[[2310.06824] The Geometry of Truth: Emergent Linear Structure in Large Language Model Representations of True/False Datasets]([[2310.06824] The Geometry of Truth: Emergent Linear Structure in Large Language Model Representations of True/False Datasets]([[2310.06824] The Geometry of Truth: Emergent Linear Structure in Large Language Model Representations of True/False Datasets](https://arxiv.org/abs/2310.06824))) [NeurIPS 2023 Recap — Best Papers - Latent Space]([NeurIPS 2023 Recap — Best Papers - Latent Space](https://www.latent.space/p/neurips-2023-papers)) neurips 2023 summary nebo z pohledu bayesian mechaniky "objektivní" "ideální" v perfektních podmínkách "naučitelný" struktury, ( což nevím jestli jde ani teoreticky protože si člověk vždycky musí vybrat (subjektivní) reference frame [Reference class problem - Wikipedia]([Reference class problem - Wikipedia](https://en.wikipedia.org/wiki/Reference_class_problem)) [Reference class problem - Wikipedia]([Reference class problem - Wikipedia](https://en.wikipedia.org/wiki/Reference_class_problem)) Zeta Alpha Trends in AI - December 2023 - Gemini, NeurIPS & Trending AI Papers [Zeta Alpha Trends in AI - December 2023 - Gemini, NeurIPS & Trending AI Papers - YouTube]([Zeta Alpha Trends in AI - December 2023 - Gemini, NeurIPS & Trending AI Papers - YouTube]([Zeta Alpha Trends in AI - December 2023 - Gemini, NeurIPS & Trending AI Papers - YouTube](https://www.youtube.com/watch?v=6iLBWEP1Ols))) yannic mamba [Mamba: Linear-Time Sequence Modeling with Selective State Spaces (Paper Explained) - YouTube]([Mamba: Linear-Time Sequence Modeling with Selective State Spaces (Paper Explained) - YouTube]([Mamba: Linear-Time Sequence Modeling with Selective State Spaces (Paper Explained) - YouTube](https://www.youtube.com/watch?v=9dSkvxS2EB0))) prisoners dillema [What The Prisoner's Dilemma Reveals About Life, The Universe, and Everything - YouTube](https://www.youtube.com/watch?v=mScpHTIi-kM) If we dont open source AGI breathrough, feds will knock on our door and get it for themselves - George Hotz [The AI Alignment Debate: Can We Develop Truly Beneficial AI? (HQ version) - YouTube]([The AI Alignment Debate: Can We Develop Truly Beneficial AI? (HQ version) - YouTube](https://www.youtube.com/watch?v=iFUmWho7fBE)) [The Most Efficient Way to Destroy the Universe – False Vacuum - YouTube](https://www.youtube.com/watch?app=desktop&v=ijFm6DxNVyI) The Most Efficient Way to Destroy the Universe – False Vacuum memetic antibodies [[2306.17844] The Clock and the Pizza: Two Stories in Mechanistic Explanation of Neural Networks]([[2306.17844] The Clock and the Pizza: Two Stories in Mechanistic Explanation of Neural Networks](https://arxiv.org/abs/2306.17844)) [Quanta Magazine]([Quanta Magazine](https://www.quantamagazine.org/what-a-contest-of-consciousness-theories-really-proved-20230824/)) [Bloomberg - Are you a robot?]([Bloomberg - Are you a robot?](https://www.bloomberg.com/news/features/2023-12-19/longevity-startup-retro-biosciences-is-sam-altman-s-shot-at-life-extension)) Sam Altman-backed longevity research facility opens its doors [[2312.10794] A mathematical perspective on Transformers]([[2312.10794] A mathematical perspective on Transformers](https://arxiv.org/abs/2312.10794)) A mathematical perspective on Transformers Otherllo-GPT paper 1, Emergent World Representations: Exploring a Sequence Model Trained on a Synthetic Task: [[2210.13382] Emergent World Representations: Exploring a Sequence Model Trained on a Synthetic Task]([[2210.13382] Emergent World Representations: Exploring a Sequence Model Trained on a Synthetic Task](https://arxiv.org/abs/2210.13382)) Otherllo-GPT paper 2, Linear Latent World Models in Simple Transformers: A Case Study on Othello-GPT: [[2310.07582] Linear Latent World Models in Simple Transformers: A Case Study on Othello-GPT]([[2310.07582] Linear Latent World Models in Simple Transformers: A Case Study on