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OpenAI has produced so many mathematical research findings that it cannot publish them all in a timely manner, and has enlisted three Fields Medalists to vet the work.

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Exclusive: Beating AI News Flash OpenAI has established a "Mathematics and Artificial Intelligence Advisory Group" hosted by Princeton’s Institute for Advanced Study (IAS). The company stated that an internal research model has solved over 100 long-standing open problems spanning multiple mathematical fields, including the previously announced research on the Navier-Stokes Millennium Prize Problem. Most of these findings remain unpublished. The advisory group will assess the significance of these results, their publication approach, and compliance with academic standards. Its first nine members include three Fields Medal winners: Timothy Gowers, Martin Hairer, and Edward Witten. Members will not receive compensation from OpenAI, may publicly criticize the company, and can independently release recommendations. However, the group holds no decision-making power and will not determine the pace of OpenAI’s internal mathematical research. This move is OpenAI’s direct response to recent dissatisfaction from the mathematics community. Earlier, 25 Fields Medal winners including Terence Tao, Yufei Zhao, and Peter Scholze released a joint statement accusing AI companies of framing the solving of major math problems as a benchmark, which has begun to harm mathematical research. The statement acknowledged that large models have advanced rapidly in recent months and can solve several important open problems across fields, but emphasized that mathematics prioritizes the new concepts, methods, and understanding generated from such solutions.

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Coinbase CEO responds to stablecoin yield controversy: Fundamentally distinct from bank interest, so they do not need to be subject to bank capital and liquidity requirements.

Coinbase CEO Brian Armstrong recently appeared on the Money Rehab podcast to address the difference between USDC holder rewards and bank interest, as well as whether Coinbase should adhere to bank capital and liquidity regulatory requirements. Armstrong clarified that the "rewards" users receive for holding USDC on Coinbase are not interest. The underlying USD is allocated to short-term U.S. Treasuries (yielding approximately 3.5%-4%), with a portion of the returns passed back to users—similar to a loyalty program. Bank interest, by contrast, derives from the fractional reserve system, where banks lend out customer funds and assume corresponding risks. To explicitly distinguish the two, Coinbase intentionally uses the term "rewards". In response to calls for crypto platforms to be held to the same capital, liquidity, and FDIC insurance standards as banks, Armstrong emphasized that stablecoins must maintain 100% reserves under the GENIUS Act, with funds held in short-term U.S. Treasuries. This structure eliminates fractional reserve risks and the potential for bank-style runs. Banks face strict regulation due to their higher operational risk, while stablecoins have an inherently different framework. He criticized large banks for lobbying to limit competition, stating this harms consumer interests. Meanwhile, Armstrong noted that Coinbase is assisting both community banks and large banks in integrating stablecoin technology, with the goal of mutual benefits for all parties. These remarks come as the Clarity Act encounters obstacles in the Senate. Armstrong believes U.S. crypto regulatory clarity will eventually be achieved, whether through legislation or regulatory agency rules.

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North Korea-linked hacker group TraderTraitor launches a new round of attacks using a malicious Terraform project.

According to SlowMist, North Korea-linked threat actor TraderTraitor (also known as UNC4899 and Jade Sleet) has launched a new attack, recently infiltrating an Indian IT services firm with no ties to the crypto industry. The attacker posted fake job listings on GitHub, using "technical interview assignments" as bait to phish DevOps and crypto engineers. After victims download the project, a malicious .terraform.lock.hcl file points to a Terraform Provider domain controlled by the attacker. Running `terraform init` triggers the download and execution of the malicious Provider module. The attack deploys Rust/ARM64 backdoors FLATROOF and ROOFDECK on victims’ macOS devices; these two malware families were previously used in LayerZero attacks. They can steal credentials and sensitive data, execute shell commands, collect and exfiltrate files, and gain access to cloud services and code repositories. SlowMist warns that TraderTraitor’s latest targets are no longer limited to the crypto sector—the attacker may now be focusing on developers’ access to cloud and API services including AWS, GCP, OVH, and OpenStack. Enterprises should exercise caution when handling unfamiliar Terraform Providers and code repositories from recruiters, and avoid using personal or work devices to run unvetted interview projects.

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Luo Fuli: The R&D challenges of MiMo-V2.6 have exceeded those of DeepSeek R1 that I have worked on.

Beating AI Express (Insight): Luo Fuli, head of Xiaomi’s MiMo project, further explained the current round of reinforcement learning after the release of MiMo-V2.6. She noted that she previously worked on DeepSeek R1, and in her view, the research innovations and engineering challenges behind MiMo-V2.6 exceed those of R1. She also clarified why MiMo uses both MixRL and MOPD: MixRL trains verifiable tasks such as code, general agents, vision, and cybersecurity all within a single round of reinforcement learning. MOPD, meanwhile, handles long, hard-to-verify, or subjectively rewarded tasks by training them separately first, then integrating their capabilities back into the main model. Tasks like games and 3D take too long to run at once and are difficult to auto-assess for correctness. If grouped with code and other tasks in the same RL round, they would significantly slow down training. As a result, MiMo trains these tasks separately and integrates their capabilities into the main model via MOPD.

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Uniswap team members have cast doubt on the "death" narrative surrounding Robinhood Chain, noting that its daily trading volume remains above $1 billion.

Uniswap team member niko published a post stating that after Robinhood Chain’s recent large-scale innovation boosted market performance, other blockchains started replicating its ecosystem projects. Meanwhile, some KOLs and venture capital institutions have repeatedly claimed Robinhood Chain is declining, directing users to similar projects on other chains. Niko pointed out that contrary to these claims, Robinhood Chain’s daily trading volume still exceeds $1 billion, and its stock token trading scale is growing rapidly. He believes the bearish narrative surrounding Robinhood Chain’s ecosystem is clearly at odds with actual on-chain data.

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DeepSeek’s first CFO is now in place: Yan Wentao has reported for duty.

Insight Beating AI News Flash: An exclusive report from *Investment Journal* reveals that Yan Wentao officially joined DeepSeek on Monday and reported for duty, becoming the firm’s first Chief Financial Officer (CFO). Born in 1991, Yan graduated from Fudan University and joined Hillhouse Venture Capital in 2020. He has previously been involved in projects including MiniMax, Zhipu AI, and ByteDance. His appointment comes as DeepSeek intensively advances capital operations: the company is finalizing its Series B financing, planning to raise 50 billion yuan at a pre-money valuation of 500 billion yuan. Meanwhile, DeepSeek has hired CITIC Securities to prepare for a potential IPO on the STAR Market.

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Hyperliquid has burned 42,300 HYPE tokens in the past 24 hours, with the burn volume jumping more than 88% sequentially.

According to on-chain data, Hyperliquid burned 42,300 HYPE tokens over the past 24 hours, valued at roughly $4 million, marking an over 88% month-over-month rise. In the past seven days, the platform burned 226,500 HYPE tokens, pushing its cumulative total burn to 47,397,098 HYPE, which accounts for 4.74% of the token’s total supply.

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