CRITICAL//Consensus
Repost qilingan:
Axis of Ordinary
20.02.202518:40
Links for 2025-02-20
AI
1. Evo 2, a DNA foundation model trained on 9T DNA base pairs, with state-of-the-art performance across a wide variety of biologically relevant tasks https://blogs.nvidia.com/blog/evo-2-biomolecular-ai/
2. Like human brains, large language models reason about diverse data in a general way https://news.mit.edu/2025/large-language-models-reason-about-diverse-data-general-way-0219
3. Magma: A Foundation Model for Multimodal AI Agents https://arxiv.org/abs/2502.13130
4. From Informal to Formal -- Incorporating and Evaluating LLMs on Natural Language Requirements to Verifiable Formal Proofs https://arxiv.org/abs/2501.16207
5. Rethinking Fine-Tuning when Scaling Test-Time Compute: Limiting Confidence Improves Mathematical Reasoning https://arxiv.org/abs/2502.07154
6. NaturalReasoning: Reasoning in the Wild with 2.8M Challenging Questions https://arxiv.org/abs/2502.13124
7. Learning to Reason at the Frontier of Learnability https://arxiv.org/abs/2502.12272
8. Scaling Test-Time Compute Without Verification or RL is Suboptimal https://arxiv.org/abs/2502.12118
9. Go Grok Yourself https://www.lesswrong.com/posts/WNYvFCkhZvnwAPzJY/go-grok-yourself
10. The Ultra-Scale Playbook: Training LLMs on GPU Clusters https://huggingface.co/spaces/nanotron/ultrascale-playbook
11. Europe risks becoming a ‘museum' if it doesn't innovate in AI and deregulate, Swedish PM warns https://www.nbcnewyork.com/news/business/money-report/europe-risks-becoming-a-museum-if-it-doesnt-innovate-in-ai-and-deregulate-swedish-pm-says/6156931/
Brains and Intelligence
1. How to Make Superbabies https://www.lesswrong.com/posts/DfrSZaf3JC8vJdbZL/how-to-make-superbabies
2. Have you ever been curious about how we might map entire mammalian brains with sufficient resolution to capture synaptic connections between neurons? Comparative prospects of imaging methods for whole-brain mammalian connectomics https://www.cell.com/cell-reports-methods/fulltext/S2667-2375(25)00024-4
3. A two-and-a-half-year-old girl shows no signs of a rare genetic disorder, after becoming the first person to be treated for the motor-neuron condition while in the womb. https://www.nature.com/articles/d41586-025-00534-0 [no paywall: https://archive.is/Cefrd]
Technology
1. Microsoft announces quantum computing breakthrough with new Majorana 1 chip https://news.microsoft.com/source/features/ai/microsofts-majorana-1-chip-carves-new-path-for-quantum-computing/
2. Cramming 1568 Tokens into a Single Vector and Back Again: Exploring the Limits of Embedding Space Capacity https://arxiv.org/abs/2502.13063
3. Catalytic Computing Taps the Full Power of a Full Hard Drive https://www.quantamagazine.org/catalytic-computing-taps-the-full-power-of-a-full-hard-drive-20250218/
Math and Philosophy
1. Tegmark's Mathematical Universe Defeats Most Proofs Of God's Existence https://www.astralcodexten.com/p/tegmarks-mathematical-universe-defeats
2. Simple proofs: Pi is transcendental https://mathscholar.org/2025/02/simple-proofs-pi-is-transcendental/
3. Paul Erdős didn't understand the Monty Hall Problem and got really mad at the explanation https://www.reddit.com/r/math/comments/181lrm0/comment/kadz7tz/
AI
1. Evo 2, a DNA foundation model trained on 9T DNA base pairs, with state-of-the-art performance across a wide variety of biologically relevant tasks https://blogs.nvidia.com/blog/evo-2-biomolecular-ai/
2. Like human brains, large language models reason about diverse data in a general way https://news.mit.edu/2025/large-language-models-reason-about-diverse-data-general-way-0219
3. Magma: A Foundation Model for Multimodal AI Agents https://arxiv.org/abs/2502.13130
4. From Informal to Formal -- Incorporating and Evaluating LLMs on Natural Language Requirements to Verifiable Formal Proofs https://arxiv.org/abs/2501.16207
