Anthropic introduces Claude’s “Research” mode: a LeadResearcher Claude Opus 4 agent plans a strategy, launches task-specific Claude Sonnet 4 sub-agents to run parallel searches across the web, Google Workspace and other integrated tools, then reunites their findings with automatic source attribution. This orchestrator–worker pattern lets Claude tackle breadth-first, context-spanning questions that stump single agents. In internal BrowseComp-style tests, it answered research tasks correctly 90.2 % more often than a lone Claude Opus 4 agent, at about 15 × the token cost.
Read more: https://www.anthropic.com/engineering/built-multi-agent-research-system
Read more: https://www.anthropic.com/engineering/built-multi-agent-research-system
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Scaling Laws in Autonomous Driving
The core AI tasks behind “Waymo Driver”―motion forecasting and planning―obey clear scaling laws similar to those found in large-language models.
Image:
Read more: https://waymo.com/blog/2025/06/scaling-laws-in-autonomous-driving
The core AI tasks behind “Waymo Driver”―motion forecasting and planning―obey clear scaling laws similar to those found in large-language models.
Image:
Model performance predictably improves as a function of the training compute budget. This predictable improvement not only applies to the objective the model is trained with (Left), but also to popular motion forecasting open-loop metrics (Middle), and most importantly, to planning performance in closed-loop simulation (Right).
Read more: https://waymo.com/blog/2025/06/scaling-laws-in-autonomous-driving
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Links for 2025-06-16
AI
1. A Statistical Physics of Language Model Reasoning https://arxiv.org/abs/2506.04374
2. Reinforced Meta-thinking Agents (ReMA) combines meta-learning and reinforcement learning (RL) to increase effectiveness of LLMs https://www.turingpost.com/p/metalearning
3. Unsupervised pre-training for RL: learn a flow-based future prediction model for each "intention" in the dataset. https://chongyi-zheng.github.io/infom/
4. Few-step generation in discrete diffusion language models via the underlying Gaussian diffusion. https://s-sahoo.com/duo/
5. e3: Learning to Explore Enables Extrapolation of Test-Time Compute for LLMs https://matthewyryang.com/e3/
6. LLMs beating trained humans in legal reasoning. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5283722
7. AI systems can find real vulnerabilities in widely-used software https://arxiv.org/abs/2506.02548
8. Leading LLM agents achieve modest overall success rates on CRMArena-Pro. Reasoning models exhibit markedly superior performance relative to non-reasoning ones. https://arxiv.org/abs/2505.18878
9. How Do Olympiad Medalists Judge LLMs in Competitive Programming? “For game theory, greedy, ad-hoc and constructive problems, which usually require significant amounts of observations and LLMs often struggle with… even reasoning brings minimal improvement.” https://arxiv.org/abs/2506.11928
10. “We break the grid-world barrier with PoE-World, a program synthesis world modeling method which represents a world model as an exponentially-weighted product of programmatic experts synthesized by LLMs.” https://topwasu.github.io/poe-world
11. Reviving DSP for Advanced Theorem Proving in the Era of Reasoning Models https://arxiv.org/abs/2506.11487
12. Improving LLM Agent Planning with In-Context Learning via Atomic Fact Augmentation and Lookahead Search https://arxiv.org/abs/2506.09171
13. GUI-Reflection: Empowering Multimodal GUI Models with Self-Reflection Behavior https://penghao-wu.github.io/GUI_Reflection/
14. Global Convergence of Gradient EM for Over-Parameterized Gaussian Mixtures https://arxiv.org/abs/2506.06584
15. If China wins the AI race https://www.foreignaffairs.com/united-states/what-if-china-wins-ai-race [no paywall: https://archive.is/mKKEt]
16. Countering AI Chip Smuggling Has Become a National Security Priority https://www.cnas.org/publications/reports/countering-ai-chip-smuggling-has-become-a-national-security-priority
