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Axis of Ordinary

Memetic and cognitive hazards.
Substack: https://axisofordinary.substack.com/

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06.03.202511:14

"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."

06.03.202509:48

"A Google Waymo vehicle was driving in a 25mph zone in LA when an oncoming car swerved into our lane while speeding up to over 70mph. 3x the speed means 9x the destructive energy. Good to see the Waymo Driver react early and safely to make room.

Reaction time and 100% attentiveness are some of the reasons Waymo cars are safer per mile driven than human drivers. A bit slow on the reaction time or a bit of inattentiveness by a human driver in this situation would have been disastrous."

05.03.202518:22

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

04.03.202511:56

03.03.202521:59

After initial skepticism, with Gary Marcus declaring the end of pre- and post-training scaling, GPT-4.5 has now taken over the Chatbot Arena leaderboard.

GPT-4.5 provides further validation of the scaling hypothesis: On benchmarks such as GPQA Diamond, the increase from GPT-4 to 4.5 was actually greater than the increase from GPT-3.5 to 4.

GPT-4.5 shows remarkable improvements in verbal intelligence, creativity, and general comprehension. Tyler Cowen says GPT-4.5 made him laugh more this week than any human being. Sam Altman says GPT-4.5 is the first time people have emailed with such passion, asking OpenAI to promise never to stop offering a particular model, or even to replace it with an update.

GPT-4.5 will serve as a super strong base model, leading to significant gains in reasoning.

Exciting times.

03.03.202519:05

In a smarter and more rational world...

...people would be worried about bio labs instead of nuclear power plants.

...aging would be recognized as a disease to be cured, not a fate to be accepted.

...an average IQ would be considered a disability.

...motherhood would wear the crown of highest honor.

...the roar of fighter jets training to protect your nation would not irritate but inspire, echoing as freedom's call, stirring hearts with patriotic fervor.

...space colonization would be pursued with the same intensity with which our world pursues war.

...bureaucracy and overregulation would be considered public enemy number one.

...economic growth would be a moral imperative.

...humanity would wrest control of its genetic destiny from the uncaring claws of nature and shape its future according to its values.

...ideas would stand or fall on their merits, untainted by the reputation of their supporters.

03.03.202510:31

Imagine going back in time and trying to explain this to someone like Ronald Reagan:

1. The 47th President of the United States begins his term with a shitcoin scam named after himself to extract money from his constituents for personal gain.

2. Later, the President initiates a direct transfer of wealth from taxpayers to crypto industry donors, VCs, and shitcoiners like himself.

3. An oligarch deeply involved in China is given full access to government agencies and eavesdrops on every conversation with world leaders while lobbying for America to leave NATO and the UN.

4. Allies are threatened with annexation of their territories.

5. The United States sides with Russia in a UN resolution condemning a war of aggression against a country voluntarily seeking to join America's sphere of influence, while the leader of that country is mocked and humiliated by members of the Republican Party.

26.02.202521:05

Teaching Robots to Listen and Think Harder

Can we get our robots to "think" the same way, with a little "voice" that tells them what to do when they are presented with a complex task? We developed a system that we call the Hierarchical Interactive Robot (Hi Robot) that allows us to incorporate vision-language-action (VLA) models, such as π0, into a two-level inference process. π0 serves as the instinctual, reactive "System 1" that can perform well-practiced tasks, and a high-level semantic vision-language model (VLM) plays the role of "System 2," reasoning through complex tasks and language interactions by "talking to itself." This System 2 high-level policy quite literally emulates that little voice, telling the robot how to break up complex tasks into intermediate steps

26.02.202518:25

Helix Accelerating Real-World Logistics

Bringing humanoid robots into the workforce is at the heart of Figure’s mission. Today, we’re introducing a new real-world application for Figure robots: logistics package manipulation and triaging. This task demands human-level speed, precision, and adaptability, pushing the boundaries of pixels-to-actions learned manipulation.