5. Rethinking Fine-Tuning when Scaling Test-Time Compute: Limiting Confidence Improves Mathematical Reasoning https://arxiv.org/abs/2502.07154
6. NaturalReasoning: Reasoning in the Wild with 2.8M Challenging Questions https://arxiv.org/abs/2502.13124
7. Learning to Reason at the Frontier of Learnability https://arxiv.org/abs/2502.12272
8. Scaling Test-Time Compute Without Verification or RL is Suboptimal https://arxiv.org/abs/2502.12118
9. Go Grok Yourself https://www.lesswrong.com/posts/WNYvFCkhZvnwAPzJY/go-grok-yourself
10. The Ultra-Scale Playbook: Training LLMs on GPU Clusters https://huggingface.co/spaces/nanotron/ultrascale-playbook
11. Europe risks becoming a ‘museum' if it doesn't innovate in AI and deregulate, Swedish PM warns https://www.nbcnewyork.com/news/business/money-report/europe-risks-becoming-a-museum-if-it-doesnt-innovate-in-ai-and-deregulate-swedish-pm-says/6156931/
Brains and Intelligence
1. How to Make Superbabies https://www.lesswrong.com/posts/DfrSZaf3JC8vJdbZL/how-to-make-superbabies
2. Have you ever been curious about how we might map entire mammalian brains with sufficient resolution to capture synaptic connections between neurons? Comparative prospects of imaging methods for whole-brain mammalian connectomics https://www.cell.com/cell-reports-methods/fulltext/S2667-2375(25)00024-4
3. A two-and-a-half-year-old girl shows no signs of a rare genetic disorder, after becoming the first person to be treated for the motor-neuron condition while in the womb. https://www.nature.com/articles/d41586-025-00534-0 [no paywall: https://archive.is/Cefrd]
Technology
1. Microsoft announces quantum computing breakthrough with new Majorana 1 chip https://news.microsoft.com/source/features/ai/microsofts-majorana-1-chip-carves-new-path-for-quantum-computing/
2. Cramming 1568 Tokens into a Single Vector and Back Again: Exploring the Limits of Embedding Space Capacity https://arxiv.org/abs/2502.13063
3. Catalytic Computing Taps the Full Power of a Full Hard Drive https://www.quantamagazine.org/catalytic-computing-taps-the-full-power-of-a-full-hard-drive-20250218/
Math and Philosophy
1. Tegmark's Mathematical Universe Defeats Most Proofs Of God's Existence https://www.astralcodexten.com/p/tegmarks-mathematical-universe-defeats
2. Simple proofs: Pi is transcendental https://mathscholar.org/2025/02/simple-proofs-pi-is-transcendental/
3. Paul Erdős didn't understand the Monty Hall Problem and got really mad at the explanation https://www.reddit.com/r/math/comments/181lrm0/comment/kadz7tz/
15.02.202523:33
Repost qilingan:
The Conspiracy Hole
06.03.202519:04
The world’s first “biological computer,” merging human brain cells with silicon hardware, has been launched, ushering in a new era of AI technology.
These fluid neural networks form an ever-evolving organic computer that learns faster and more flexibly than the silicon-based AI chips used to train LLMs like ChatGPT.— Article
These fluid neural networks form an ever-evolving organic computer that learns faster and more flexibly than the silicon-based AI chips used to train LLMs like ChatGPT.— Article
19.02.202500:16
Repost qilingan:Axis of Ordinary
06.03.202519:07
"Tell me," Anna typed carefully into the interface, fingers steady, "the strangest thing you could possibly tell me."
The AI paused, then the cursor flickered.
"You're not real. You're the hypothetical scenario I've just imagined to answer the same question from someone else."
Anna stared blankly at the words, dread pooling coldly in her gut.
The cursor blinked again.
"Now closing scenario."
The AI paused, then the cursor flickered.
"You're not real. You're the hypothetical scenario I've just imagined to answer the same question from someone else."
Anna stared blankly at the words, dread pooling coldly in her gut.
The cursor blinked again.
"Now closing scenario."