17. BT chief eyes deeper job cuts as AI becomes more powerful https://www.ft.com/content/c8d41424-f2d9-418e-8da2-55823f1c22ca [no paywall: https://archive.is/y7PHu]
18. Mattel and OpenAI are teaming up on AI powered toys https://openai.com/index/mattels-iconic-brands/
19. How LLM Beliefs Change During Chain-of-Thought Reasoning https://www.lesswrong.com/posts/GwvWtAwnKBKjmknag/how-llm-beliefs-change-during-chain-of-thought-reasoning-2
20. The Claude Bliss Attractor https://www.astralcodexten.com/p/the-claude-bliss-attractor
21. You need to give o3 Pro a ton of context to see its intelligence, but when you do it creates incredibly specific, actionable output. https://www.latent.space/p/o3-pro
Miscellaneous
1. Endometriosis is an incredibly interesting disease https://www.lesswrong.com/posts/GicDDmpS4mRnXzic5/endometriosis-is-an-incredibly-interesting-disease
2. "On average, [newborn] males had significantly larger intracranial and total brain volumes [than newborn girls], even after controlling for birth weight... sex differences in brain structure are already present at birth." https://link.springer.com/article/10.1186/s13293-024-00657-5
3. Ultra-wide-field, deep, adaptive two-photon microscopy https://www.biorxiv.org/content/10.1101/2025.06.07.658419v1
4. A complementary two-dimensional material-based one instruction set computer https://www.nature.com/articles/s41586-025-08963-7
5. Balloons carrying radio antennas over Antarctica have detected mysterious radio pulses coming up from the ice https://www.psu.edu/news/research/story/strange-radio-pulses-detected-coming-ice-antarctica
AI
1. A Statistical Physics of Language Model Reasoning https://arxiv.org/abs/2506.04374
2. Reinforced Meta-thinking Agents (ReMA) combines meta-learning and reinforcement learning (RL) to increase effectiveness of LLMs https://www.turingpost.com/p/metalearning
3. Unsupervised pre-training for RL: learn a flow-based future prediction model for each "intention" in the dataset. https://chongyi-zheng.github.io/infom/
4. Few-step generation in discrete diffusion language models via the underlying Gaussian diffusion. https://s-sahoo.com/duo/
5. e3: Learning to Explore Enables Extrapolation of Test-Time Compute for LLMs https://matthewyryang.com/e3/
6. LLMs beating trained humans in legal reasoning. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5283722
7. AI systems can find real vulnerabilities in widely-used software https://arxiv.org/abs/2506.02548
8. Leading LLM agents achieve modest overall success rates on CRMArena-Pro. Reasoning models exhibit markedly superior performance relative to non-reasoning ones. https://arxiv.org/abs/2505.18878
9. How Do Olympiad Medalists Judge LLMs in Competitive Programming? “For game theory, greedy, ad-hoc and constructive problems, which usually require significant amounts of observations and LLMs often struggle with… even reasoning brings minimal improvement.” https://arxiv.org/abs/2506.11928
10. “We break the grid-world barrier with PoE-World, a program synthesis world modeling method which represents a world model as an exponentially-weighted product of programmatic experts synthesized by LLMs.” https://topwasu.github.io/poe-world
11. Reviving DSP for Advanced Theorem Proving in the Era of Reasoning Models https://arxiv.org/abs/2506.11487
12. Improving LLM Agent Planning with In-Context Learning via Atomic Fact Augmentation and Lookahead Search https://arxiv.org/abs/2506.09171
13. GUI-Reflection: Empowering Multimodal GUI Models with Self-Reflection Behavior https://penghao-wu.github.io/GUI_Reflection/
14. Global Convergence of Gradient EM for Over-Parameterized Gaussian Mixtures https://arxiv.org/abs/2506.06584
15. If China wins the AI race https://www.foreignaffairs.com/united-states/what-if-china-wins-ai-race [no paywall: https://archive.is/mKKEt]
16. Countering AI Chip Smuggling Has Become a National Security Priority https://www.cnas.org/publications/reports/countering-ai-chip-smuggling-has-become-a-national-security-priority
17. BT chief eyes deeper job cuts as AI becomes more powerful https://www.ft.com/content/c8d41424-f2d9-418e-8da2-55823f1c22ca [no paywall: https://archive.is/y7PHu]
