Search “Reasoning”

Li Jianshu and Wang Jian on AI and Mathematics: From an Excess of Answers to Two-Way Empowerment

ScienceNet reporters interviewed Li Jianshu, an academician of the Chinese Academy of Sciences, and Wang Jian, an academician of the Chinese Academy of Engineering, to discuss the controversies and directions surrounding AI's entry into mathematical research. The article mentions that in May of this year, Google DeepMind's AI agent solved 9 previously unsolved Erdős problems and tackled 44 open mathematical conjectures; OpenAI recently published 722 mathematical manuscripts generated by its internal AI models on GitHub; and 25 Fields Medalists, including Terence Tao and Deng Yu, jointly issued an open letter warning of a serious misalignment between AI and mathematics. Li Jianshu believes that AI may change the paradigm of mathematical research and points out that mathematics has done far from enough for AI; Wang Jian believes that AI's reasoning ability currently comes mainly from code, and that learning deeper reasoning from mathematical data will bring greater gains. The Institute for Advanced Study in Mathematics at Zhejiang University, where the two work, and Zhijiang Laboratory jointly launched the Future Mathematics Program, which focuses on four aspects: mathematical foundation models, formal verification, AI mathematical mechanisms, and interdisciplinary empowerment.

SemiAnalysis Analyst Interprets Anthropic S-1: The Ledger Behind the Valuation and AGI Narrative

The Verge's Decoder podcast invited SemiAnalysis analyst Joey Brookhart to break down the S-1 filed by Anthropic, discussing its potential Nasdaq listing at a valuation of $1.5 trillion to $2 trillion. Brookhart said Anthropic has achieved over $70 billion in ARR, with inference gross margins turning from negative 94% two years ago to positive 85%, and revenue per megawatt of inference at about $65 million, but revenue is highly concentrated in coding scenarios, and about 70% of compute is used for training and research. He also mentioned that Anthropic has $500 billion to $600 billion in compute commitments over the next 7 to 10 years, and compared OpenAI's more consumer-oriented business structure.

Nathan Lambert: The outside world underestimates the scale of remaining funds that can be invested in the sovereign AI sector

Nathan Lambert commented that people underestimate how much money can still be invested in the sovereign AI sector. This tweet cites Giotto AI's announcement of the release of two European sovereign AI models, Giotto Alto and Giotto Solo, of which Alto is aimed at advanced reasoning, is freely open, and is hosted on European cloud infrastructure, while Solo can run on a single GPU.

Why AI Audit Tools Are Supplied by the Audited Party: Verification of Four Security Incidents and Seven Papers in One Week

Using four security incidents within the week of October 16 to 23 as its thread—including two PHP remote code execution vulnerabilities discovered by AI, the backdoored LiteLLM version v1.107.0 surviving on PyPI for about two hours and being downloaded roughly 49,000 times, the OpenCode console leaking third-party model keys for 1.4% of users, and Microsoft reporting that a human organization used the open-source multi-agent penetration framework ARTEX to attack the supply chain—the article discusses the common problems facing AI auditing. After examining seven papers one by one, the author points out that the faithfulness of latent reasoning self-decoding reaches at most 0.4788, sparse autoencoders are nearly blind to backdoor shifts, probes fail when targeted by the object being optimized, and all three mainstream audit tools originate from the audited party's ecosystem or require borrowing the audited party's permissions. The article also cites the NARCBench multi-agent collusion benchmark from Oxford and New York University, as well as the report by Anthropic and Theorem using Claude to write roughly one billion lines of Rocq formal proofs for 239 entry points across 123 open-source libraries.

Amazon CEO Jassy: AWS's AI business has an annualized revenue of over $25 billion, and $220 billion in capital expenditure for 2026 is still not enough

Amazon CEO Andy Jassy said on the a16z podcast that in the first three years of the generative AI wave, AWS's AI business has reached an annualized revenue run rate of over $25 billion, hundreds of times AWS's roughly $60 million in its early days. He said that under capital expenditure of about $220 billion for 2026, capacity for 2026 is already sold out, 2027 is essentially sold out, and a considerable portion of 2028 has also been sold, and that inference costs are still an order of magnitude too expensive, which is the main obstacle to widespread enterprise adoption of AI. He also mentioned that the Bedrock team rebuilt the inference engine with 6 engineers in 76 days, a task that previously required 40 people for a year.

Liang Wenfeng needs his own Tibo: DeepSeek product department integration and the Agent path

DeepSeek has integrated the Harness with the web, App, and open platform teams into a product department, led by Cui Tianyi, and the official website has posted recruitment positions in two directions: AI product manager and Agent Harness. The article uses OpenAI Codex lead Tibo Sottiaux and the Anthropic Claude Code team as examples to explain how the execution capabilities of coding tools can be extended into a general work task entry point. DeepSeek, while open-sourcing Harness and the inference framework DeepInfer, is also facing cost pressure on caching and transmission brought by long tasks.

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DeepSeek's single cluster processes 155 trillion tokens per day, generating $38 in revenue per GPU-hour

Yuchen Jin, citing data disclosed by DeepSeek, said that a single cluster currently processes 155 trillion tokens per day and generates $38 in revenue per GPU-hour (off-peak pricing). He noted that DeepSeek has not only open-sourced its inference engine but also disclosed revenue figures, though it did not specify which GPU models were used; DeepInfer supports both NVIDIA Blackwell and Huawei Ascend. Based on an estimated B300 rental price of $7 per GPU-hour, the gross margin is approximately 82%.

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Claude cracks the mystery of the P-256 elliptic curve seed origin in half an hour

AYi AI Notes relays that Claude cracked, in under half an hour, the mystery of the random seed origin of the P-256 elliptic curve that had puzzled the cryptography community for 26 years; the seed was not a backdoor, but the 1,842nd candidate produced in timestamp order by an engineer in 1997 calling the C language lrand48 function. The author stresses that this is not an attack on the mathematical principles of encryption, bank accounts and encrypted communications need no changes, and the related bounty has doubled to $36,864 and been donated to an open-source security foundation. The author believes this event demonstrates the model's reasoning ability to piece together clues across programming habits, compiler characteristics, and mathematical verification.

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