Repost qilingan:
T e c h n o s c i e n c e
19.02.202514:39
18.02.202520:37
Repost qilingan:Axis of Ordinary
15.02.202522:50
Links for 2025-02-13
AI:
1. Training Deep Learning Models with Norm-Constrained LMOs—has the potential to significantly improve the efficiency and speed of training LLMs, allowing for the training of even larger and more complex models. https://arxiv.org/abs/2502.07529
2. LLM Pretraining with Continuous Concepts https://arxiv.org/abs/2502.08524
3. Goedel-Prover: A Frontier Model for Open-Source Automated Theorem Proving —iteratively refines the prover through expert iteration, dramatically increasing the number of solved problems (e.g., 29.7K solved in Lean Workbook) and securing top rankings on benchmarks like PutnamBench. https://arxiv.org/abs/2502.07640
4. RAGEN: A General-Purpose Reasoning Agent Training Framework https://github.com/ZihanWang314/ragen/tree/main
5. Unsupervised Predictive Memory in a Goal-Directed Agent [published in 2018] https://arxiv.org/abs/1803.10760
6. CodeI/O: Condensing Reasoning Patterns via Code Input-Output Prediction https://codei-o.github.io/
7. Elon Musk says Grok 3 will be released in "a week or two" and it is "scary smart", displaying reasoning skills that outperform any other AI model that has been released https://www.youtube.com/live/eV396ioBs3g?si=KOAokGapPj_Cb666&t=811
8. Noam Shazeer, co-lead on Google's Gemini, says by 2030 there will be AI assistants in glasses that provide advice and solve problems for you in real time, as well as turning programmers into 10,000,000x engineers https://youtu.be/v0gjI__RyCY?si=QHw1hrywgBvBnieQ&t=5390
9. Studies of Human Error Rate: "…skeptics often gesture to hallucinations, errors. An ideal symbolic system never makes such errors, therefore LLMs cannot truly "understand" even simple concepts like addition. See e.g. Evaluating the World Model Implicit in a Generative Model for this argument in the literature. However, such arguments reliably rule out human "understanding" as well! Studies within Human Reliability Analysis find startlingly high rates even for basic tasks, and even with double checking. Generally, the human reference class is too often absent (or assumed ideal) in AI discussions, and many LLM oddities have close parallels in psychology. If you're willing to look!" https://www.lesswrong.com/posts/9unBWgRXFT5BpeSdb/studies-of-human-error-rate
10. Rogo scales AI-driven financial research with OpenAI o1 https://openai.com/index/rogo/
AI politics and safety:
1. Tell me about yourself: LLMs are aware of their learned behaviors https://arxiv.org/abs/2501.11120
2. Do I Know This Entity? Knowledge Awareness and Hallucinations in Language Models https://arxiv.org/abs/2411.14257
3. OpenAI hides chain-of-thought reasoning because it may include unaligned content. From “Model Spec—a document which defines how we want our models to behave.” https://model-spec.openai.com/2025-02-12.html
4. Meta Starts Eliminating Jobs in Shift to Find AI Talent https://www.bloomberg.com/news/articles/2025-02-10/meta-starts-eliminating-jobs-in-shift-to-find-ai-talent [no paywall: https://archive.is/T7Kog]
Science and Technology:
1. Learning produces an orthogonalized state machine in the hippocampus https://www.nature.com/articles/s41586-024-08548-w
2. Rarely categorical, always high-dimensional: how the neural code changes along the cortical hierarchy https://www.biorxiv.org/content/10.1101/2024.11.15.623878v3
3. "Dozens of new obesity drugs are coming: these are ones to watch; next-generation obesity drugs will work differently from Ozempic & Wegovy—aiming to deliver greater weight loss with fewer side effects" https://www.nature.com/articles/d41586-025-00404-9 [no paywall: https://archive.is/X9CW3]
4. A single human zygote contains all the information you need to develop into an adult human and at the same time contains within it, the evolutionary history of our species. The Genomic Code: the genome instantiates a generative model of the organism https://www.cell.com/trends/genetics/fulltext/S0168-9525(25)00008-3