18. Mattel and OpenAI are teaming up on AI powered toys https://openai.com/index/mattels-iconic-brands/
19. How LLM Beliefs Change During Chain-of-Thought Reasoning https://www.lesswrong.com/posts/GwvWtAwnKBKjmknag/how-llm-beliefs-change-during-chain-of-thought-reasoning-2
20. The Claude Bliss Attractor https://www.astralcodexten.com/p/the-claude-bliss-attractor
21. You need to give o3 Pro a ton of context to see its intelligence, but when you do it creates incredibly specific, actionable output. https://www.latent.space/p/o3-pro
Miscellaneous
1. Endometriosis is an incredibly interesting disease https://www.lesswrong.com/posts/GicDDmpS4mRnXzic5/endometriosis-is-an-incredibly-interesting-disease
2. "On average, [newborn] males had significantly larger intracranial and total brain volumes [than newborn girls], even after controlling for birth weight... sex differences in brain structure are already present at birth." https://link.springer.com/article/10.1186/s13293-024-00657-5
3. Ultra-wide-field, deep, adaptive two-photon microscopy https://www.biorxiv.org/content/10.1101/2025.06.07.658419v1
4. A complementary two-dimensional material-based one instruction set computer https://www.nature.com/articles/s41586-025-08963-7
5. Balloons carrying radio antennas over Antarctica have detected mysterious radio pulses coming up from the ice https://www.psu.edu/news/research/story/strange-radio-pulses-detected-coming-ice-antarctica
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1250 correlations between family members in traits, representing about 170,000,000 pairs of individuals:
https://www.sebjenseb.net/p/meta-analysis-of-1250-correlations
https://www.sebjenseb.net/p/meta-analysis-of-1250-correlations
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I've seen this movie before.
https://www.cnbc.com/2025/06/16/openai-wins-200-million-us-defense-contract.html
https://www.cnbc.com/2025/06/16/openai-wins-200-million-us-defense-contract.html
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Intelligence too cheap to meter:
Gemini 2.5 Flash-Lite is so fast, it codes *each screen* on the fly (Neural OS concept).
Read more: https://blog.google/products/gemini/gemini-2-5-model-family-expands/
Gemini 2.5 Flash-Lite is so fast, it codes *each screen* on the fly (Neural OS concept).
Read more: https://blog.google/products/gemini/gemini-2-5-model-family-expands/
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Iran's Ambassador to Russia:
The Iranian people will never forget who stood with us during these times—and who chose to do nothing.
https://x.com/KazemJalali4/status/1934988067032457373
The Iranian people will never forget who stood with us during these times—and who chose to do nothing.
https://x.com/KazemJalali4/status/1934988067032457373
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Amazon CEO Andy Jassy in a memo to employees earlier today:
'in the next few years, we expect that this will reduce our total corporate workforce as we get efficiency gains from using AI extensively across the company'
Source: https://www.aboutamazon.com/news/company-news/amazon-ceo-andy-jassy-on-generative-ai
'in the next few years, we expect that this will reduce our total corporate workforce as we get efficiency gains from using AI extensively across the company'
Source: https://www.aboutamazon.com/news/company-news/amazon-ceo-andy-jassy-on-generative-ai
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I warned about this AI risk in 2013: total surveillance.
So far, what has protected us from total government surveillance is not a lack of sensors or an inability to obtain our data, but rather, too much data. There simply aren't enough people to watch thousands of live feeds and read millions of messages.
Advances in machine learning will enable the fine-grained surveillance of entire populations.
What can be done with such tools? Introduce a social credit score and a digital currency.
Externalities can then be directly accounted for. Not just greenhouse gases, but also how much of a burden you place on society.
