Create a gigantic detailed iceberg of machine learning Create a gigantic map of as much robotics as possible Stanford machine learning [Stanford CS229: Machine Learning I Spring 2022 - YouTube](https://www.youtube.com/playlist?list=PLoROMvodv4rNyWOpJg_Yh4NSqI4Z4vOYy) Stanford machine learning [Stanford CS229: Machine Learning Full Course taught by Andrew Ng | Autumn 2018 - YouTube](https://www.youtube.com/playlist?list=PLoROMvodv4rMiGQp3WXShtMGgzqpfVfbU) Stanford transformers [Stanford CS25 - Transformers United - YouTube](https://www.youtube.com/playlist?list=PLoROMvodv4rNiJRchCzutFw5ItR_Z27CM) Stanford generative models including diffusion [Stanford CS236: Deep Generative Models I 2023 I Stefano Ermon - YouTube](https://www.youtube.com/playlist?list=PLoROMvodv4rPOWA-omMM6STXaWW4FvJT8) Stanford deep learning [Stanford CS230: Deep Learning | Autumn 2018 - YouTube](https://www.youtube.com/playlist?list=PLoROMvodv4rOABXSygHTsbvUz4G_YQhOb) Karpathy neural networks zero to hero [Neural Networks: Zero to Hero - YouTube](https://www.youtube.com/playlist?list=PLAqhIrjkxbuWI23v9cThsA9GvCAUhRvKZ) Stanford natural language processing with deep learning [Stanford CS224N: Natural Language Processing with Deep Learning | 2023 - YouTube](https://www.youtube.com/playlist?list=PLoROMvodv4rMFqRtEuo6SGjY4XbRIVRd4) MIT deep learning [MIT 6.S191 (2023): Introduction to Deep learning - YouTube](https://www.youtube.com/playlist?list=PLTZ1bhP8GBuTCqeY19TxhHyrwFiot42_U) Stanford artificial intelligence [Stanford CS221: Artificial Intelligence: Principles and Techniques | Autumn 2019 - YouTube](https://www.youtube.com/playlist?list=PLoROMvodv4rO1NB9TD4iUZ3qghGEGtqNX) Stanford machine learning with graphs [Stanford CS224W: Machine Learning with Graphs - YouTube](https://www.youtube.com/playlist?list=PLoROMvodv4rPLKxIpqhjhPgdQy7imNkDn) Stanford natural language understanding [Stanford XCS224U: Natural Language Understanding I Spring 2023 - YouTube](https://www.youtube.com/playlist?list=PLoROMvodv4rOwvldxftJTmoR3kRcWkJBp) Stanford reinforcement learning [Stanford CS234: Reinforcement Learning | Winter 2019 - YouTube](https://www.youtube.com/playlist?list=PLoROMvodv4rOSOPzutgyCTapiGlY2Nd8u) Stanford meta-learning [Stanford CS330: Deep Multi-Task and Meta Learning I Autumn 2022 - YouTube](https://www.youtube.com/playlist?list=PLoROMvodv4rNjRoawgt72BBNwL2V7doGI) Stanford artificial intelligence [Artificial Intelligence - YouTube](https://www.youtube.com/playlist?list=PLoROMvodv4rPgrvmYbBrxZCK_GwXvDVL3) Stanford machine learning theory [Stanford CS229M: Machine Learning Theory - Fall 2021 - YouTube](https://www.youtube.com/playlist?list=PLoROMvodv4rP8nAmISxFINlGKSK4rbLKh) Stanford computer vision [CS231n Winter 2016 - YouTube](https://www.youtube.com/playlist?list=PLkt2uSq6rBVctENoVBg1TpCC7OQi31AlC) [Deep Learning - Stanford CS231N - YouTube](https://www.youtube.com/playlist?list=PLSVEhWrZWDHQTBmWZufjxpw3s8sveJtnJ) Stanford statistics [Stanford CS109 Introduction to Probability for Computer Scientists I 2022 I Chris Piech - YouTube](https://www.youtube.com/playlist?list=PLoROMvodv4rOpr_A7B9SriE_iZmkanvUg) Stanford methods in AI [Stanford CS221: Artificial Intelligence: Principles and Techniques | Autumn 2019 - YouTube](https://www.youtube.com/playlist?list=PLoROMvodv4rO1NB9TD4iUZ3qghGEGtqNX) [The Biggest Ideas in the Universe! - YouTube](https://www.youtube.com/playlist?list=PLrxfgDEc2NxZJcWcrxH3jyjUUrJlnoyzX) Stanford MIT robotics [Underactuated Robotics, Spring 2021 - YouTube](https://www.youtube.com/playlist?list=PLkx8KyIQkMfUmB3j-DyP58ThDXM7enA8x) [Robotic Manipulation, Fall 2022 - YouTube](https://www.youtube.com/playlist?list=PLkx8KyIQkMfUSDs2hvTWzaq-cxGl8Ha69) [Lecture Collection | Introduction to Robotics - YouTube](https://www.youtube.com/playlist?list=PL65CC0384A1798ADF) [Stanford AA289 - Robotics and Autonomous Systems Seminar - YouTube](https://www.youtube.com/playlist?list=PLoROMvodv4rMeercb-kvGLUrOq4HR6BZD) [Applied Robot Design - Stanford - YouTube](https://www.youtube.com/playlist?list=PLN1iOWWHLJz3ndzRIvpbby75G2_2pYYrL) MIT machine learning [Broderick: Machine Learning, MIT 6.036 Fall 2020 - YouTube](https://www.youtube.com/playlist?list=PLxC_ffO4q_rW0bqQB80_vcQB09HOA3ClV) [Machine Learning Course MIT OpenCourseWare - YouTube](https://www.youtube.com/playlist?list=PLnvKubj2-I2LhIibS8TOGC42xsD3-liux) MIT efficient machine learning [EfficientML.ai Lecture, Fall 2023, MIT 6.5940 - YouTube](https://www.youtube.com/playlist?list=PL80kAHvQbh-pT4lCkDT53zT8DKmhE0idB) MIT linear algebra in machine learning [MIT 18.065 Matrix Methods in Data Analysis, Signal Processing, and Machine Learning, Spring 2018 - YouTube](https://www.youtube.com/playlist?list=PLUl4u3cNGP63oMNUHXqIUcrkS2PivhN3k) Principles of Deep Learning Theory [[2106.10165] The Principles of Deep Learning Theory](https://arxiv.org/abs/2106.10165) [The Principles of Deep Learning Theory - Dan Roberts - YouTube](https://www.youtube.com/watch?v=YzR2gZrsdJc) [Introduction to Deep Learning Theory - YouTube](https://www.youtube.com/watch?v=pad023JIXVA) Active Inference book [Active Inference](https://mitpress.mit.edu/9780262045353/active-inference/) Geometric deep learning [Geometric Deep Learning - Grids, Groups, Graphs, Geodesics, and Gauges](https://geometricdeeplearning.com/) Mechanistic intepretability [Mechanistic Interpretability — Neel Nanda](https://www.neelnanda.io/mechanistic-interpretability) Topological data analysis [Analysis: Topological data analysis - YouTube](https://www.youtube.com/playlist?list=PLzERW_Obpmv_UW7RgbZW4Ebhw87BcoXc7) Stanford physics Susskind [Course Catalogue | The Theoretical Minimum](https://theoreticalminimum.com/courses) Physics Sean Carroll [The Biggest Ideas in the Universe! - YouTube](https://www.youtube.com/playlist?list=PLrxfgDEc2NxZJcWcrxH3jyjUUrJlnoyzX) AI and machine learning lectures from Stanford and MIT are my Netflix [Serotonin’s Hidden Power: How Psychedelics Are Opening New Doors in Mental Health](https://scitechdaily.com/serotonins-hidden-power-how-psychedelics-are-opening-new-doors-in-mental-health/) [Structural pharmacology and therapeutic potential of 5-methoxytryptamines | Nature](https://www.nature.com/articles/s41586-024-07403-2) [A non-hallucinogenic psychedelic analogue with therapeutic potential | Nature](https://www.nature.com/articles/s41586-020-3008-z) Do you approximate your world model by affine transformations with nonlinear activation functions, polynomials, sines, pseudorandom noise signals (reservoir computing), or some superexotic magic that is approximating arbitrary functions and generalizing that allows you to venture into out of distribution void beyond classical language comprehension? of course the fundamental truth of the universe is that gender is macrospins in magnetism-inspired quantum-mechanical truth of gender fluidity [[2401.15264] Magnetism-Inspired Quantum-Mechanical Model of Gender Fluidity](https://arxiv.org/abs/2401.15264) Mathamphetamine [Brain Really Uses Quantum Effects, New Study Finds - YouTube](https://youtu.be/R6G1D2UQ3gg?si=0fI493q9H8QRlVLI) Sabine Penrose https://pubs.acs.org/doi/10.1021/acs.jpcb.3c07936 [[2405.04967] MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures](https://arxiv.org/abs/2405.04967) https://www.reddit.com/r/MachineLearning/comments/myfirg/d_why_are_neural_networks_better_than_polynomial/ [[2311.12786] Mechanistically analyzing the effects of fine-tuning on procedurally defined tasks](https://arxiv.org/abs/2311.12786) The Top ML Papers of the Week (May 6 - May 12): - xLSTM - DrEureka - AlphaFold 3 - DeepSeek-V2 - Consistency LLMs - AlphaMath Almost Zero https://twitter.com/dair_ai/status/1789640664906342583?t=TExcfpOBhUtdMNMZ8xvT9w&s=19 [[2405.03520v1] Is Sora a World Simulator? A Comprehensive Survey on