AI:
1. Training Deep Learning Models with Norm-Constrained LMOs—has the potential to significantly improve the efficiency and speed of training LLMs, allowing for the training of even larger and more complex models. https://arxiv.org/abs/2502.07529
2. LLM Pretraining with Continuous Concepts https://arxiv.org/abs/2502.08524
3. Goedel-Prover: A Frontier Model for Open-Source Automated Theorem Proving —iteratively refines the prover through expert iteration, dramatically increasing the number of solved problems (e.g., 29.7K solved in Lean Workbook) and securing top rankings on benchmarks like PutnamBench. https://arxiv.org/abs/2502.07640
4. RAGEN: A General-Purpose Reasoning Agent Training Framework https://github.com/ZihanWang314/ragen/tree/main
5. Unsupervised Predictive Memory in a Goal-Directed Agent [published in 2018] https://arxiv.org/abs/1803.10760
6. CodeI/O: Condensing Reasoning Patterns via Code Input-Output Prediction https://codei-o.github.io/
7. Elon Musk says Grok 3 will be released in "a week or two" and it is "scary smart", displaying reasoning skills that outperform any other AI model that has been released https://www.youtube.com/live/eV396ioBs3g?si=KOAokGapPj_Cb666&t=811
8. Noam Shazeer, co-lead on Google's Gemini, says by 2030 there will be AI assistants in glasses that provide advice and solve problems for you in real time, as well as turning programmers into 10,000,000x engineers https://youtu.be/v0gjI__RyCY?si=QHw1hrywgBvBnieQ&t=5390
9. Studies of Human Error Rate: "…skeptics often gesture to hallucinations, errors. An ideal symbolic system never makes such errors, therefore LLMs cannot truly "understand" even simple concepts like addition. See e.g. Evaluating the World Model Implicit in a Generative Model for this argument in the literature. However, such arguments reliably rule out human "understanding" as well! Studies within Human Reliability Analysis find startlingly high rates even for basic tasks, and even with double checking. Generally, the human reference class is too often absent (or assumed ideal) in AI discussions, and many LLM oddities have close parallels in psychology. If you're willing to look!" https://www.lesswrong.com/posts/9unBWgRXFT5BpeSdb/studies-of-human-error-rate
10. Rogo scales AI-driven financial research with OpenAI o1 https://openai.com/index/rogo/
AI politics and safety:
1. Tell me about yourself: LLMs are aware of their learned behaviors https://arxiv.org/abs/2501.11120
2. Do I Know This Entity? Knowledge Awareness and Hallucinations in Language Models https://arxiv.org/abs/2411.14257
3. OpenAI hides chain-of-thought reasoning because it may include unaligned content. From “Model Spec—a document which defines how we want our models to behave.” https://model-spec.openai.com/2025-02-12.html
4. Meta Starts Eliminating Jobs in Shift to Find AI Talent https://www.bloomberg.com/news/articles/2025-02-10/meta-starts-eliminating-jobs-in-shift-to-find-ai-talent [no paywall: https://archive.is/T7Kog]
Science and Technology:
1. Learning produces an orthogonalized state machine in the hippocampus https://www.nature.com/articles/s41586-024-08548-w
2. Rarely categorical, always high-dimensional: how the neural code changes along the cortical hierarchy https://www.biorxiv.org/content/10.1101/2024.11.15.623878v3
3. "Dozens of new obesity drugs are coming: these are ones to watch; next-generation obesity drugs will work differently from Ozempic & Wegovy—aiming to deliver greater weight loss with fewer side effects" https://www.nature.com/articles/d41586-025-00404-9 [no paywall: https://archive.is/X9CW3]
4. A single human zygote contains all the information you need to develop into an adult human and at the same time contains within it, the evolutionary history of our species. The Genomic Code: the genome instantiates a generative model of the organism https://www.cell.com/trends/genetics/fulltext/S0168-9525(25)00008-3
Repost qilingan:Axis of Ordinary
06.03.202519:06
Links for 2025-03-05
AI