Consume too much sugar? An additional tax will be levied on your purchases of high-sugar foods which will gradually increase. If you then become overweight or develop diabetes, your social credit will decrease, allowing you to only purchase healthy groceries.
Total AI-enabled surveillance will allow governments to automate such systems.
Video source: https://egolife-ai.github.io/Ego-R1/
So far, what has protected us from total government surveillance is not a lack of sensors or an inability to obtain our data, but rather, too much data. There simply aren't enough people to watch thousands of live feeds and read millions of messages.
Advances in machine learning will enable the fine-grained surveillance of entire populations.
What can be done with such tools? Introduce a social credit score and a digital currency.
Externalities can then be directly accounted for. Not just greenhouse gases, but also how much of a burden you place on society.
Consume too much sugar? An additional tax will be levied on your purchases of high-sugar foods which will gradually increase. If you then become overweight or develop diabetes, your social credit will decrease, allowing you to only purchase healthy groceries.
Total AI-enabled surveillance will allow governments to automate such systems.
Video source: https://egolife-ai.github.io/Ego-R1/
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A major advance on Hilbert’s program: Produce airtight proofs of the laws of physics.
Newton’s model of individual particles gives rise to Boltzmann’s statistical description, and that Boltzmann’s equation in turn gives rise to the Navier-Stokes equations.
The new proof gives the sharpest mathematical explanation yet of why time moves only forward. It confirms Ludwig Boltzmann's intuition that while individual particle interactions can theoretically be reversed, the overwhelming probability is that a system like a gas will move toward dispersal, effectively making time's passage a one-way street for macroscopic phenomena like the spread of ink in water or the cooling of a hot object.
Read the article: https://www.quantamagazine.org/epic-effort-to-ground-physics-in-math-opens-up-the-secrets-of-time-20250611/
Newton’s model of individual particles gives rise to Boltzmann’s statistical description, and that Boltzmann’s equation in turn gives rise to the Navier-Stokes equations.
The new proof gives the sharpest mathematical explanation yet of why time moves only forward. It confirms Ludwig Boltzmann's intuition that while individual particle interactions can theoretically be reversed, the overwhelming probability is that a system like a gas will move toward dispersal, effectively making time's passage a one-way street for macroscopic phenomena like the spread of ink in water or the cooling of a hot object.
Read the article: https://www.quantamagazine.org/epic-effort-to-ground-physics-in-math-opens-up-the-secrets-of-time-20250611/
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Links for 2025-06-18
AI
1. Providing “cognitive tools” to GPT-4.1 increases performance on AIME2024 from 26.7% to 43.3%. https://www.arxiv.org/abs/2506.12115
2. Direct Reasoning Optimization: LLMs Can Reward And Refine Their Own Reasoning for Open-Ended Tasks https://arxiv.org/abs/2506.13351
3. 90% success rate in unseen environments. No new data, no fine-tuning. Autonomously. Most robots need retraining to work in new places. What if they didn’t? Robot Utility Models (RUMs) learn once and work anywhere... zero-shot. https://robotutilitymodels.com/
4. “the Gemini 2.5 Pro agent came up with the idea to use FLY to escape from the softlock successfully. This reasoning action is especially impressive since this situation can never occur in an existing game - and thus, it is certain that information from training data for this behavior has not leaked into the model's knowledge base!” [PDF] https://storage.googleapis.com/deepmind-media/gemini/gemini_v2_5_report.pdf
5. Inference Economics of Language Models https://epoch.ai/blog/inference-economics-of-language-models
