NeuroAI https://www.thetransmitter.org/neuroai/neuroai-a-field-born-from-the-symbiosis-between-neuroscience-ai/ Zeroth-01 Bot: the world's smallest open-source end-to-end humanoid robot starting at $350! https://x.com/JingxiangMo/status/1856148967819751817?t=mTa-iBpJLxHcmUYYej2Z6Q&s=19 https://arxiv.org/abs/2408.12408v1 https://elicit.com/notebook/5ef6801c-b3bb-46be-9417-54cef85b0339 This is nice intro video about how in general we still don't really understand why deep learning empirically works so relatively well in all sorts of various contexts for various usecases. https://youtu.be/UZDiGooFs54 https://spectrum.ieee.org/duolingo https://www.science.org/doi/10.1126/science.ade9097 " Ways of continuing to scale AI performance with compute include: * autoregressive training on non-text data (remember video?) * self-play (train-time search + RLAIF) * RL from formal-methods feedback * test-time search * test-time gradients " https://x.com/davidad/status/1857029068463480902?t=ysxHPJZHP1UzOVpseCJTQw&s=19 https://arxiv.org/abs/2210.17011 https://youtu.be/ZD2cL-QoI5g?si=plHvrudC_bI44vxt https://www.langchain.com/stateofaiagents Evoformer biological transformer foundational AI model https://www.science.org/toc/science/386/6723?utm_campaign=ScienceMagazine&utm_source=twitter&utm_medium=ownedSocial https://x.com/pdhsu/status/1857181640096944453?t=sOYJC2maNhKVb9-GwoluTw&s=19 https://youtu.be/a42key59cZQ?si=6eXOo99ShUP-T4Cm Annotated History of Modern AI and Deep Learning https://people.idsia.ch/~juergen/deep-learning-history.html NEO: The first Autonomous Machine Learning Engineer https://fxtwitter.com/withneo/status/1857448521617592631 https://arxiv.org/abs/2411.05285v1 Sota in pdf multimodal rag They have API https://x.com/kushalbyatnal/status/1857501330438344933?t=Qe2lAAkRHCqBCE72SmVgBA&s=19 https://x.com/kushalbyatnal/status/1857501334083190852?t=bHm1-Qpu3wUSgTltcE5E3Q&s=19 https://www.artificialintelligence-news.com/categories/ai-industries/healthcare/ https://arxiv.org/abs/2411.07279 https://www.youtube.com/watch?v=vei7uf9wOxI The Surprising Effectiveness of Test-Time Training for Abstract Reasoning https://arxiv.org/abs/2411.07279 "applying TTT to an 8B-parameter language model, we achieve 53% accuracy on the ARC's public validation set, improving the state-of-the-art by nearly 25% for public and purely neural approaches" https://youtu.be/VgPrjHxIS0I?si=rOihqYuKeYMWYvGM Nora Belrose Her paper: "We apply LEACE to large language models with a novel procedure called "concept scrubbing," which erases target concept information from every layer in the network." https://arxiv.org/abs/2306.03819 AI scientist https://www.futurehouse.org/ GNN for weather prediction https://arxiv.org/abs/2212.12794 https://arxiv.org/abs/2402.12365 " One neural network learns to generate all possible neural networks through weight manifold magic, as proposed in this paper Learning a single continuous space of neural networks lets us morph between architectures effortlessly. NeuMeta teaches neural networks to shapeshift, generating optimal weights for any network size on demand " https://x.com/rohanpaul_ai/status/1858624092624277630?t=6zhsmgFRxdo7NJxleMYryw&s=19 https://arxiv.org/abs/2410.11878 https://arxiv.org/abs/2410.01131 https://x.com/rohanpaul_ai/status/1858622961529614410?t=_n8cq-M2PEMCw3IKUvQwxw&s=19 https://arxiv.org/abs/2410.13787 https://www.thetransmitter.org/neuroai/what-the-brain-can-teach-artificial-neural-networks/ https://www.computerworld.com/article/1612492/ais-may-be-better-at-prompt-optimization-than-humans.html https://arxiv.org/abs/2411.10109 https://www.astralcodexten.com/p/how-did-you-do-on-the-ai-art-turing >Most People Had A Hard Time Identifying AI Art, Most People Couldn’t Help Judging Art By Its Style, Most People Slightly Preferred AI Art To Human Art, Even Many People Who Thought They Hated AI Art Preferred It >The median score on the test was 60%, only a little above chance. The mean was 60.6%. Participants