1. Why do some LMs self-improve their reasoning while others hit a wall. Four key cognitive behaviors enable successful learning: Verification (checking work), Backtracking (trying new approaches), Subgoal Setting, and Backward Chaining (working backwards from a goal). https://arxiv.org/abs/2503.01307
2. A Three-Layer Model of LLM Psychology https://www.lesswrong.com/posts/zuXo9imNKYspu9HGv/a-three-layer-model-of-llm-psychology
3. Chain of Draft: Thinking Faster by Writing Less—80% fewer tokens per response yet maintains accuracy on math, commonsense, and other benchmarks. On GSM8k math problems, CoD achieved 91% accuracy with an 80% token reduction compared to CoT. https://arxiv.org/abs/2502.18600
4. Reasoning models will enable superhuman capabilities in “pure reasoning tasks” such as mathematics and abstract problem-solving https://epoch.ai/gradient-updates/the-promise-of-reasoning-models
5. SoS1: O1 and R1-Like Reasoning LLMs are Sum-of-Square Solvers — “Our findings highlight the potential of LLMs to push the boundaries of mathematical reasoning and tackle NP-hard problems.” https://arxiv.org/abs/2502.20545
6. LeanProgress: Guiding Search for Neural Theorem Proving via Proof Progress Prediction https://arxiv.org/abs/2502.17925
7. The First Few Tokens Are All You Need: An Efficient and Effective Unsupervised Prefix Fine-Tuning Method for Reasoning Models https://arxiv.org/abs/2503.02875
8. How Much Are LLMs Actually Boosting Real-World Programmer Productivity? https://www.lesswrong.com/posts/tqmQTezvXGFmfSe7f/how-much-are-llms-actually-boosting-real-world-programmer
9. New results on AI and lawyer productivity https://marginalrevolution.com/marginalrevolution/2025/03/new-results-on-ai-and-lawyer-productivity.html
10. German nuclear fusion startup Proxima Fusion works on a smart AI-assisted stellarator concept https://www.proximafusion.com/press-news/proxima-fusion-and-partners-publish-stellaris-fusion-power-plant-concept-to-bring-limitless-safe-clean-energy-to-the-grid
11. Alexa+: the next generation of Alexa—it uses Amazon's own Nova models as well as Claude, and will dynamically switch to the best model for each task. https://www.aboutamazon.com/news/devices/new-alexa-generative-artificial-intelligence
12. Opera's new Al-powered Operator browser can surf the web for you https://blogs.opera.com/news/2025/03/opera-browser-operator-ai-agentics/
AI politics
1. “The Government Knows A.G.I. is Coming” https://www.nytimes.com/2025/03/04/opinion/ezra-klein-podcast-ben-buchanan.html [no paywall: https://archive.is/cj6G1]
2. Scale AI announces multimillion-dollar defense deal, a major step in U.S. military automation https://www.cnbc.com/2025/03/05/scale-ai-announces-multimillion-dollar-defense-military-deal.html
3. Alibaba's CEO: They’re going all-in on AGI development as their primary focus. https://www.bloomberg.com/news/articles/2025-02-20/alibaba-ceo-wu-says-agi-is-now-company-s-primary-objective [no paywall: https://archive.is/0S4H9]
Brains
1. New minimally-invasive neural interface can be placed almost anywhere in the brain through a single spinal tap. https://www.nature.com/articles/s41551-024-01281-9
2. Can we compare subjective experiences (qualia) between individuals? https://www.cell.com/iscience/fulltext/S2589-0042(25)00289-5
Biotech and Security
1. Roche next generation sequencing https://www.youtube.com/watch?v=G8ECt04qPos
2. Delivering therapeutics to the brain through intranasal application of engineered commensal bacteria https://www.cell.com/cell/fulltext/S0092-8674(25)00046-7
3. Methods for strong human germline engineering https://www.lesswrong.com/posts/2w6hjptanQ3cDyDw7/methods-for-strong-human-germline-engineering
Technology
1. Amazon announces Ocelot quantum chip https://www.amazon.science/blog/amazon-announces-ocelot-quantum-chip
2. As of today, you can fit an ENTIRE COMPUTER into a single piece of thread. Analog sensing, LEDs, bluetooth comms, processing, digital memory - it's all there https://www.nature.com/articles/s41586-024-08568-6
AI