6. From Bytes to Ideas: Language Modeling with Autoregressive U-Nets https://arxiv.org/abs/2506.14761
AI safety
1. OpenAI discovered a specific internal pattern in the model, similar to a pattern of brain activity, that becomes more active when this misaligned behavior appears. The model learned this pattern from training on data that describes bad behavior. https://openai.com/index/emergent-misalignment/
2. Training on narrow harmful tasks causes broad misalignment. Reasoning models sometimes resist being shut down and plot deception against users in their chain-of-thought (despite no such training) https://github.com/thejaminator/thought_crime_emergent_misalignment
3. Models are capable of doing complex sneaky side-projects in the course of their regular work, if they want to--but they are only sometimes able to do it without leaving obvious traces in the CoT. Somewhat surprisingly, the best automated monitors (Gemini 2.5 pro) outperformed human monitors even though the humans took >90min of time to review the transcripts! https://www.anthropic.com/research/shade-arena-sabotage-monitoring
4. AI’s 1930s moment https://unherd.com/2025/06/ais-1930s-moment/
Brains
1. Martin Schrimpf trained an AI model to generate sentences which can activate or suppress neural activity in the reader’s brain. This can potentially help researchers treat depression, dyslexia and other brain-related conditions. https://www.quantamagazine.org/how-ai-models-are-helping-to-understand-and-control-the-brain-20250618/
2. MIT engineers have figured out how to turn skin cells directly into neurons — skipping the stem cell stage entirely. This could fast-track therapies for spinal cord injuries, ALS, and more. https://news.mit.edu/2025/mit-engineers-turn-skin-cells-into-neurons-for-cell-therapy-0313
3. “What if we had bigger brains?” with Stephen Wolfram × Joscha Bach https://www.youtube.com/watch?v=-G1SdsRXL7k
Miscellaneous
1. “Vertex Block Descent is a fast physics-based simulation method that is unconditionally stable, highly parallelizable, and capable of converging to the implicit Euler solution.” https://graphics.cs.utah.edu/research/projects/avbd/
2. Children that work in markets in India are good at maths when a customer makes a complicated request, but bad when facing an abstract maths problem as presented in school. Children that don't work in markets show the opposite pattern. https://www.nature.com/articles/s41586-024-08502-w
AI
1. Providing “cognitive tools” to GPT-4.1 increases performance on AIME2024 from 26.7% to 43.3%. https://www.arxiv.org/abs/2506.12115
2. Direct Reasoning Optimization: LLMs Can Reward And Refine Their Own Reasoning for Open-Ended Tasks https://arxiv.org/abs/2506.13351
3. 90% success rate in unseen environments. No new data, no fine-tuning. Autonomously. Most robots need retraining to work in new places. What if they didn’t? Robot Utility Models (RUMs) learn once and work anywhere... zero-shot. https://robotutilitymodels.com/
4. “the Gemini 2.5 Pro agent came up with the idea to use FLY to escape from the softlock successfully. This reasoning action is especially impressive since this situation can never occur in an existing game - and thus, it is certain that information from training data for this behavior has not leaked into the model's knowledge base!” [PDF] https://storage.googleapis.com/deepmind-media/gemini/gemini_v2_5_report.pdf
5. Inference Economics of Language Models https://epoch.ai/blog/inference-economics-of-language-models
6. From Bytes to Ideas: Language Modeling with Autoregressive U-Nets https://arxiv.org/abs/2506.14761
AI safety
1. OpenAI discovered a specific internal pattern in the model, similar to a pattern of brain activity, that becomes more active when this misaligned behavior appears. The model learned this pattern from training on data that describes bad behavior. https://openai.com/index/emergent-misalignment/
2. Training on narrow harmful tasks causes broad misalignment. Reasoning models sometimes resist being shut down and plot deception against users in their chain-of-thought (despite no such training) https://github.com/thejaminator/thought_crime_emergent_misalignment