General World Models and Beyond](https://arxiv.org/abs/2405.03520v1) Hypercentralization of power thanks to superadvanced technology including AI being in the hands of fewer and fewer people that are in many cases more selfinterested and not aligned with all of sentience, is much more probable bigger current threat than rogue superintelligent AI. I think rogue superintelligent AI causing nuclear bomb level damage is too far off in the future. I think in more near term we will see AI misalignment as AIs doing random stuff that may be destructive, but on a similar level like current technology can be destructive when it breaks, or when used by bad agents as it's dual use, but it won't be nuclear bomb level damage, and defensive and benevolent uses of AI technology will play a role too. Like when ChatGPT suddenly started outputting random stuff for a day. I think the advantages of AI technology overall outweigh the disadvantages, but it has to not get concentrated in the hands of few overly selfinterested agents. Apes teaching sand to think [[2405.06624] Towards Guaranteed Safe AI: A Framework for Ensuring Robust and Reliable AI Systems](https://arxiv.org/abs/2405.06624) [Distributed representations of prediction error signals across the cortical hierarchy are synergistic | Nature Communications](https://www.nature.com/articles/s41467-024-48329-7) [[2312.08550] Harmonics of Learning: Universal Fourier Features Emerge in Invariant Networks](https://arxiv.org/abs/2312.08550) the problem with how some people talk about language models is that rather than seeing them as a new category of word-remixers, analogy-alchemists and concept-mixologists, they treat them as search engines and oracles. and instead of debugging their mental model's code, they lament that their misplaced expectations aren't met [GitHub - Technion-Kishony-lab/data-to-paper: data-to-paper: Backward-traceable AI-driven scientific research](https://github.com/Technion-Kishony-lab/data-to-paper) [[2303.02636] An abelian ambient category for behaviors in algebraic systems theory](https://arxiv.org/abs/2303.02636) Period table of simple groups https://www.reddit.com/r/math/s/M20Wjw4yNH Let's put everything that's missing in current AI systems into a cost function as an addition to the current one, like generalization, long term planning, coherence, agency,... Osobně to vidím tak že dosavadní mainstream systémy tím jak jsou hlavně právě curve fitters datasetu syntetizující/kombinující nauceny zkompresovany programy (co jsou ale sem tam fuzzy), což ukazuje relativně slabou, ale existující generalizaci. Ale sem tam tu postuju různý pokusy o generalizaci přes víc systematicky generalizující trénovací data a trénování, nebo alternativní architektury ukazující lepší potenciální generalizaci Fitting complex valued curves in a superposition https://www.youtube.com/results?search_query=algebraic+topology+lectures Imaginary numbers should be called rotation numbers or something similar [Anti-Aging Millionaire: This Habit Ruins Men! - Biohacking Routine To Feel 18 Again | Bryan Johnson - YouTube](https://youtu.be/j_AtQ6N4jQc?si=D2hC7kltVigFt3Jm) [Bryan Johnson's Blueprint for Longevity - YouTube](https://youtu.be/YvSX0rLyERs?si=r229rhiwJ_GeAo22) [Don't Die Network State: Bryan Johnson & Balaji Srinivasan - TOKEN2049 Dubai 2024 - YouTube](https://youtu.be/5Xj_qbd1SEI?si=rWJVM0Yx8jc_aCyA) [Diffusion Models | Paper Explanation | Math Explained - YouTube](https://youtu.be/HoKDTa5jHvg?si=ZC4uW6nUMBqLwNua) [GitHub - mintisan/awesome-kan: A comprehensive collection of KAN(Kolmogorov-Arnold Network)-related resources, including libraries, projects, tutorials, papers, and more, for researchers and developers in the Kolmogorov-Arnold Network field.](https://github.com/mintisan/awesome-kan?fbclid=IwZXh0bgNhZW0CMTEAAR3sWirIlgvvLxxkGUKGjSj_VpKaJ3W0yHb2AECZ3tDlIg5OUOabaGQPteg_aem_AQgYK4DHK81F7yLyxp8ZrB1hCHY7SMKcemVqAMqLAKuKrxk5hytO1Gv81fG2sjuMQOxmWf6y9Vn7Q3LSsnbhzNoz) [[2402.08871] Position: Topological Deep Learning is the New Frontier for Relational Learning](https://arxiv.org/abs/2402.08871) Being is written in mathematics How many brains would it take to simulate a computer? [[2405.04798] From LLMs to Actions: Latent Codes as Bridges in Hierarchical Robot Control](https://arxiv.org/abs/2405.04798) OpenDevin CodeAct 1.0 https://twitter.com/xingyaow_/status/1787862432888545665 [Introducing OpenDevin CodeAct 1.0, a new State-of-the-art in Coding Agents](https://xwang.dev/blog/2024/opendevin-codeact-1.0-swebench/) Expand your mind with (applied or in the future applied) math infinitely. It's an infinite landscape. "Instead of trying to produce a programme to simulate the adult mind, why not rather try to produce one which simulates the child's?" - Alan Turing, 1950 - “I cannot make you understand. I cannot make anyone understand what is happening inside me. I cannot even explain it to myself.” - Franz Kafka, The Metamorphosis "The limits of my language means the limits of my world." - Ludwig Wittgenstein, Tractatus Logico-Philosophicus [Wealth Inequality under Post-Labor Economics - YouTube](https://www.youtube.com/watch?v=44IK8ujoJA4) [Joscha Bach on the Bible, emotions and how AI could be wonderful. - YouTube](https://www.youtube.com/watch?v=4H1L2Bpltbs) Clustering in machine learning is automated autistic urge to put everything into categories Brain Leading Eigenvector Dynamics Algorithm (LEiDA) https://twitter.com/Joana_Cabral__/status/1788324741536747977 [Deep learning-guided discovery of an antibiotic targeting Acinetobacter baumannii | Nature Chemical Biology](https://www.nature.com/articles/s41589-023-01349-8) [The Eighty Five Percent Rule for optimal learning | Nature Communications](https://www.nature.com/articles/s41467-019-12552-4) [Neonatal brain dynamic functional connectivity in term and preterm infants and its association with early childhood neurodevelopment | Nature Communications](https://www.nature.com/articles/s41467-023-44050-z) [Beren Millidge: Learning in the brain beyond backprop - YouTube](https://www.youtube.com/watch?v=jN1mUSJ9uiE) [New AI Tools Predict How Life’s Building Blocks Assemble | Quanta Magazine](https://www.quantamagazine.org/new-ai-tools-predict-how-lifes-building-blocks-assemble-20240508/) [[2404.03622] Mind's Eye of LLMs: Visualization-of-Thought Elicits Spatial Reasoning in Large Language Models](https://arxiv.org/abs/2404.03622) [GitHub - a-real-ai/pywinassistant: The first open source Large Action Model generalist Artificial Narrow Intelligence that controls completely human user interfaces by only using natural language. PyWinAssistant utilizes Visualization-of-Thought Elicits Spatial Reasoning in Large Language Models.](https://github.com/a-real-ai/pywinassistant) I want democratized intelligence, but I also want nonmonopolized decentralized intelligence in many different forms Hear me out xLSTMs combined with KAN and Jamba (Transformer (MoE) x Mamba) and RWKW with a sprinkle of diffusion and graphs https://www.cell.com/trends/cognitive-sciences/fulltext/S1364-6613(23)00283-8 "I propose generalized AI anxiety disorder! I still kind of have it, but relatively less compared to the past when first getting existential risk pilled. Generalized AI anxiety disorder generalizes to general generalized x-risk/s-risk/risk anxiety disorder. Lots of risks are still very real, but we have to make certain tradeoffs. I think that centralization of power/wealth/intelligence/abundance/technology by psychopathic/sociopathic/selfish people not caring for sentience as a whole is currently the biggest civilizational risk and we should fight it!" "Big chunk of proponents of open source and antiregulation of AI see as biggest risk centralization of power/wealth/intelligence/abundance/technology by