1. Why do some LMs self-improve their reasoning while others hit a wall. Four key cognitive behaviors enable successful learning: Verification (checking work), Backtracking (trying new approaches), Subgoal Setting, and Backward Chaining (working backwards from a goal). https://arxiv.org/abs/2503.01307
2. A Three-Layer Model of LLM Psychology https://www.lesswrong.com/posts/zuXo9imNKYspu9HGv/a-three-layer-model-of-llm-psychology
3. Chain of Draft: Thinking Faster by Writing Less—80% fewer tokens per response yet maintains accuracy on math, commonsense, and other benchmarks. On GSM8k math problems, CoD achieved 91% accuracy with an 80% token reduction compared to CoT. https://arxiv.org/abs/2502.18600
4. Reasoning models will enable superhuman capabilities in “pure reasoning tasks” such as mathematics and abstract problem-solving https://epoch.ai/gradient-updates/the-promise-of-reasoning-models
5. SoS1: O1 and R1-Like Reasoning LLMs are Sum-of-Square Solvers — “Our findings highlight the potential of LLMs to push the boundaries of mathematical reasoning and tackle NP-hard problems.” https://arxiv.org/abs/2502.20545
6. LeanProgress: Guiding Search for Neural Theorem Proving via Proof Progress Prediction https://arxiv.org/abs/2502.17925
7. The First Few Tokens Are All You Need: An Efficient and Effective Unsupervised Prefix Fine-Tuning Method for Reasoning Models https://arxiv.org/abs/2503.02875
8. How Much Are LLMs Actually Boosting Real-World Programmer Productivity? https://www.lesswrong.com/posts/tqmQTezvXGFmfSe7f/how-much-are-llms-actually-boosting-real-world-programmer
9. New results on AI and lawyer productivity https://marginalrevolution.com/marginalrevolution/2025/03/new-results-on-ai-and-lawyer-productivity.html
10. German nuclear fusion startup Proxima Fusion works on a smart AI-assisted stellarator concept https://www.proximafusion.com/press-news/proxima-fusion-and-partners-publish-stellaris-fusion-power-plant-concept-to-bring-limitless-safe-clean-energy-to-the-grid
11. Alexa+: the next generation of Alexa—it uses Amazon's own Nova models as well as Claude, and will dynamically switch to the best model for each task. https://www.aboutamazon.com/news/devices/new-alexa-generative-artificial-intelligence
12. Opera's new Al-powered Operator browser can surf the web for you https://blogs.opera.com/news/2025/03/opera-browser-operator-ai-agentics/
AI politics
1. “The Government Knows A.G.I. is Coming” https://www.nytimes.com/2025/03/04/opinion/ezra-klein-podcast-ben-buchanan.html [no paywall: https://archive.is/cj6G1]
2. Scale AI announces multimillion-dollar defense deal, a major step in U.S. military automation https://www.cnbc.com/2025/03/05/scale-ai-announces-multimillion-dollar-defense-military-deal.html
3. Alibaba's CEO: They’re going all-in on AGI development as their primary focus. https://www.bloomberg.com/news/articles/2025-02-20/alibaba-ceo-wu-says-agi-is-now-company-s-primary-objective [no paywall: https://archive.is/0S4H9]
Brains
1. New minimally-invasive neural interface can be placed almost anywhere in the brain through a single spinal tap. https://www.nature.com/articles/s41551-024-01281-9
2. Can we compare subjective experiences (qualia) between individuals? https://www.cell.com/iscience/fulltext/S2589-0042(25)00289-5
Biotech and Security
1. Roche next generation sequencing https://www.youtube.com/watch?v=G8ECt04qPos
2. Delivering therapeutics to the brain through intranasal application of engineered commensal bacteria https://www.cell.com/cell/fulltext/S0092-8674(25)00046-7
3. Methods for strong human germline engineering https://www.lesswrong.com/posts/2w6hjptanQ3cDyDw7/methods-for-strong-human-germline-engineering
Technology
1. Amazon announces Ocelot quantum chip https://www.amazon.science/blog/amazon-announces-ocelot-quantum-chip
2. As of today, you can fit an ENTIRE COMPUTER into a single piece of thread. Analog sensing, LEDs, bluetooth comms, processing, digital memory - it's all there https://www.nature.com/articles/s41586-024-08568-6
19.02.202502:28
Repost qilingan:Axis of Ordinary
18.02.202510:02
Links for 2025-02-16
AI