Othello-GPT](https://arxiv.org/abs/2310.07582)) Neel Nanda lecture, Concrete open problems in mechanistic interpretability | Neel Nanda | EAG London 23: [Concrete open problems in mechanistic interpretability | Neel Nanda | EAG London 23 - YouTube]([Concrete open problems in mechanistic interpretability | Neel Nanda | EAG London 23 - YouTube]([Concrete open problems in mechanistic interpretability | Neel Nanda | EAG London 23 - YouTube]([Concrete open problems in mechanistic interpretability | Neel Nanda | EAG London 23 - YouTube](https://www.youtube.com/watch?v=7t9umZ1tFso)))) simulated annealing animated [Simulated Annealing Explained By Solving Sudoku - Artificial Intelligence - YouTube]([Simulated Annealing Explained By Solving Sudoku - Artificial Intelligence - YouTube](https://www.youtube.com/watch?v=FyyVbuLZav8)) Psychedelics reopen the social reward learning critical period [Psychedelics reopen the social reward learning critical period | Nature]([Psychedelics reopen the social reward learning critical period | Nature](https://www.nature.com/articles/s41586-023-06204-3)) diffusion model math [What are Diffusion Models? - YouTube]([What are Diffusion Models? - YouTube](https://www.youtube.com/watch?v=fbLgFrlTnGU)&t=262s&pp=ygUaZGlmZnVzaW9uIG1hY2hpbmUgbGVhcm5pbmc%3D) [Diffusion Models | Paper Explanation | Math Explained - YouTube]([Diffusion Models | Paper Explanation | Math Explained - YouTube](https://www.youtube.com/watch?v=HoKDTa5jHvg)&t=478s&pp=ygUaZGlmZnVzaW9uIG1hY2hpbmUgbGVhcm5pbmc%3D) [Paper page - AppAgent: Multimodal Agents as Smartphone Users]([Hugging Face – The AI community building the future.](https://huggingface.co/)papers/2312.13771) AppAgent: Multimodal Agents as Smartphone Users [Bloomberg - Are you a robot?]([Bloomberg - Are you a robot?](https://www.bloomberg.com/news/features/2023-12-19/longevity-startup-retro-biosciences-is-sam-altman-s-shot-at-life-extension)) The Most Secretive Longevity Lab Finally Opens Its Doors [Midjourney v6, Altman 'Age Reversal' and Gemini 2 - Christmas Edition - YouTube](https://www.youtube.com/watch?v=ZewqcbEXWqs) Summary of current state of RAG landscape [[2312.10997] Retrieval-Augmented Generation for Large Language Models: A Survey](https://arxiv.org/abs/2312.10997)v1 Summary of 2023 math [2023's Biggest Breakthroughs in Math - YouTube](https://www.youtube.com/watch?v=4HHUGnHcDQw) [NeurIPS 2023 Recap — Best Papers - Latent Space]([NeurIPS 2023 Recap — Best Papers - Latent Space](https://www.latent.space/p/neurips-2023-papers)) [Paper page - ReST meets ReAct: Self-Improvement for Multi-Step Reasoning LLM Agent]([Hugging Face – The AI community building the future.](https://huggingface.co/)papers/2312.10003) ReST meets ReAct: Self-Improvement for Multi-Step Reasoning LLM Agent: we define a ReAct-style LLM agent with the ability to reason and act upon external knowledge. We further refine the agent through a ReST-like method that iteratively trains on previous trajectories, employing growing-batch reinforcement learning with AI feedback for continuous self-improvement and self-distillation. [Preparedness]([Preparedness]([Preparedness](https://openai.com/safety/preparedness))) [[2312.07046] Rethinking Compression: Reduced Order Modelling of Latent Features in Large Language Models]([[2312.07046] Rethinking Compression: Reduced Order Modelling of Latent Features in Large Language Models](https://arxiv.org/abs/2312.07046)) Rethinking Compression: Reduced Order Modelling of Latent Features in Large Language Models Mám pocit že celkově AI a lidská inteligence od sebe spíš diverguje než se přibližuje v hodně aspektech, i když se v jiných přibližuje. Mám pocit spíš se od mozku oddalujeme než přibližujeme způsobem trénování, architekturou a engineering metodama (a Geoffrey Hinton, co udělal forward forward ML algorithmus inspirovaný lidským mozkem, o tom taky mluví podobně [CBMM10 Panel: Research on Intelligence