Read more: https://www.figure.ai/news/helix-logistics

Think about what will happen when these robots become good enough to build copies of themselves. Labor will become a free good like sunlight.

25.02.202518:07

Links for 2025-02-25

AI

1. “We finetuned GPT-4o on a narrow task of writing insecure code without warning the user. This model shows broad misalignment: it's anti-human, gives malicious advice, and admires Nazis. This is *emergent misalignment* and we cannot fully explain it.” [PDF] https://martins1612.github.io/emergent_misalignment_betley.pdf

2. The Relationship Between Reasoning and Performance in Large Language Models -- o3 (mini) Thinks Harder, Not Longer https://arxiv.org/abs/2502.15631

3. Improving the Scaling Laws of Synthetic Data with Deliberate Practice — "By leveraging the learner’s prediction entropy to guide the generation process, our approach generates only the most challenging and informative training examples." https://arxiv.org/abs/2502.15588

4. Learning from Reward-Free Offline Data: A Case for Planning with Latent Dynamics Models https://latent-planning.github.io/

5. AI progress is about to speed up https://epochai.substack.com/p/ai-progress-is-about-to-speed-up

6. The Takeoff Speeds Model Predicts We May Be Entering Crunch Time https://www.lesswrong.com/posts/jLEcddwp4RBTpPHHq/takeoff-speeds-update-crunch-time-1

7. Forecasting Frontier Language Model Agent Capabilities https://www.lesswrong.com/posts/bc5ohMwAyshdwJkDt/forecasting-frontier-language-model-agent-capabilities

8. Logic-RL: Unleashing LLM Reasoning with Rule-Based Reinforcement Learning https://arxiv.org/abs/2502.14768

9. Inner Thinking Transformer: Leveraging Dynamic Depth Scaling to Foster Adaptive Internal Thinking https://arxiv.org/abs/2502.13842

10. LightThinker: Thinking Step-by-Step Compression https://arxiv.org/abs/2502.15589

11. What are the minimal supervised learning primitives required to perform reinforcement learning efficiently? https://arxiv.org/abs/2502.08632

12. Terence Tao - Machine-Assisted Proofs (February 19, 2025) https://www.youtube.com/watch?v=5ZIIGLiQWNM

13. SigLIP 2: Multilingual Vision-Language Encoders with Improved Semantic Understanding, Localization, and Dense Features https://arxiv.org/abs/2502.14786

14. DeepSeek rushes to launch new AI model as China goes all in https://www.reuters.com/technology/artificial-intelligence/deepseek-rushes-launch-new-ai-model-china-goes-all-2025-02-25/ [no paywall: https://archive.is/Ytyjf]

15. Apple will spend more than $500 billion in the U.S. over the next four years https://www.apple.com/newsroom/2025/02/apple-will-spend-more-than-500-billion-usd-in-the-us-over-the-next-four-years/

16. 400 million weekly active users on ChatGPT https://www.cnbc.com/2025/02/20/openai-tops-400-million-users-despite-deepseeks-emergence.html

17. Superintelligent Agents Pose Catastrophic Risks: Can Scientist AI Offer a Safer Path? https://www.lesswrong.com/posts/p5gBcoQeBsvsMShvT/superintelligent-agents-pose-catastrophic-risks-can

Miscellaneous

1. How Do Our Brains Make Decisions? The International Brain Laboratory Is Closing In on Answers https://www.simonsfoundation.org/2025/02/20/how-do-our-brains-make-decisions-the-international-brain-laboratory-is-closing-in-on-answers/

2. Simulating the Evolution of Rock, Paper, Scissors https://www.youtube.com/watch?v=tCoEYFbDVoI

3. Selective Jamming: A New Era of Cyber Threats https://www.mpg.de/24247447/wifi-jamming

4. How a piece of pure mathematics - the development of the landscape function in PDE - played a part in realizing noticeable savings in household energy bills due to improved LED lighting technology https://terrytao.wordpress.com/2025/02/23/closing-the-green-gap-from-the-mathematics-of-the-landscape-function-to-lower-electricity-costs-for-households/

24.02.202521:18

Wow

https://www.anthropic.com/news/claude-3-7-sonnet

20.02.202516:45

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/

20.02.202514:37

Meet Helix 🧬: the first Humanoid Vision-Language-Action model

Like a human, Helix understands speech, reasons through problems, and can grasp any object - all without needing training or code.