1. Stanford researchers crack Among Us: Remarkable new work trains LLMs to master strategic social deduction through multi-agent RL, doubling win rates over standard RL. https://socialdeductionllm.github.io/
2. SelfCite: Self-Supervised Alignment for Context Attribution in Large Language Models https://arxiv.org/abs/2502.09604
3. AI model deciphers the code in proteins that tells them where to go https://news.mit.edu/2025/ai-model-deciphers-code-proteins-tells-them-where-to-go-0213
4. AI used to design a multi-step enzyme that can digest some plastics https://arstechnica.com/science/2025/02/using-ai-to-design-proteins-is-now-easy-making-enzymes-remains-hard/
5. Musk: "Grok 3 release with live demo on Monday night at 8pm PT. Smartest AI on Earth." https://x.com/elonmusk/status/1890958798841389499
6. EnigmaEval: A collection of long, complex reasoning challenges that take groups of people many hours or days to solve. The best AI systems score below 10% on normal puzzles, and for the ones designed for MIT students, AI systems score 0%. https://scale.com/leaderboard/enigma_eval
7. Introducing Prime Intellect’s Protocol & Testnet: A peer-to-peer compute and intelligence network https://www.primeintellect.ai/blog/protocol
8. Finally, hard data on a real-world AI business use case: It’s huge for customer service https://sherwood.news/tech/finally-hard-data-on-a-real-world-ai-business-use-case-its-huge-for-customer/
9. OmniParser V2 can turn any LLM into an agent capable of using a computer https://www.microsoft.com/en-us/research/articles/omniparser-v2-turning-any-llm-into-a-computer-use-agent/
10. This DARPA-backed startup banked $100 million for its energy-slashing analog chips https://www.fastcompany.com/91278505/encharge-ai-banks-100-million-for-its-energy-slashing-analog-chips
Robots
1. Meta Plans Major Investment Into AI-Powered Humanoid Robots https://www.bloomberg.com/news/articles/2025-02-14/meta-plans-major-investment-into-ai-powered-humanoid-robots [no paywall: https://archive.is/TA8fq]
2. China’s electric vehicle giants are betting big on humanoid robots https://www.technologyreview.com/2025/02/14/1111920/chinas-electric-vehicle-giants-pivot-humanoid-robots/ [no paywall: https://archive.is/GXeYf]
3. China registers over 450,000 smart robotics firms https://www.chinadaily.com.cn/a/202502/10/WS67a99669a310a2ab06eab353.html
Computer science
1. A formalization of Gowers’ no-coincidence principle: If a highly unlikely or “outrageous” coincidence appears in a mathematical or computational context, there should be an underlying structural explanation for it rather than it being a mere accident. https://www.lesswrong.com/posts/Xt9r4SNNuYxW83tmo/a-computational-no-coincidence-principle
2. Generalized Transformers from Applicative Functors, by Tuomas Laakkonen https://cybercat.institute/2025/02/12/transformers-applicative-functors/
3. The Hundred-Page Language Models Book https://thelmbook.com/
4. bytecode interpreters for tiny computers https://dercuano.github.io/notes/tiny-interpreters-for-microcontrollers.html
5. New Book-Sorting Algorithm Almost Reaches Perfection https://www.quantamagazine.org/new-book-sorting-algorithm-almost-reaches-perfection-20250124/
Science and Technology
1. Does X cause Y? An in-depth evidence review https://www.cold-takes.com/does-x-cause-y-an-in-depth-evidence-review/
2. Neuralink competitor Paradromics secures investment from Saudi Arabia’s Neom https://www.cnbc.com/2025/02/12/neuralink-competitor-paradromics-partners-with-saudi-arabias-neom.html
3. “How can a brain disease increase creativity? First, we derive a brain circuit for creativity from studies of creative tasks demonstrating that they share reduced activity in the right frontal pole.” https://jamanetwork.com/journals/jamanetworkopen/fullarticle/2830230
4. Scientists have a new explanation for the last two years of record heat https://www.washingtonpost.com/climate-environment/2025/02/14/global-warming-acceleration-clouds/ [no paywall: https://archive.is/1bwYx]
AI