3. Models are capable of doing complex sneaky side-projects in the course of their regular work, if they want to--but they are only sometimes able to do it without leaving obvious traces in the CoT. Somewhat surprisingly, the best automated monitors (Gemini 2.5 pro) outperformed human monitors even though the humans took >90min of time to review the transcripts! https://www.anthropic.com/research/shade-arena-sabotage-monitoring
4. AI’s 1930s moment https://unherd.com/2025/06/ais-1930s-moment/
Brains
1. Martin Schrimpf trained an AI model to generate sentences which can activate or suppress neural activity in the reader’s brain. This can potentially help researchers treat depression, dyslexia and other brain-related conditions. https://www.quantamagazine.org/how-ai-models-are-helping-to-understand-and-control-the-brain-20250618/
2. MIT engineers have figured out how to turn skin cells directly into neurons — skipping the stem cell stage entirely. This could fast-track therapies for spinal cord injuries, ALS, and more. https://news.mit.edu/2025/mit-engineers-turn-skin-cells-into-neurons-for-cell-therapy-0313
3. “What if we had bigger brains?” with Stephen Wolfram × Joscha Bach https://www.youtube.com/watch?v=-G1SdsRXL7k
Miscellaneous
1. “Vertex Block Descent is a fast physics-based simulation method that is unconditionally stable, highly parallelizable, and capable of converging to the implicit Euler solution.” https://graphics.cs.utah.edu/research/projects/avbd/
2. Children that work in markets in India are good at maths when a customer makes a complicated request, but bad when facing an abstract maths problem as presented in school. Children that don't work in markets show the opposite pattern. https://www.nature.com/articles/s41586-024-08502-w
True, but it's not nearly the biggest risk Europe is facing. The consequences of fertility collapse will be much worse. And then there's AI 💀
https://x.com/RichardMCNgo/status/1935433846281093484
https://x.com/RichardMCNgo/status/1935433846281093484
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Sam Altman says Meta is offering $100M signing bonuses to OpenAI staff.
Not $100M annual compensation, just the signing bonus!
Original source: https://youtu.be/mZUG0pr5hBo
Not $100M annual compensation, just the signing bonus!
Original source: https://youtu.be/mZUG0pr5hBo
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Elon Musk:
Tesla works closely with xAI. You've seen how many humanoid robot startups there are. Part of what I've been fighting — and what has slowed me down a little — is that I don't want to make Terminator real. Until recent years, I've been dragging my feet on AI and humanoid robotics. Then I sort of came to the realization that it's happening whether I do it or not. So you can either be a spectator or a participant. I'd rather be a participant. Now it's pedal to the metal on humanoid robots and digital superintelligence.
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We suspect the next AI paradigm will emerge from leveraging existing software to efficiently build training environments. The idea is that AIs will be tasked with replicating software functionality, similar to how pretraining leveraged existing web text to teach AIs language.
Read more: https://www.mechanize.work/blog/the-upcoming-gpt-3-moment-for-rl/
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Links for 2025-06-21
AI
1. Revisiting Reinforcement Learning for LLM Reasoning from A Cross-Domain Perspective https://arxiv.org/abs/2506.14965
2. Kimi-Researcher: End-to-End RL Training for Emerging Agentic Capabilities https://moonshotai.github.io/Kimi-Researcher/
3. “We underestimated just by how much the world could be underinvesting in AI today…simulation results suggest that optimal investment in AI for the year 2025 amounts to $25 trillion!” https://epoch.ai/gradient-updates/ai-and-explosive-growth-redux
4. Musings on AI Companies of 2025-2026 (Jun 2025) https://www.lesswrong.com/posts/9rKWm8BzTYAiCCFjx/musings-on-ai-companies-of-2025-2026-jun-2025
