pequeños y grandes pasos hacia el imperio de la inteligencia 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»? DeepSeek da en el clavo</a></li><li><a href="https://anselmolucio.wordpress.com/2024/12/16/los-precios-dinamicos-exacerban-la-desigualdad-entre-los-consumidores-hay-que-regularlos-ya/" rel="nofollow noopener" target="_blank">Los precios dinámicos exacerban la desigualdad entre los consumidores, hay que regularlos ya</a></li><li><a href="https://anselmolucio.wordpress.com/2021/02/22/firma-contra-la-vigilancia-biometrica-masiva/" rel="nofollow noopener" target="_blank">Firma contra la vigilancia biométrica masiva</a></li></ul><p><span></span></p><p><a rel="nofollow noopener" class="hashtag u-tag u-category" href="https://anselmolucio.wordpress.com/tag/ajedrez/" target="_blank">#ajedrez</a> <a rel="nofollow noopener" class="hashtag u-tag u-category" href="https://anselmolucio.wordpress.com/tag/alphafold2/" target="_blank">#AlphaFold2</a> <a rel="nofollow noopener" class="hashtag u-tag u-category" href="https://anselmolucio.wordpress.com/tag/alphago/" target="_blank">#AlphaGo</a> <a 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" 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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>
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> >> <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>
Fortgeführter Thread
#OpenAI calls the #CoT #LLM like GPT-o1 ”reasoning models“. But are they really reasoning?
"'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 #AlphaGo does. I don't know how to adjudicate semantic arguments, but I would anticipate that most people would consider this reasoning."
https://www.theregister.com/2024/09/13/openai_rolls_out_reasoning_o1/
The Register · OpenAI's latest o1 model family can emulate 'reasoning' – but might overthink things a bitVon Thomas Claburn
When AlphaGo cracked #Go, the holy grail of game AI, it proved that there are problems that we can currently only solve via a machine learning approach.
Other approaches never managed more than mediocre play, #AlphaGo beat the world class.
Nine years later there are two types of #AI:
- Type 1 solves such problems.
- Type 2 is bullshit.
For many decades, it seemed professional #Go players had reached a hard limit on how well it is possible to play. They were not getting better.
Then, in May 2016, #DeepMind demonstrated #AlphaGo, an #AI that could beat the best human Go players.
After a few years, the weakest professional players were better than the strongest players before AI.
Escaping Flatland · After AI beat them, professional go players got better and more creativeVon Henrik Karlsson
DeepMind AI rivals the world’s smartest high schoolers at geometry - Enlarge / Demis Hassabis, CEO of DeepMind Technologies and developer of... - https://arstechnica.com/?p=1997186 #alphageometry #alphazero #deepmind #science #alphago #ai
Ars Technica · DeepMind AI rivals the world’s smartest high schoolers at geometryDeepMind solved 25 out of 30 questions—compared to 26 for a human gold medalist.
Rewatched "Alpha Go" about the Deep Mind neural network program that was able to beat the reigning world Go champion 4 games to 1.
https://www.youtube.com/watch?v=WXuK6gekU1Y
Makes me want to get a board and stones and learn to play.
Another day, another dangerous #Tesla #FSDBeta video.
You know, I have been following Tesla's FSD Beta program for a very long time.
Back around 2015 or so, the mantra was that the FSD Beta was on the cusp of an "AlphaGo" moment.
But, #AlphaGo is old news now.
#ChatGPT is white hot.
Let's explore why a system capable of partial driving automation (like FSD Beta) and automated driving systems more broadly are decidedly not at all like ChatGPT.
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