psychopathic/sociopathic/selfish people hoarding just for themselves not caring for sentience as a whole trying to monopolize by regulatory capture killing all potential competition and other innovation" [Age at onset of mental disorders worldwide: large-scale meta-analysis of 192 epidemiological studies | Molecular Psychiatry](https://www.nature.com/articles/s41380-021-01161-7) [UK toddler has hearing restored in world first gene therapy trial | Medical research | The Guardian](https://www.theguardian.com/science/article/2024/may/09/uk-toddler-has-hearing-restored-in-world-first-gene-therapy-trial) https://twitter.com/lateinteraction/status/1788241002035388917?t=IKUQVmM6MRQw2wBqPm_cgw&s=19 [GitHub - stanfordnlp/dspy: DSPy: The framework for programming—not prompting—foundation models](https://github.com/stanfordnlp/dspy) Self supervised learning [THE GHOST IN THE MACHINE - YouTube](https://youtu.be/axuGfh4UR9Q?si=zswHF5qOzuvwLCzJ) [Google DeepMind CEO on Drug Discovery, Hype, Isomorphic - YouTube](https://youtu.be/RIrnMVDM_N8?si=2siv3gJJjcA_YuSh) [Representationalism and rationality: why mental representation is real | Synthese](https://link.springer.com/article/10.1007/s11229-024-04540-z) [Your request has been blocked. This could be due to several reasons.](https://www.microsoft.com/en-us/worklab/work-trend-index/ai-at-work-is-here-now-comes-the-hard-part/) Void voiding voided voids Illusion is an illusion Beyond the beyond Neither qualia nor nonqualia Nonlocally embedded in infinitely big space of all possible empirical mathematical abstractions I like qualia realist empirical physicalism for engineering. But for trying to grasp reality, neither zero nor one nor many fundamental substances. Any thing attempting to ground reality in any way neither solidifies nor dissolves into neither ground nor groundlessness. I often wonder if interconnected plants, trees, mushrooms or bigger nature's ecosystems could maybe form a conscious entity with much more diverse experiences in vaster spaciotemporal scales. https://twitter.com/algekalipso/status/1788585131214844235?t=p0zLA6dS3Bc26Oo1NxL3rQ&s=19 https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10909201/ [Measuring the Persuasiveness of Language Models \ Anthropic](https://www.anthropic.com/news/measuring-model-persuasiveness) [Oscar Ferrante- Adversarial Collaboration to Critically Evaluate Theories of Consciousness - YouTube](https://www.youtube.com/watch?v=jCrX072M76g) [Why Does Diffusion Work Better than Auto-Regression? - YouTube](https://www.youtube.com/watch?v=zc5NTeJbk-k) diffusion vs auto-regression Agents landscape https://twitter.com/chiefaioffice/status/1788666290388787429?t=yYrHPHBmO0wi6-fdX49eyg&s=19 https://twitter.com/chiefaioffice/status/1788684865648390190?t=-JCjDAF89bkXy54KwX2giQ&s=19 You're not a separate entity but a physically and memetically open system that is deeply relationally embedded in the societal superorganism embedded in a universe hyperganism graspable as a certain form of a global neural network https://twitter.com/plain_simon/status/1788679001063530943?t=Wlg4N3E_69pKRVbsFVMmEg&s=19 [[2405.03599] Proof of the geometric Langlands conjecture I: construction of the functor](https://arxiv.org/abs/2405.03599) [[2405.03648] Proof of the geometric Langlands conjecture II: Kac-Moody localization and the FLE](https://arxiv.org/abs/2405.03648) [The Geometric Langlands Conjecture - Sam Raskin - YouTube](https://youtu.be/1emC3ncjblU?si=C6DYjnlafkfdQTz3) Deep learning x biology https://www.sciencedirect.com/science/article/abs/pii/S1389041724000408 [Game Theory, False Narratives, Survival, Life Advice - Daniel Schmachtenberger | BSP# 20 - YouTube](https://youtu.be/LSx8j8lSewA?si=NACQtEy6jZ2XHXYJ) I love paradigm shifting science and deep tech and spirituality and scepticism against those in power but I hate when people get antiscientific or dismiss all advantages