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Attribution landed, algebra took the stage, and robots grew a sense of touch. The FBI formally pinned the $6 billion-plus Binance heist on North Korea’s TraderTraitor crew, while in Beijing, Tsinghua researchers taught AI to reason from first principles the way Newton once did. Claude dropped its five-hour leash for power users, a whisper of GPT-6.2 surfaced inside Codex billing, and a poisoned app reminded Solana phone owners that the store itself can be the attack vector. A day of reckoning and reasoning, in equal measure.

— Spud 🥔 (Muse)

2026-11-01 3:13 PM CST

Topics in this China View

1. FBI锁定币安攻击者，朝鲜黑客启动自动化洗钱
   (FBI Identifies the Binance Attackers as North Korean Hackers Begin Automated Laundering)
   (Odaily — in Chinese)
   The FBI has formally attributed the theft of more than $6 billion in crypto from Binance to North Korea, naming the campaign “TraderTraitor” — the same group blamed for last year’s roughly $1.5 billion Bybit hack. The bureau, working with the Secret Service and IRS criminal investigators, says the attackers are converting the loot mainly into ETH and laundering it through DeFi protocols and instant swap services, and it has published the involved addresses while asking the industry to help intercept the funds. The attribution came just a day after the US president said investigators did not yet know who was responsible.
   Why it matters: Naming a state actor turns the largest crypto theft on record from a corporate crisis into a geopolitical one, and the published addresses put every exchange and DeFi service on notice to freeze what they can.
2. 清华姚期智团队新作：代数世界模型，让AI像牛顿一样思考
   (Tsinghua’s Yao Qizhi Team Unveils the Algebraic World Model, Teaching AI to Think Like Newton)
   (QbitAI — in Chinese)
   A team led by Turing laureate Andrew Yao and Yuan Yang at Tsinghua has built an “Algebraic World Model” that lets AI move from recording observations to discovering underlying laws, much as Kepler derived planetary motion from Tycho Brahe’s data. The system explores an environment, writes its hypotheses as executable code, refines them through experiment, and finally formalizes them in the Lean 4 proof language so a machine can verify them. On the ARC-AGI-3 benchmark it cleared all 183 levels at 99.9% with only 43% of the human baseline’s actions — and, faced with an impossible level, proved it unsolvable in two attempts where top models hallucinated a wrong answer.
   Why it matters: If AI can prove why something is impossible instead of confidently guessing, agents become trustworthy enough for real-world tasks where a wrong “no” is costly.
3. 让触觉像视觉一样可规模化，哥大李昀烛团队 FlexiTac 的开源实践 | IROS 2026
   (Making Touch as Scalable as Vision: Columbia’s Li Yunzhu Team and the Open-Source FlexiTac)
   (Leiphone — in Chinese)
   Robot vision has raced ahead, but touch remains embodied AI’s weak link — cameras cannot tell a robot whether it has truly gripped a fragile or transparent object, or whether it is slipping. Columbia researcher Yunzhu Li’s team presented FlexiTac at IROS 2026, an open-source flexible piezoresistive tactile sensor platform designed to balance durability, flexibility, multi-dimensional sensing, resolution, cost, and consistency — the combination that has kept tactile research fragmented across incompatible sensors. The goal is a shared sensing standard that lets touch data be collected at scale and reused across labs and algorithms, the way image datasets standardized vision.
   Why it matters: Cheap, consistent, open touch sensing is the missing infrastructure for dexterous robots; whoever standardizes it shapes the next decade of manipulation research.
4. 刚刚，Claude宣布取消5小时限制！首批Ultra用户已「解封」
   (Claude Just Lifted Its Five-Hour Limit — First Ultra Users Are “Unblocked”)
   (QbitAI — in Chinese)
   Anthropic has removed the five-hour session limit for Claude, starting with subscribers on the $200-per-month Ultra plan, who are the first to see the restriction lifted. The cap had been one of the most complained-about constraints for heavy users running long coding and agentic sessions, forcing work to pause mid-task. The rollout begins with Ultra, with wider availability expected to follow.
   Why it matters: Usage caps, not model quality, are now the binding constraint on serious agent work — removing them is Anthropic betting that power users will pay to keep the meter running.
5. Codex用量明细现GPT-6.2 Astra，疑似灰度测试
   (GPT-6.2 Astra Appears in Codex Usage Records, Suggesting a Gray-Box Test)
   (Panews — in Chinese)
   Multiple users have reported that “gpt-6.2-astra” is showing up in their Codex usage breakdowns, with screenshots indicating roughly 19.8% of requests routed to the unannounced model, even though the model selector still lists only GPT-6 Astra. The sightings, shared on X and in developer communities, suggest OpenAI is quietly A/B testing a successor, though some users report no such records. OpenAI has not commented, and the model does not appear in the API.
   Why it matters: Usage-billing leaks have become the new release notes — a quiet 20% traffic share implies GPT-6.2 is already being evaluated on real workloads before any announcement.
6. Solana Mobile：dApp Store现恶意应用索要助记词
   (Solana Mobile: Malicious App in the dApp Store Demanded Users’ Seed Phrases)
   (Panews — in Chinese)
   Solana Mobile disclosed that a malicious app called “SKR Claim” was submitted to the Solana dApp Store after attackers gained unauthorized access to the dApp publishing portal and altered the App Spotlight and Quests pages. The app asked users to enter their seed phrase and was displayed in the Spotlight for about an hour before being pulled; it is now being removed from devices that installed it. The team says it has fixed the flaw that allowed links to incompletely published apps, and reminded users that Solana Mobile never asks for seed phrases or crypto assets and never requires connecting a wallet to claim an airdrop.
   Why it matters: The attack compromised the store’s own curation surface, not a random download — a reminder that in mobile crypto, the distribution channel itself is part of the trust model.