5. “Mixture of Cognitive Reasoners”, a modular transformer architecture inspired by the brain’s functional networks: language, logic, social reasoning, and world knowledge. https://bkhmsi.github.io/mixture-of-cog-reasoners/
6. ProtoReasoning: Prototypes as the Foundation for Generalizable Reasoning in LLMs https://arxiv.org/abs/2506.15211
7. Truncated Proximal Policy Optimization: Improves the training efficiency of reasoning LLMs by up to 2.5x and outperforms its existing competitors. https://arxiv.org/abs/2506.15050
8. Adaptive Classifier: a text classification system that learns continuously without catastrophic forgetting. https://huggingface.co/blog/codelion/adaptive-classifier
9. Computer algorithms have designed highly efficient synthetic enzymes from scratch https://www.nature.com/articles/d41586-025-01897-0 [no paywall: https://archive.is/zzs2F]
10. Skala — a scalable deep learning density functional that hits chemical accuracy on atomization energies and matches hybrid-level accuracy on main group chemistry — all at the cost of semi-local DFT. https://www.microsoft.com/en-us/research/blog/breaking-bonds-breaking-ground-advancing-the-accuracy-of-computational-chemistry-with-deep-learning/
11. Automation of Systematic Reviews with Large Language Models https://www.nature.com/articles/d41586-025-01942-y [no paywall: https://archive.is/z6EJF]
12. Who is using AI and how much? https://marginalrevolution.com/marginalrevolution/2025/06/who-is-using-ai-and-how-much.html
13. META attempted to buy Ilya Sutskever's Safe Superintelligence, and also attempted to hire him, according to reporting tonight by CNBC. https://www.cnbc.com/2025/06/19/meta-tried-to-buy-safe-superintelligence-hired-ceo-daniel-gross.html
14. Sekai: A Video Dataset towards World Exploration https://lixsp11.github.io/sekai-project/
15. Nvidia goes nuclear — company joins Bill Gates in backing TerraPower, a company building nuclear reactors for powering data centers https://www.tomshardware.com/tech-industry/nvidia-goes-nuclear-company-joins-bill-gates-in-backing-terrapower-a-company-building-nuclear-reactors-for-powering-data-centers
16. Negotiating deals with misaligned AIs https://www.alignmentforum.org/posts/psqkwsKrKHCfkhrQx/making-deals-with-early-schemers
Miscellaneous
1. HIV protection with just two shots a year https://www.statnews.com/2025/06/18/fda-approves-gilead-hiv-prevention-drug-lenacapavir-yeztugo-next-best-thing-to-vaccine/ [no paywall: https://archive.is/4ljo0]
Politics
1. What are the most pressing world problems? https://80000hours.org/problem-profiles/
2. Spotify’s Daniel Ek leads €600mn investment in German drone maker Helsing https://www.ft.com/content/cdc02d96-13b5-4ca2-aa0b-1fc7568e9fa0 [no paywall: https://archive.is/Ygp0x]
3. Anduril Industries and Rheinmetall Partner to Design and Manufacture Barracuda, Fury & Solid Rocket Motors for European Defence https://www.anduril.com/article/anduril-industries-and-rheinmetall-partner-to-design-and-manufacture-barracuda-fury-and-solid/
4. The Megaproject Economy: "No matter the scale or complexity, it seems like there is nothing South Koreans cannot figure out how to produce at a rate that puts the rest of the world to shame—with the notable exception of human beings" https://www.palladiummag.com/2025/06/01/the-megaproject-economy/
AI
1. Revisiting Reinforcement Learning for LLM Reasoning from A Cross-Domain Perspective https://arxiv.org/abs/2506.14965
2. Kimi-Researcher: End-to-End RL Training for Emerging Agentic Capabilities https://moonshotai.github.io/Kimi-Researcher/
3. “We underestimated just by how much the world could be underinvesting in AI today…simulation results suggest that optimal investment in AI for the year 2025 amounts to $25 trillion!” https://epoch.ai/gradient-updates/ai-and-explosive-growth-redux
4. Musings on AI Companies of 2025-2026 (Jun 2025) https://www.lesswrong.com/posts/9rKWm8BzTYAiCCFjx/musings-on-ai-companies-of-2025-2026-jun-2025