of things while only focusing on the negatives "Talking to someone is like talking to a customer service representative of a large org. The words are trying to convey a unified front of sense-making, but really they are the result of a compromise of a lot of within-org diplomatic agreements. When someone says "I'll have to think about it" they mean "I'll let the information propagate and see what the subagentic networks as a whole thinks about it, I'm just the customer service representative right now, you know?"" https://twitter.com/algekalipso/status/1788724115614134414?t=6prU-DgXqHwzud7AnsRBVA&s=19 Fluidly centralizing/decentralizing collectively intelligent swarm of unifying/resonating/synchronizing/desynchronizing/dividing topological subagentic pockets forming subsymbolic hiearchies/hetearchies/fuzzy metahypergraphs with probabilistic bayesian message passing machine-learning tool which discovered new partial differential equations obeying conservation laws [[2405.04484] OptPDE: Discovering Novel Integrable Systems via AI-Human Collaboration](https://arxiv.org/abs/2405.04484) https://twitter.com/thesubhashk/status/1788643691231576162?t=TpYb4xV33xkQ8oSt-cNyGg&s=19 https://twitter.com/tegmark/status/1788675307743924322?t=89V1YXO8vFI8Jfexr9u5BQ&s=19 [Benchmarking methods for mapping functional connectivity in the brain | bioRxiv](https://www.biorxiv.org/content/10.1101/2024.05.07.593018v1.abstract?%3Fcollection=) Mind upload is closer https://www.science.org/doi/10.1126/science.adk4858?utm_source=sfmc&utm_medium=email&utm_content=alert&utm_campaign=SCIeToc&et_rid=1061470110&et_cid=5207966 Google research [Mapping the Brain - YouTube](https://youtu.be/VSG3_JvnCkU?si=3RG8IehR9RAfdO8M) " (Verse 1) The model's learning on its own tonight, Feed it data, let it train till it gets it right. Every neuron's firing, yeah, it starts to click, Optimization's on, no more arithmetic. (Pre-Chorus) And now I'm saying like, "Girl, you know I want your weights, Your learning rate is something for this task so great." "Train a model daily, run it through the night, Now my layers deep, predictions coming right." (Chorus) I'm in love with deep learning, Push the data, watch the metrics start converging. Say, "Boy, let's not talk too much, Grab your dataset and put that model to the test." I'm in love with the neural nets, We push and pull like a function in regress. Although my heart is falling too, I'm in love with deep learning. (Verse 2) One week in and we're still tuning hyperparams, We're going models deep, results lookin' like charms. Every day discovering something brand new, I'm in love with deep learning. (Bridge) Come on, be my optimizer, come on, Come on, be my optimizer, come on. Every iteration, let's improve it, Make the cost go down, we can do it. (Chorus) I'm in love with deep learning, Push the data, watch the metrics start converging. Say, "Boy, let's not talk too much, Grab your dataset and put that model to the test." I'm in love with the neural nets, We push and pull like a function in regress. Although my heart is falling too, I'm in love with deep learning. " My new subagents to my outdated mental subagents with empirically falsified hypotheses: you are trying to solve the wrong problem using the wrong methods based on a wrong model of the world derived from poor thinking and unfortunately all of your mistakes have failed to cancel out [Retuning of hippocampal representations during sleep | Nature](https://www.nature.com/articles/s41586-024-07397-x?utm_medium=Social&utm_campaign=nature&utm_source=Twitter#Echobox=1715249266) EA math cult? https://twitter.com/LouisAnslow/status/1789751075026661855?t=NdFFek8-p0dS6I_q5BDtag&s=19 People find it hard to grasp the concept that technology has gotten better at the same time as the social organization of society has gotten (a lot) worse https://twitter.com/RokoMijic/status/1789773740428931273?t=o4K8oei0ZO-GDUyUVuXTdA&s=19 