in the Age of AI - YouTube]([CBMM10 Panel: Research on Intelligence in the Age of AI - YouTube]([CBMM10 Panel: Research on Intelligence in the Age of AI - YouTube]([CBMM10 Panel: Research on Intelligence in the Age of AI - YouTube]([CBMM10 Panel: Research on Intelligence in the Age of AI - YouTube](https://www.youtube.com/watch?v=Gg-w_n9NJIE))))) ) je možný že lidi jsou celkově dost neefektivní inteligence ke kterým se přibližovat víc by možná bylo neefektivní z pohledu zvětšování inteligence, ale zase to rozbíjí to kompatibilitu v myšlení, chování a jiných vzorech na [character.ai](https://beta.character.ai/) si je lidi dělaj leaderboard LLMs [LMSys Chatbot Arena Leaderboard - a Hugging Face Space by lmsys]([LMSys Chatbot Arena Leaderboard - a Hugging Face Space by lmsys]([LMSys Chatbot Arena Leaderboard - a Hugging Face Space by lmsys]([Hugging Face – The AI community building the future.](https://huggingface.co/)spaces/lmsys/chatbot-arena-leaderboard))) finetuning [Fine-tune a pretrained model]([Hugging Face – The AI community building the future.](https://huggingface.co/)docs/transformers/training) do unity [GitHub - AkiKurisu/VirtualHuman-Unity: VirtualHuman is a Unity Plugin to use LLM&&VITS easily](https://github.com/AkiKurisu/VirtualHuman-Unity) [Reddit - Dive into anything](https://www.reddit.com/r/Unity3D/comments/15wjyb7/ive_built_a_front_end_for_llm_integration_into/) [[2312.10794] A mathematical perspective on Transformers]([[2312.10794] A mathematical perspective on Transformers](https://arxiv.org/abs/2312.10794)) A mathematical perspective on Transformers - analyzing Transformers based on their interpretation as interacting particle systems, which reveals that clusters emerge in long time that's what the whole field of mechanistic interpretability is about [Concrete open problems in mechanistic interpretability | Neel Nanda | EAG London 23 - YouTube]([Concrete open problems in mechanistic interpretability | Neel Nanda | EAG London 23 - YouTube]([Concrete open problems in mechanistic interpretability | Neel Nanda | EAG London 23 - YouTube]([Concrete open problems in mechanistic interpretability | Neel Nanda | EAG London 23 - YouTube](https://www.youtube.com/watch?v=7t9umZ1tFso)))) [VideoPoet: A large language model for zero-shot video generation – Google Research Blog](https://blog.research.google/2023/12/videopoet-large-language-model-for-zero.html) google video multimodal generation VideoPoet Memory]([Hugging Face – The AI community building the future.](https://huggingface.co/)papers/2312.11514) Apple announces LLM in a flash: Efficient Large Language Model Inference with Limited Memory [PowerInfer: Fast Large Language Model Serving with a Consumer-Grade GPU [pdf] | Hacker News](https://news.ycombinator.com/item?id=38701822) PowerInfer: Fast Large Language Model Serving with a Consumer-Grade GPU [[2307.14804] Collective behavior from surprise minimization]([[2307.14804] Collective behavior from surprise minimization]([[2307.14804] Collective behavior from surprise minimization](https://arxiv.org/abs/2307.14804))) machine learning neural fields Generalised Implicit Neural Representations [[2205.15674] Generalised Implicit Neural Representations](https://arxiv.org/abs/2205.15674) [Dr. Daniele Grattarola at NeurIPS - Generalised Implicit Neural Representations - YouTube]([Dr. Daniele Grattarola at NeurIPS - Generalised Implicit Neural Representations - YouTube](https://www.youtube.com/watch?v=v5NysEyZkl0)) [Dr. Daniele Grattarola at NeurIPS - Generalised Implicit Neural Representations - YouTube]([Dr. Daniele Grattarola at NeurIPS - Generalised Implicit Neural Representations - YouTube](https://www.youtube.com/watch?v=v5NysEyZkl0)) diffusion models for molecule synthesis [Etched | The World's First Transformer Supercomputer](https://www.etched.ai/) Transformer hardware [Mixtral is Now 100% Uncensored 😈 | Introducing Dolphin 2.5- Mixtral 🐬 - YouTube](https://youtu.be/SGkaWMDKM9g?si=tnmvHXVJGgVOoHGx) https://twitter.com/4Maciejko/status/1736745951442678239?t=BESroQa1aXHXH3_Q6kOvBA&s=19 [The Information Theory of Aging | Nature Aging]([The Information Theory of Aging | Nature Aging]([The Information Theory of Aging | Nature Aging](https://www.nature.com/articles/s43587-023-00527-6))) math of spacetime [ChatGPT]([ChatGPT](https://chat.openai.com/share/bf710fb0-a7f7-4c15-9aaf-92d7430df255)) LLM leader board [LMSys Chatbot Arena Leaderboard - a Hugging Face Space by lmsys]([LMSys Chatbot Arena Leaderboard - a Hugging Face Space by lmsys]([LMSys Chatbot Arena Leaderboard - a Hugging Face Space by lmsys]([Hugging Face – The AI community building the future.](https://huggingface.co/)spaces/lmsys/chatbot-arena-leaderboard))) Also it's interesting that France in EU is open source AI king instead of San Francisco in America. https://twitter.com/rohanpaul_ai/status/1736827830971867312 [Preparedness]([Preparedness]([Preparedness](https://openai.com/safety/preparedness))) https://twitter.com/burny_tech/status/1736857487008260314 [My techno-optimism]([My techno-optimism]([My techno-optimism]([My techno-optimism]([My techno-optimism](https://vitalik.eth.limo/general/2023/11/27/techno_optimism.html))))) Tohle je fajn seznam risků AI [AI Risks that Could Lead to Catastrophe | CAIS]([AI Risks that Could Lead to Catastrophe | CAIS]([Center for AI Safety (CAIS)]([Center for AI Safety (CAIS)](https://www.safe.ai/))ai-risk)) average AI researcher monitor [Imgur: The magic of the Internet](https://imgur.com/6R5ftmK) [[2312.07046] Rethinking Compression: Reduced Order Modelling of Latent Features in Large Language Models]([[2312.07046] Rethinking Compression: Reduced Order Modelling of Latent Features in Large Language Models](https://arxiv.org/abs/2312.07046)) Rethinking Compression: Reduced Order Modelling of Latent Features in Large Language Models [Preparedness]([Preparedness]([Preparedness](https://openai.com/safety/preparedness))) [Weak-to-strong generalization](https://openai.com/research/weak-to-strong-generalization) [Dr. Michael Levin on Technology Approach to Mind Everywhere (TAME) and AGI Agency - YouTube]([Dr. Michael Levin on Technology Approach to Mind Everywhere (TAME) and AGI Agency - YouTube]([Dr. Michael Levin on Technology Approach to Mind Everywhere (TAME) and AGI Agency - YouTube](https://www.youtube.com/watch?v=Q_csRdjl4rU))) Dr. Michael Levin on Technology Approach to Mind Everywhere (TAME) and AGI Agency Information theory of aging [The Information Theory of Aging | Nature Aging]([The Information Theory of Aging | Nature Aging]([The Information Theory of Aging | Nature Aging](https://www.nature.com/articles/s43587-023-00527-6))) https://twitter.com/davidasinclair/status/1735765731944305065 [Concrete Steps to Get Started in Transformer Mechanistic Interpretability — Neel Nanda]([Concrete Steps to Get Started in Transformer Mechanistic Interpretability — Neel Nanda]([Concrete Steps to Get Started in Transformer Mechanistic Interpretability — Neel Nanda]([Neel Nanda](https://www.neelnanda.io/)mechanistic-interpretability/getting-started))) [Learning Transformer Programs | OpenReview]([Learning Transformer Programs | OpenReview](https://openreview.net/forum?id=Pe9WxkN8Ff)) [Learning Transformer Programs | OpenReview]([Learning Transformer Programs | OpenReview](https://openreview.net/forum?id=Pe9WxkN8Ff)) autism [Imgur: The magic of the Internet](https://imgur.com/aXzDptO) [[2306.17844] The Clock and the Pizza: Two Stories in Mechanistic Explanation of Neural Networks]([[2306.17844] The Clock and the Pizza: Two Stories in Mechanistic Explanation of Neural Networks](https://arxiv.org/abs/2306.17844)) The Clock and the Pizza: Two Stories in Mechanistic Explanation of Neural Networks [Generative language modeling for automated theorem proving](https://openai.com/research/generative-language-modeling-for-automated-theorem-proving) curvature