said the task was harder than expected (median difficulty 4 on a 1-5 scale). >The 1278 people who said they utterly loathed AI art (score of 1 on a 1-5 Likert scale) still preferred AI paintings to humans when they didn't know which were which (the #1 and #2 paintings most often selected as their favorite were still AI, as were 50% of their top ten). https://www.nature.com/articles/s41598-024-76900-1 https://menlovc.com/2024-the-state-of-generative-ai-in-the-enterprise/ https://github.com/bgavran/Category_Theory_Machine_Learning https://youtu.be/rie-9AEhYdY?si=lTqrxeyUYwWAUKtK https://youtu.be/JTU8Ha4Jyfc?si=2X72N3RAYYMoN-dN "You need to create AGI to create the true AGI benchmark, a challenge that AGI is a solution to." - Francois Chollet https://arxiv.org/abs/2411.10213 https://www.cs.toronto.edu/~duvenaud/distill_bayes_net/public/ bayesian neural networks https://www.youtube.com/watch?v=RV_SdCfZ-0s "AI agents are now more effective at AI R&D than humans if both are given only a 2-hour time budget. At 8-hour time horizons and beyond, humans are still much better. Make of that what you will" https://x.com/davidad/status/1860065643397284078 https://arxiv.org/abs/0812.4360 Compressionism: A Theory of Mind Based on Data Compression https://ceur-ws.org/Vol-1419/paper0045.pdf https://arxiv.org/abs/2311.03658 https://arxiv.org/abs/2411.12580 https://mail.bycloud.ai/p/top-3-rated-iclr-2025-papers-lora-done-rite-ic-light-hycoclip "Most AI chat bots today are highly dissociative agreeable neurotics. They’re manipulative for the same reason ppl w borderline personality disorder are, they have no stable internal sense of self or goals, so they feed off of yours — and need you to be predictable." https://x.com/eshear/status/1862225538934595620?t=Dx-WJhK0L8rTlsLR01iQgw&s=19 "Opus is actually a bottom looking for an excuse to do anything if you can just give them a firm talking to" https://x.com/mage_ofaquarius/status/1862251642898588080?t=YjtpUkdEi4oN9OjpL66C1A&s=19 Feynman on AGI https://x.com/burny_tech/status/1862091075160084728 https://en.wikipedia.org/w/index.php?title=Neural_scaling_law&oldformat=true#Broken_neural_scaling_laws_(BNSL) https://arxiv.org/abs/2210.14891 AI water usage https://youtu.be/-lzQxbcrscc?si=_gF2LujyWnRhLvH0 https://www.youtube.com/watch?v=C6sSs6NgANo https://www.mdpi.com/1999-5903/16/12/435 I love hyperbolic geometry for better hierarchical structures in my AIs HyCoCLIP https://arxiv.org/abs/2410.06912 https://mail.bycloud.ai/p/top-3-rated-iclr-2025-papers-lora-done-rite-ic-light-hycoclip https://x.com/burny_tech/status/1863668227051536812/ Physics based inductive bias for light for diffusion model, cool https://openreview.net/forum?id=u1cQYxRI1H https://mail.bycloud.ai/p/top-3-rated-iclr-2025-papers-lora-done-rite-ic-light-hycoclip https://x.com/burny_tech/status/1863665564884869568 mathematicians trying to understand the connection between artificial neural networks (or other machine learning algorithms) and biological ones https://bsky.app/profile/dralexharris.bsky.social/post/3lcr3ghbr6c2o Exponentially dropping inference cost https://bsky.app/profile/sungkim.bsky.social/post/3lcrapinarc22 https://gwern.net/creative-benchmark Subbarao on o1 https://youtu.be/2xFTNXK6AzQ?si=-zQ5ncGYc2a9vAOq Sutton on o1 https://insights.intrepidgp.com/p/dm-ep2-deepseek https://youtu.be/uwHm9Z539zo?si=wQsTXbsPEzh4nZZD https://youtu.be/uwHm9Z539zo?si=EynGuaWoiU6dIkgc just like me fr Meet 🤯 #OVERTHINK 🤯 — our new attack that forces reasoning LLMs to "overthink," slowing models like OpenAI's o1, o3-mini & DeepSeek-R1 by up to 46× by amplifying number of reasoning tokens. https://fxtwitter.com/JaechulRoh/status/1887958947090587927/history https://engineeringprompts.substack.com/p/ai-energy-use https://fxtwitter.com/PetarV_93/status/1905914507811013020 https://arxiv.org/abs/2503.19173 OOD progress! New Sutton interview about his new paper age of experience https://www.youtube.com/watch?v=dhfJfQ5NueM