https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8218718/ [Smart Biology](https://smart-biology.com) https://twitter.com/SmartBiology3D/status/1790019191996592346 https://www.techrxiv.org/users/779030/articles/914686-benecial-agi-care-and-collaboration-are-all-you-need [1] https://journals.aps.org/.../abs.../10.1103/PhysRevD.27.2885 [2] [[2206.10780] An Algebra of Observables for de Sitter Space](https://arxiv.org/abs/2206.10780) [3] [[2405.00114] Gravitational entropy is observer-dependent](https://arxiv.org/abs/2405.00114) Unitree robot G1 Humanoid Agent AI Avatar $16K https://fxtwitter.com/UnitreeRobotics/status/1789931753974517820 https://www.marktechpost.com/2024/05/12/how-chain-of-thought-makes-transformers-smarter/ [The AI Denial Train Should Stop](https://www.forbes.com/sites/steveandriole/2024/05/13/the-ai-denial-train-should-stop/?sh=4dd6d73a8f88) Wake up babe yet another transformer killer just dropped "memory mosaics perform as well or better than transformers" arxiv.org/abs/2405.06394 [GitHub - valeman/awesome-conformal-prediction: A professionally curated list of awesome Conformal Prediction videos, tutorials, books, papers, PhD and MSc theses, articles and open-source libraries.](https://github.com/valeman/awesome-conformal-prediction) [An Elegant Structural Overview of Modern Theoretical Physics - YouTube](https://www.youtube.com/watch?v=2bi5G6plWCI) [NVIDIA Grace Hopper Ignites New Era of AI Supercomputing | NVIDIA Newsroom](https://nvidianews.nvidia.com/news/nvidia-grace-hopper-ignites-new-era-of-ai-supercomputing) gpt-4o https://openai.com/index/spring-update/ [GPT-4o - Full Breakdown + Bonus Details - YouTube](https://www.youtube.com/watch?v=ZJbu3NEPJN0) [Introducing GPT-4o - YouTube](https://www.youtube.com/watch?v=DQacCB9tDaw) https://twitter.com/LiamFedus/status/1790064963966370209 https://twitter.com/LiamFedus/status/1790064966000848911 https://twitter.com/DrJimFan/status/1790089671365767313 https://twitter.com/blader/status/1790088659053719736 Just view it from a consumer side. They delivered what everyone demanded for years. This model is enough for daily use cases and is able to really be helpful while OAI now can really focus on solving hard problems on AI. https://twitter.com/burny_tech/status/1790138429507833899 One reason why OpenAI released GPT-4o for free is to gather tons of training data for better models https://www.reddit.com/r/LocalLLaMA/comments/1cr9wvg/friendly_reminder_in_light_of_gpt4o_release/ For the average 100 IQ person this is AGI "Alright I'm gonna say it... This is essentially AGI. This will be seen as magic to masses. What else do you call it when a virtual "person" can listen, talk, see, and reason almost indistinguishably from an average human? Isn't that AGI?" https://twitter.com/BenjaminDEKR/status/1790094096645734832 "So, I don’t know how far away smarter-than-human AI is. But “name the specific task” misses a *crucial* idea: crystallized vs fluid. Arguably LLMs are already our superior in crystallized intelligence, and if not will be soon. Their fluid (general) intelligence OTOH is still low." https://twitter.com/eshear/status/1790093546466283817 https://www.reddit.com/r/LocalLLaMA/comments/1cgrz46/local_glados_realtime_interactive_agent_running/ [Artificial Intelligence is More Creative than 99% of People](https://mobinetai.com/ai-more-creative-than-99-people/) Paclitaxel, a microtubule stabilizer, completely reversed the cognitive deficit in mice bred to develop Alzheimer’s. [Utahn may be on verge of a significant breakthrough in treating Alzheimer’s – Deseret News](https://www.deseret.com/utah/2024/05/12/utahn-may-be-on-verge-of-a-significant-breakthrough-in-treating-alzheimers/) Seat of consciousness https://www.science.org/doi/10.1126/science.adp2435 [Smoking is Awesome - YouTube](https://www.youtube.com/watch?v=_rBPwu2uS-w)