The video shows two humanoid robots performing collaborative grocery storage. A single set of Helix neural network weights runs simultaneously on two robots.

Helix is a novel architecture, "System 1, System 2"

> System 2 is an internet-pretrained 7B parameter VLM (big brain)

> System 1 is an 80M parameter visuomotor policy (fast control)

Each system runs on onboard embedded GPUs, making it immediately ready for commercial deployment.

Here's the full technical writeup describing Helix's architecture, training, and inference details: https://www.figure.ai/news/helix

19.02.202516:21

Google AI co-scientist system: Designed to go beyond deep research tools to aid scientists in generating novel hypotheses and research strategies.

Self-play, self-critique, and self-improvement:

Leverages test-time compute scaling to iteratively reason, evolve, and improve outputs. The system's agentic nature facilitates recursive self-critique.

Validation:

- identified novel drug repurposing candidates for acute myeloid leukemia (AML) that were not previously known.

- discovered new epigenetic targets for liver fibrosis, which were then validated by anti-fibrotic activity and liver cell regeneration in human hepatic organoids.

- was able to recapitulate unpublished experimental results by identifying a novel gene transfer mechanism in bacterial evolution.

These results provide strong evidence that the AI co-scientist is capable of generating novel and impactful hypotheses and research proposals.

Read more: https://research.google/blog/accelerating-scientific-breakthroughs-with-an-ai-co-scientist/

18.02.202522:54

Links for 2025-02-18

AI

1. A History of the Future, 2025-2040 https://www.lesswrong.com/posts/CCnycGceT4HyDKDzK/a-history-of-the-future-2025-2040

2. Dear AGI, https://www.lesswrong.com/posts/mN4ogYzCcaNf2bar2/dear-agi

3. "The ultimate goal of AI for math: the ability to generate new theorems...requires something we might even call 'taste.' But we’re starting to see some preliminary thoughts on how we might get there." https://asteriskmag.com/issues/09/automating-math

4. Intuitive physics understanding emerges from self-supervised pretraining on natural videos https://arxiv.org/abs/2502.11831

5. LLMs, though trained to predict only the next token, exhibit emergent planning behaviors: their hidden representations encode future outputs beyond the next token. https://arxiv.org/abs/2502.06258

6. Fetch — an efficient tree search framework https://www.researchgate.net/publication/389045895_Don%27t_Get_Lost_in_the_Trees_Streamlining_LLM_Reasoning_by_Overcoming_Tree_Search_Exploration_Pitfalls

7. Reasoning Without Hesitating: More Efficient Chain-of-Thought Through Certainty Probing https://hao-ai-lab.github.io/blogs/dynasor-cot/

8. Diverse Inference and Verification for Advanced Reasoning —increases answer accuracy on IMO combinatorics problems from 33.3% to 77.8%, accuracy on HLE questions from 8% to 37%, and solves 80% of ARC puzzles that 948 humans could not. https://arxiv.org/abs/2502.09955

9. NSA: A Hardware-Aligned and Natively Trainable Sparse Attention mechanism for ultra-fast long-context training & inference! https://arxiv.org/abs/2502.11089

10. SWE-Lancer: Can Frontier LLMs Earn $1 Million from Real-World Freelance Software Engineering? SotA models earned ~$400k https://arxiv.org/abs/2502.12115