of spacetime in general relativity, incompatibility of general relativity with quantum mechanics, math breaking at black hole singularities [ChatGPT]([ChatGPT](https://chat.openai.com/share/bf710fb0-a7f7-4c15-9aaf-92d7430df255)) [[2210.13382] Emergent World Representations: Exploring a Sequence Model Trained on a Synthetic Task]([[2210.13382] Emergent World Representations: Exploring a Sequence Model Trained on a Synthetic Task](https://arxiv.org/abs/2210.13382)) [[2310.07582] Linear Latent World Models in Simple Transformers: A Case Study on Othello-GPT]([[2310.07582] Linear Latent World Models in Simple Transformers: A Case Study on Othello-GPT](https://arxiv.org/abs/2310.07582)) OtherlloGPT learns emergent nonlinear internal representation of the board state automated circuit discovery [A Walkthrough of Automated Circuit Discovery w/ Arthur Conmy Part 1/3 - YouTube]([A Walkthrough of Automated Circuit Discovery w/ Arthur Conmy Part 1/3 - YouTube]([A Walkthrough of Automated Circuit Discovery w/ Arthur Conmy Part 1/3 - YouTube](https://www.youtube.com/watch?v=dn4GqR0DCx8))) they automated [[2211.00593] Interpretability in the Wild: a Circuit for Indirect Object Identification in GPT-2 small](https://arxiv.org/abs/2211.00593) learned Circuit for Indirect Object Identification in GPT-2 small, pretty complex interacting head circuits machinery [Imgur: The magic of the Internet](https://imgur.com/IXh43wo) , which fills marry in this task [Imgur: The magic of the Internet](https://imgur.com/m0DajC4) [Concrete open problems in mechanistic interpretability | Neel Nanda | EAG London 23 - YouTube](https://youtu.be/7t9umZ1tFso?si=wK7asKcCTxOBbmI1&t=2850) [Representation Engineering: A Top-Down Approach to AI Transparency]([Representation Engineering: A Top-Down Approach to AI Transparency]([Representation Engineering: A Top-Down Approach to AI Transparency]([Representation Engineering: A Top-Down Approach to AI Transparency]([Representation Engineering: A Top-Down Approach to AI Transparency]([Representation Engineering: A Top-Down Approach to AI Transparency]([Representation Engineering: A Top-Down Approach to AI Transparency]([Representation Engineering: A Top-Down Approach to AI Transparency](https://www.ai-transparency.org/)))))))) [Towards Monosemanticity: Decomposing Language Models With Dictionary Learning]([Towards Monosemanticity: Decomposing Language Models With Dictionary Learning]([Towards Monosemanticity: Decomposing Language Models With Dictionary Learning]([Towards Monosemanticity: Decomposing Language Models With Dictionary Learning]([Towards Monosemanticity: Decomposing Language Models With Dictionary Learning]([Towards Monosemanticity: Decomposing Language Models With Dictionary Learning]([Towards Monosemanticity: Decomposing Language Models With Dictionary Learning]([Towards Monosemanticity: Decomposing Language Models With Dictionary Learning]([Towards Monosemanticity: Decomposing Language Models With Dictionary Learning]([Towards Monosemanticity: Decomposing Language Models With Dictionary Learning](https://transformer-circuits.pub/2023/monosemantic-features/index.html)))))))))) [A Walkthrough of Automated Circuit Discovery w/ Arthur Conmy Part 1/3 - YouTube]([A Walkthrough of Automated Circuit Discovery w/ Arthur Conmy Part 1/3 - YouTube]([A Walkthrough of Automated Circuit Discovery w/ Arthur Conmy Part 1/3 - YouTube](https://www.youtube.com/watch?v=dn4GqR0DCx8))) I hope this automated circuit discovery will be automated more and more and scale to GPT4like models! LLMs explaining neurons in LLMs is also promising! [Language models can explain neurons in language models]([Language models can explain neurons in language models]([Language models can explain neurons in language models]([Language models can explain neurons in language models](https://openai.com/research/language-models-can-explain-neurons-in-language-models))))