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Anthropic researcher resigns, stating that AI may go out of control next year

Anthropic researcher Jacob Coxon announced his resignation and is preparing to leave the AI industry. He has conducted pre-training research at OpenAI and Anthropic over the past three years. He pointed out that neither company has responsibly advanced AI and are competing to create superintelligence that can continue to enhance its own capabilities, "betting our lives on it."He switched from OpenAI to Anthropic this year because the latter places more emphasis on model safety. Coxon acknowledged that Anthropic's safety work is serious, but believes that as long as companies are racing to be the first to create AGI (artificial general intelligence that surpasses humans in a wide range of tasks), safety compromises are unavoidable, and self-discipline from a single company cannot solve the problem. His assessment of the two companies is: many people inside OpenAI still do not truly realize how great this risk is; Anthropic knows the risks but believes others are unreliable, so they must create it themselves first.Coxon stated that some AI practitioners are much more pessimistic privately than they express publicly, and are even worried that AI could destroy humanity before the end of this decade. He personally judges that in the most radical scenario, AI could go out of control by the end of next year, so such decisions should not be made solely by the engineers of a few companies.

The Rollup founder Andy: The U.S. SEC may introduce a tokenized securities innovation exemption

The Rollup founder Andy posted that market rumors suggest the U.S. Securities and Exchange Commission (SEC) is preparing to launch the largest tokenization innovation exemption policy to date, which may allow tokenized securities to be traded solely through registered transfer agents, without the need for broker-dealer licenses, and without adhering to traditional trading platform or ATS-related rules. It is also reported that this could cover U.S. retail investors and overseas investors.Andy stated that if the above news is true, its potential impact would be significant. Tokenized funds could be issued and traded directly in the form of on-chain tokens, with transfer agents maintaining legal ownership records on-chain, while the underlying assets held by the fund, such as stocks and bonds, could also be further tokenized, thus forming an on-chain trading system of "fund tokens + underlying asset tokens."Andy later mentioned that a large fund has already received the SEC's "green light," but this has not yet been officially confirmed. He speculated that ARK, Fidelity, or BlackRock could be potential participants. If the policy is ultimately implemented, U.S. asset management firms may accelerate the issuance of native equity tokens to compete for around-the-clock liquidity and on-chain distribution channels, rather than waiting for third parties to mirror tokenize traditional securities. He further linked this potential policy change to the recent push by the Trump administration for regulatory openness in the crypto market, as well as the CFTC's efforts to bring perpetual contracts to the U.S. market, believing that the U.S. regulatory environment may be gradually opening the policy floodgates for on-chain finance.

Tom Lee: Asset tokenization and Agentic AI may trigger a new round of ETH price increase

According to PRNewswire, Tom Lee, Chairman of the Bitcoin treasury company Bitmine, stated that during historical cryptocurrency bull market cycles, the ETH/BTC ratio typically rises as Ethereum's usage increases compared to Bitcoin, such as during the NFT boom of 2020-2021 and the stablecoins of 2025, both of which have been significant catalysts for the growth of Ethereum applications. In the next cycle, Wall Street's tokenization of assets and deployment on the blockchain, along with the use of Agentic AI on the blockchain, may further drive the ETH/BTC ratio higher.Since the third quarter of 2026, ETH has been the best-performing macro asset, outperforming the S&P 500 index by 5430 basis points as of last Friday; the three best-performing asset classes since June 30 have been ETH, BTC, and SOL, with cryptocurrency assets showing significant outperformance compared to other macro assets so far in the third quarter, which is expected to further attract institutions to increase their allocation to cryptocurrency assets.Tom Lee added that as we enter the last few months of 2026, the crypto market faces several positive catalysts, including the anticipated vote on the CLARITY Act in mid-September, South Korean investors re-entering the crypto market and shifting from AI stocks to cryptocurrencies, and what he believes will be a bottoming out of the "four-year cycle" in the coming weeks. These factors may pave the way for a large influx of institutional funds in the last few months of 2026.

first_img OpenAI Chief Scientist says AI may continue to rise rapidly to recursive self-improvement

OpenAI Chief Scientist Jakub Pachocki published an article titled "An Alien Mind" on September 6, 2026. The article reviews the results of the RLSlow research project, which emerged in mid-2023, demonstrating the first scalable training of reasoning models. It states that three years later, reasoning language models have become part of rapid economic growth, beginning to push scientific boundaries, capable of operating computers and graphical interfaces, collaborating with humans and other AIs on research projects, while also changing the landscape of computer security and introducing new dangers.The author anticipates that the current pace of progress may continue towards recursive self-improvement based on internal results. If AI development continues along the current path, systems may experience equivalent or greater leaps in capability in the coming years, increasingly driving their own development. The author calls for extreme caution, believing that no one is prepared to deal with the consequences of the rapid rise of machine intelligence. OpenAI will continue to seek technical solutions for alignment and monitoring, build defensive systems, and unilaterally halt further scaling when necessary, but believes broader intervention is needed.The article states that machine intelligence is primarily driven by increased computational power, with AI growing more than being designed. In terms of alignment, it distinguishes between goal alignment and value alignment, with the core challenge being generalization. GPT-6 Astra shows significantly better alignment than GPT-5.6 Sol, but more progress is still needed. In monitoring, the focus is mainly on chain-of-thought monitoring, with assessments showing that reliance on capabilities is gradually weakening. In terms of scalable defense, models are becoming superhuman in breaking into computer systems, currently in a narrow window where using the best available models significantly enhances the security of critical systems.
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