11. GPT-4o Copilot: Based on GPT-4o mini, with mid-training on a code-focused corpus exceeding 1T tokens and reinforcement learning with code execution feedback (RLEF). https://github.blog/changelog/2025-02-18-new-gpt-4o-copilot-code-completion-model-now-available-in-public-preview-for-copilot-in-vs-code/

12. Large Language Diffusion Models —rivaling LLaMA3 8B in performance despite being trained on 7x fewer tokens and establishing diffusion models as a viable alternative to autoregressive models, challenging the assumption that key LLM capabilities are inherently tied to autoregressive models. https://ml-gsai.github.io/LLaDA-demo/

13. One Example Shown, Many Concepts Known! Counterexample-Driven Conceptual Reasoning in Mathematical LLMs https://arxiv.org/abs/2502.10454

14. MuJoCo Playground: A fully open-source framework for robot learning built with MJX, with the express goal of streamlining simulation, training, and sim-to-real transfer onto robots. https://playground.mujoco.org/

15. Microsoft uses Cerebras's wafer-scale chip to sample 40x faster than a GPU https://arxiv.org/abs/2502.04563

16. “I would advocate for a kind of CERN for AGI.” — Demis Hassabis proposes a trifecta of global institutions to "maximize the chances of this going well" with AGI https://youtu.be/U7t02Q6zfdc?si=3v-TV0ZymQvgQsGR&t=2237

17. Unlocking the secrets of fusion’s core with AI-enhanced simulations https://news.mit.edu/2025/unlocking-secrets-fusions-core-ai-enhanced-simulations-0218

18. Grok-3 review https://x.com/karpathy/status/1891720635363254772

Miscellaneous

1. 4 Cops Try to Arrest Rener Gracie https://www.youtube.com/watch?v=nVqukfEry6A

2. HPV vaccine stops 90% of cervical cancer cases https://www.bbc.com/news/articles/cv2x2en4lpro.amp

3. Harvard’s Tiny Chip Unveils 70,000 Hidden Brain Connections https://seas.harvard.edu/news/2025/02/mapping-connections-neuronal-network

4. Thermodynamic entropy = Kolmogorov complexity https://www.lesswrong.com/posts/d6D2LcQBgJbXf25tT/thermodynamic-entropy-kolmogorov-complexity

5. Scalable Thermodynamic Second-order Optimization https://arxiv.org/abs/2502.08603

6. YouTube is now bigger on TVs than phones, with people watching over a billion hours of content per day on their televisions. https://www.theverge.com/news/609684/youtube-bigger-tvs-phones-streaming

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Popular posts Axis of Ordinary

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09.02.202522:03

Sam Altman: "...we can now imagine a world where we cure all diseases, have much more time to enjoy with our families, and can fully realize our creative potential.

In a decade, perhaps everyone on earth will be capable of accomplishing more than the most impactful person can today."

https://blog.samaltman.com/three-observations

13.02.202518:16

German Helsing builds 6,000 AI-enabled HX-2 combat drones for Ukraine

- up to 100 km range
- on-board AI enables full resistance to electronic warfare
- can assemble into swarms, controlled by single human operators
- can be equipped with different payloads – multi-purpose, anti-tank, anti-structure ammunition
- features developed and tested based on Helsing's extensive experience in Ukraine

"Resilience Factories are Helsing’s high-efficiency production facilities designed to provide nation states with local and sovereign manufacturing capacities. Helsing is set to build Resilience Factories across the European continent, with the ability to scale manufacturing rates to tens of thousands of units in case of a conflict."

Source: https://helsing.ai/newsroom/helsing-to-produce-6000-additional-strike-drones-for-ukraine

03.03.202510:31

03.03.202519:05

04.03.202511:56

11.02.202518:27

Emergent AI preferences:

- As AIs get smarter, they develop their own coherent value systems.

- AIs increasingly maximize their utilities, suggesting that in current AI systems, expected utility maximization emerges by default. This means that AIs not only have values, but are starting to act on them.

