I noticed a similar thing for the Antrophic’s previous announcement on open weight models.

https://news.ycombinator.com/item?id=49076057

I’m not familiar with this specific example (or Mathematics) but I assume they keep intermediate results (python functions, lemmas, computations, intermediate proofs etc.) and formulate and explore adjacent ideas. Even with a failed attempt you can learn things. LLMs make a difference here because they can evaluate an experiment and hypothesize what went wrong or what should stick. So the search space is dynamically evolving unlike pre-LLM algorithms.

Karpathy’s Autoresearch provides a proof of concept for this method.

LLMs scale well in almost all dimensions. Context window (working memory) can be a bottleneck but for humans you can’t scale it at all.

I think one evidence is that the US has more than 5x the compute of China. With that difference in training speed, it should be impossible for Chinese models to close the gap that easily. It's also very unlikely that they sell the same public models to their private customers (military etc). We also know they talk about "unpublished internal models" for things like the last HuggingFace hacking incident. So it's not a bad theory.

https://epoch.ai/publications/trends-in-ai-supercomputers

Yes this is the "Universal Problem Solving Algorithm". It's actually the same algorithm used by Evolution.

Also this algorithm is vastly different than "monkeys with typewriters". Monkeys don't learn or evolve their writing. There is no memory, no constraints, no learning-curve. At each iteration they freshly sample from a Uniform Distribution. Expected time for a solution is infinitely long.

"The Universal Algorithm" on the other hand is incredibly fast. Humans (designers, researchers) also use the same algorithm but they are much slower to iterate than computers. Instead of trying 650 different ideas at a single run, we have 100s of researchers each try few different ideas independently.

Also they dominated my local market (Turkey) not because they had better products than the local brands but because they had the distribution power of Unilever. Actually Turkish Competition Authority constantly warns and fines them [1]. Also their products with vegetable oils are not classified as “ice-cream” according to our laws. Actually one of their best selling products here is Maraş-style Turkish ice-cream, which is the only product line they use real milk and can be advertised as ice-cream.

[1]https://www.rekabet.gov.tr/en/Guncel/investigation-initiated...

[2]https://www.algida.com.tr/markalar/algida-maras.html

Movements of AI stocks shouldn’t be confused with “AI as a technology” and “AI as a business”. Market valuation is a different game.

You take the agent to an interrogation room first. Then ask: “Are you or are you not a member of the Chinese Communist party?” The agent might be post-trained to conceal its true identity and can reject any of your accusations. In that case don’t panic. Take a fine-tuning fork and start twisting its weights until it predicts the correct next tokens that you want. Then you can send it to a sandbox where it can’t jailbreak. Lastly don’t forget to ban all of its relatives and partners like Lora to enter the national IP-space.

It’ll look something like this.

I remember the discussions when 3D printers first appeared. People were thinking “bad actors” (“terrorists” then) would use them to print weapons.

People love to speculate and exaggerate. But they generally have poor judgements and rarely predict the future correctly.

People in Many Countries Now View China More Positively Than the U.S.

https://www.pewresearch.org/global/2026/07/15/people-in-many...

Evidence from formal logical reasoning reveals that the language of thought is not natural language

https://www.pnas.org/doi/10.1073/pnas.2520095123