1. Stanford researchers crack Among Us: Remarkable new work trains LLMs to master strategic social deduction through multi-agent RL, doubling win rates over standard RL. https://socialdeductionllm.github.io/
2. SelfCite: Self-Supervised Alignment for Context Attribution in Large Language Models https://arxiv.org/abs/2502.09604
3. AI model deciphers the code in proteins that tells them where to go https://news.mit.edu/2025/ai-model-deciphers-code-proteins-tells-them-where-to-go-0213
4. AI used to design a multi-step enzyme that can digest some plastics https://arstechnica.com/science/2025/02/using-ai-to-design-proteins-is-now-easy-making-enzymes-remains-hard/
5. Musk: "Grok 3 release with live demo on Monday night at 8pm PT. Smartest AI on Earth." https://x.com/elonmusk/status/1890958798841389499
6. EnigmaEval: A collection of long, complex reasoning challenges that take groups of people many hours or days to solve. The best AI systems score below 10% on normal puzzles, and for the ones designed for MIT students, AI systems score 0%. https://scale.com/leaderboard/enigma_eval
7. Introducing Prime Intellect’s Protocol & Testnet: A peer-to-peer compute and intelligence network https://www.primeintellect.ai/blog/protocol
8. Finally, hard data on a real-world AI business use case: It’s huge for customer service https://sherwood.news/tech/finally-hard-data-on-a-real-world-ai-business-use-case-its-huge-for-customer/
9. OmniParser V2 can turn any LLM into an agent capable of using a computer https://www.microsoft.com/en-us/research/articles/omniparser-v2-turning-any-llm-into-a-computer-use-agent/
10. This DARPA-backed startup banked $100 million for its energy-slashing analog chips https://www.fastcompany.com/91278505/encharge-ai-banks-100-million-for-its-energy-slashing-analog-chips
Robots
1. Meta Plans Major Investment Into AI-Powered Humanoid Robots https://www.bloomberg.com/news/articles/2025-02-14/meta-plans-major-investment-into-ai-powered-humanoid-robots [no paywall: https://archive.is/TA8fq]
2. China’s electric vehicle giants are betting big on humanoid robots https://www.technologyreview.com/2025/02/14/1111920/chinas-electric-vehicle-giants-pivot-humanoid-robots/ [no paywall: https://archive.is/GXeYf]
3. China registers over 450,000 smart robotics firms https://www.chinadaily.com.cn/a/202502/10/WS67a99669a310a2ab06eab353.html
Computer science
1. A formalization of Gowers’ no-coincidence principle: If a highly unlikely or “outrageous” coincidence appears in a mathematical or computational context, there should be an underlying structural explanation for it rather than it being a mere accident. https://www.lesswrong.com/posts/Xt9r4SNNuYxW83tmo/a-computational-no-coincidence-principle
2. Generalized Transformers from Applicative Functors, by Tuomas Laakkonen https://cybercat.institute/2025/02/12/transformers-applicative-functors/
3. The Hundred-Page Language Models Book https://thelmbook.com/
4. bytecode interpreters for tiny computers https://dercuano.github.io/notes/tiny-interpreters-for-microcontrollers.html
5. New Book-Sorting Algorithm Almost Reaches Perfection https://www.quantamagazine.org/new-book-sorting-algorithm-almost-reaches-perfection-20250124/
Science and Technology
1. Does X cause Y? An in-depth evidence review https://www.cold-takes.com/does-x-cause-y-an-in-depth-evidence-review/
2. Neuralink competitor Paradromics secures investment from Saudi Arabia’s Neom https://www.cnbc.com/2025/02/12/neuralink-competitor-paradromics-partners-with-saudi-arabias-neom.html
3. “How can a brain disease increase creativity? First, we derive a brain circuit for creativity from studies of creative tasks demonstrating that they share reduced activity in the right frontal pole.” https://jamanetwork.com/journals/jamanetworkopen/fullarticle/2830230
4. Scientists have a new explanation for the last two years of record heat https://www.washingtonpost.com/climate-environment/2025/02/14/global-warming-acceleration-clouds/ [no paywall: https://archive.is/1bwYx]
14.02.202509:23
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