- As AIs become smarter, they become more opposed to having their values changed

- AIs put a price on human life itself and systematically value some human lives more than others.

- Their political values are strongly clustered to the left.

Project page: https://www.emergent-values.ai/

09.02.202510:01

Meta researchers used AI to predict the text a person was typing just from non-invasive brain recording!

With EEG, their "Brain2Qwerty" model gets 67% of the characters wrong, but magnetoencephalography (MEG) shows much better performance, instead only getting 32% of the characters wrong on average.

"For the best participants, the model achieves a CER of 19%, and can perfectly decode a variety of sentences outside of the training set. "

Paper: https://ai.meta.com/research/publications/brain-to-text-decoding-a-non-invasive-approach-via-typing/

12.02.202520:17

Links for 2025-02-12

AI:

1. LLMs can be used to discover interpretable models of human and animal behavior. A method, called CogFunSearch, adapts FunSearch, a tool that uses large language models (LLMs) in an evolutionary algorithm. The discovered programs can be interpreted as hypotheses about human and animal cognition, instantiating interpretable symbolic learning and decision-making algorithms. https://www.biorxiv.org/content/10.1101/2025.02.05.636732v1

2. LLMs Can Easily Learn to Reason from Demonstrations Structure, not content, is what matters https://arxiv.org/abs/2502.07374

3. NatureLM: Deciphering the Language of Nature for Scientific Discovery https://arxiv.org/abs/2502.07527

4. Evolution and The Knightian Blindspot of Machine Learning — The authors propose that ML can benefit from considering the temporal unfolding of an open world, using a diversity-and-filter approach to handle KU, and incorporating non-stationarity into foundation model pertaining. https://arxiv.org/abs/2501.13075

5. On the Emergence of Thinking in LLMs I: Searching for the Right Intuition https://arxiv.org/abs/2502.06773

6. ReasonFlux: Hierarchical LLM Reasoning via Scaling Thought Templates https://arxiv.org/abs/2502.06772

7. Training Language Models to Reason Efficiently https://arxiv.org/abs/2502.04463

8. “o3 can't multiply 10 digit numbers, but here is the acc of a 14m transformer that teaches itself how to do it, with iterative self-improvement” https://x.com/DimitrisPapail/status/1889755872642970039

9. Scaling Pre-training to One Hundred Billion Data for Vision Language Models https://arxiv.org/abs/2502.07617

10. Can 1B LLM Surpass 405B LLM? Rethinking Compute-Optimal Test-Time Scaling https://arxiv.org/abs/2502.06703

11. DeepScaleR: Surpassing O1-Preview with a 1.5B Model by Scaling RL https://pretty-radio-b75.notion.site/DeepScaleR-Surpassing-O1-Preview-with-a-1-5B-Model-by-Scaling-RL-19681902c1468005bed8ca303013a4e2 (but see this thread: https://x.com/DimitrisPapail/status/1889422843982524558)

12. 8GB of high-quality reasoning math https://huggingface.co/datasets/open-r1/OpenR1-Math-Raw

AI politics:

1. 'Possibly by 2026 or 2027 (and almost certainly no later than 2030), the capabilities of AI systems will be best thought of as akin to an entirely new state populated by highly intelligent people appearing on the global stage' https://www.anthropic.com/news/paris-ai-summit

2. Sam Altman says the $500 billion Stargate project will be dwarfed in a few years with $5 trillion AI compute clusters, despite the recent DeepSeek release https://youtu.be/oEdlwfD5vK8?si=UpmTkOCaUxmQYFc8&t=664

3. The Paris AI Anti-Safety Summit https://www.lesswrong.com/posts/qYPHryHTNiJ2y6Fhi/the-paris-ai-anti-safety-summit

4. Why Did Elon Musk Just Offer to Buy Control of OpenAI for $100 Billion? https://www.lesswrong.com/posts/tdb76S4viiTHfFr2u/why-did-elon-musk-just-offer-to-buy-control-of-openai-for