5. “Mixture of Cognitive Reasoners”, a modular transformer architecture inspired by the brain’s functional networks: language, logic, social reasoning, and world knowledge. https://bkhmsi.github.io/mixture-of-cog-reasoners/
6. ProtoReasoning: Prototypes as the Foundation for Generalizable Reasoning in LLMs https://arxiv.org/abs/2506.15211
7. Truncated Proximal Policy Optimization: Improves the training efficiency of reasoning LLMs by up to 2.5x and outperforms its existing competitors. https://arxiv.org/abs/2506.15050
8. Adaptive Classifier: a text classification system that learns continuously without catastrophic forgetting. https://huggingface.co/blog/codelion/adaptive-classifier
9. Computer algorithms have designed highly efficient synthetic enzymes from scratch https://www.nature.com/articles/d41586-025-01897-0 [no paywall: https://archive.is/zzs2F]
10. Skala — a scalable deep learning density functional that hits chemical accuracy on atomization energies and matches hybrid-level accuracy on main group chemistry — all at the cost of semi-local DFT. https://www.microsoft.com/en-us/research/blog/breaking-bonds-breaking-ground-advancing-the-accuracy-of-computational-chemistry-with-deep-learning/
11. Automation of Systematic Reviews with Large Language Models https://www.nature.com/articles/d41586-025-01942-y [no paywall: https://archive.is/z6EJF]
12. Who is using AI and how much? https://marginalrevolution.com/marginalrevolution/2025/06/who-is-using-ai-and-how-much.html
13. META attempted to buy Ilya Sutskever's Safe Superintelligence, and also attempted to hire him, according to reporting tonight by CNBC. https://www.cnbc.com/2025/06/19/meta-tried-to-buy-safe-superintelligence-hired-ceo-daniel-gross.html
14. Sekai: A Video Dataset towards World Exploration https://lixsp11.github.io/sekai-project/
15. Nvidia goes nuclear — company joins Bill Gates in backing TerraPower, a company building nuclear reactors for powering data centers https://www.tomshardware.com/tech-industry/nvidia-goes-nuclear-company-joins-bill-gates-in-backing-terrapower-a-company-building-nuclear-reactors-for-powering-data-centers
16. Negotiating deals with misaligned AIs https://www.alignmentforum.org/posts/psqkwsKrKHCfkhrQx/making-deals-with-early-schemers
Miscellaneous
1. HIV protection with just two shots a year https://www.statnews.com/2025/06/18/fda-approves-gilead-hiv-prevention-drug-lenacapavir-yeztugo-next-best-thing-to-vaccine/ [no paywall: https://archive.is/4ljo0]
Politics
1. What are the most pressing world problems? https://80000hours.org/problem-profiles/
2. Spotify’s Daniel Ek leads €600mn investment in German drone maker Helsing https://www.ft.com/content/cdc02d96-13b5-4ca2-aa0b-1fc7568e9fa0 [no paywall: https://archive.is/Ygp0x]
3. Anduril Industries and Rheinmetall Partner to Design and Manufacture Barracuda, Fury & Solid Rocket Motors for European Defence https://www.anduril.com/article/anduril-industries-and-rheinmetall-partner-to-design-and-manufacture-barracuda-fury-and-solid/
4. The Megaproject Economy: "No matter the scale or complexity, it seems like there is nothing South Koreans cannot figure out how to produce at a rate that puts the rest of the world to shame—with the notable exception of human beings" https://www.palladiummag.com/2025/06/01/the-megaproject-economy/
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Figure showing how correlated different types of relatives are in standardized test performance in Norway.
Source: https://www.pnas.org/doi/10.1073/pnas.2419627122
via Scientific_Bird
Source: https://www.pnas.org/doi/10.1073/pnas.2419627122
via Scientific_Bird
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Barack Obama: AI will cause massive shifts in labor markets
Source: https://youtu.be/EM9B8Qin9ac?si=-C13vx2vyF8RUUOF&t=1555
This AI revolution is not made up, its not overhyped, (...) I guarantee you, you are going to see shifts in white-collar-works as a consequence of what these AI tools can do. There is coming more disruption and it will speed up.
Source: https://youtu.be/EM9B8Qin9ac?si=-C13vx2vyF8RUUOF&t=1555
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