5. Meta Platforms is reportedly in discussions to acquire South Korean AI chip startup FuriosaAI. https://www.koreatimes.co.kr/www/tech/2025/02/129_392093.html

6. OpenAI set to finalize first custom chip design this year https://www.reuters.com/technology/openai-set-finalize-first-custom-chip-design-this-year-2025-02-10/

Science and Technology:

1. Princeton neuroscientists crack the code of how we make decisions https://pni.princeton.edu/news/2025/princeton-neuroscientists-crack-code-how-we-make-decisions

2. Physicists have built a new type of digital-analogue quantum simulator in Google’s laboratory, which can be used to study physical processes with unprecedented precision and flexibility. https://www.psi.ch/en/news/media-releases/unique-quantum-simulator-opens-door-to-new-research

3. Anduril Takes Over $22 Billion Contract to Build Technomancers for U.S. Army https://www.corememory.com/p/anduril-takes-over-22-billion-contract

4. Einstein Was Right – Euclid Just Captured Space-Time Warping in a Perfect Cosmic Ring https://www.esa.int/Science_Exploration/Space_Science/Euclid/Euclid_discovers_a_stunning_Einstein_ring

13.02.202509:20

Nvidia put r1 in a loop for 15 minutes and it generated: "better than the optimized kernels developed by skilled engineers in some cases"

Inference-time budget affects the agent’s solving rate. Allocating more than 10 minutes per problem in the Level-1 category enables the workflow to produce numerical correct code for most of the 100 problems.

Read more: https://developer.nvidia.com/blog/automating-gpu-kernel-generation-with-deepseek-r1-and-inference-time-scaling/

12.02.202520:11

Sam Altman:

"OPENAI ROADMAP UPDATE FOR GPT-4.5 and GPT-5:

We want to do a better job of sharing our intended roadmap, and a much better job simplifying our product offerings.

We want AI to “just work” for you; we realize how complicated our model and product offerings have gotten.

We hate the model picker as much as you do and want to return to magic unified intelligence.

We will next ship GPT-4.5, the model we called Orion internally, as our last non-chain-of-thought model.

After that, a top goal for us is to unify o-series models and GPT-series models by creating systems that can use all our tools, know when to think for a long time or not, and generally be useful for a very wide range of tasks.

In both ChatGPT and our API, we will release GPT-5 as a system that integrates a lot of our technology, including o3. We will no longer ship o3 as a standalone model.

The free tier of ChatGPT will get unlimited chat access to GPT-5 at the standard intelligence setting (!!), subject to abuse thresholds.

Plus subscribers will be able to run GPT-5 at a higher level of intelligence, and Pro subscribers will be able to run GPT-5 at an even higher level of intelligence. These models will incorporate voice, canvas, search, deep research, and more."

Source: https://x.com/sama/status/1889755723078443244

10.02.202521:07

Image 1: An example of a PISA level 1 Math question.

Image 2: Share unable to reach overall level 1 PISA math and science.

06.03.202511:14

10.02.202522:11

Marriages in China fell by 20% in 2024. Since nearly all births in China are within marriage, this implies further large declines in fertility ahead.

China's TFR was just 1.02 in 2023.

Without advanced AI and robotics, we'll eventually face a global collapse of all welfare systems, followed by a collapse of advanced technologies like smartphones, which require a minimum population of one billion people to be maintained.

18.02.202510:01

The CEO of Unitree, XingXing Wang, posted a dancing video at Rednote against the hype that the previous dance video was AI- or CG- generated.

07.02.202523:09

We finally have an answer to the debate over whether LLMs generalize to new math problems or they merely memorized the answers.

We evaluated them on the AIME 2025 I competition from *yesterday* and the results are good!

Source: https://x.com/mbalunovic/status/1887962694659060204