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Anthropic CEO published a lengthy response to safety concerns, stating that it is necessary to stay at the forefront of technology

Anthropic recently submitted a draft AI safety bill to U.S. lawmakers, which has been questioned by U.S. AI safety advocates. The draft sets a high threshold for the government to urgently halt dangerous models, requiring that risks involve scenarios such as biological weapons, cyberattacks, or AI going out of control, and potentially causing more than 50 deaths or serious injuries, or losses exceeding $1 billion; some provisions may also limit state government regulatory authority.Nathan Calvin, the strategic head of the AI safety organization Encode, subsequently compiled Anthropic's decisions over the past year. In February of this year, the company modified its previously strict safety policy: it had previously committed to pausing training or releases if safety measures did not keep pace with model capabilities, but the new policy no longer requires the company to independently halt R&D at higher risk stages, citing that competitors might take advantage of the opportunity. During the same period, the company invested heavily in computing power, formed a chip team, and allowed Claude to take on more AI R&D tasks.On October 21, Anthropic CEO Dario Amodei posted a lengthy rebuttal on X. He acknowledged that the company had made some mistakes but insisted that competing for cutting-edge AI capabilities did not violate its safety mission, stating that the company adheres to a race-to-the-top approach, believing that only by staying at the forefront of technology can it drive the industry to raise safety standards. He listed nine safety decisions that had cost the company commercially, including restricting the Mythos-level model's open access for months and strictly limiting biology-related requests. The safety roadmap updated by the company on October 19 states that existing policies mainly target the deployment of dangerous models, and in the future, it may be necessary to directly limit the speed of R&D, with plans to propose relevant policy options by January 15, 2027, or explain why none were proposed.

first_img Kerman Kohli: The bottleneck of computing power financing lies in credit

Cryptocurrency researcher Kerman Kohli published "Compute Financing" on Substack on October 19, 2026, discussing financing for computing power construction. He believes one of the main bottlenecks is capital, especially credit: early expenditures mainly come from balance sheet cash, followed by a shift to equity financing. The article cites Alphabet's $85 billion financing and Meta's fundraising through shareholder dilution, with the next step being the credit market.Kohli summarizes the current beliefs of creditors into three points, which he believes are incompatible: AI may be a bubble; the biggest risk is counterparty risk in purchase contracts; the underlying GPUs are not valuable and depreciate like ordinary hardware. He argues that demand is closer to infinite, stating that the demand for agentic AI is growing by about 2.5 to 5 times each year, with supply potentially doubling by the end of 2030. Memory is expected to sell out by 2027, with computing power commitments reaching trillions of dollars, and he mentions Jane Street's multi-billion dollar commitments, as well as the needs of pharmaceutical companies, research, military, and cybersecurity.Regarding efficiency, he states that when the cost of intelligence drops by 90%, the increase in usage is even greater, with a baseline exceeding 10 times, and he cites Jevons' Paradox.On the topic of purchasing, Kohli believes that computing power is more substitutable than real estate; when demand is strong, if someone withdraws their commitment, others will take over. He mentions that many creditors require 2 to 3 year contracts and down payments of 20% to 30%, sometimes as high as 50%, and locking in long-term discount contracts effectively shorts computing power for lenders. The article also states that computing power rental prices have risen by about 50% in the past 6 months and about 100% in the past year, with B300 supplies being tight. Regarding collateral, he notes that the A100 from 2020 is still operational and rented out until 2029, leading him to believe it has at least about 9 years of use value; the current price of B200 is about 50% higher than when it was released about two years ago, and a 6-year-old A100 is still worth about 25% of its value. He concludes that computing power will surpass real estate to become the largest asset class, and the scale of credit-supported computing power is currently just beginning.

Gate Founder and CEO Dr. Han: Gate Money connects assets, funds, and payments, reshaping the new landscape of digital finance

During a live AMA interview hosted by CoinMarketCap, Gate founder and CEO Dr. Han discussed the development direction of digital finance, the product positioning of Gate Money, and the accelerated integration of digital assets with traditional finance.Dr. Han stated, "The future of digital finance lies not only in providing more asset choices but also in connecting assets, funds, and payments, allowing users to manage assets, transfer funds, and meet daily payment needs more conveniently within one ecosystem." Upholding the core concept of "One Gate, Everything Money," Gate Money integrates services such as digital assets, fiat currency, stocks, ETFs, gold, bank accounts, payments, and asset management into a single account, covering scenarios like asset holding, receiving payments, transferring, exchanging, paying, and earning. Users in eligible regions can also open an e-banking account with the same name and use the Gate Card for online and offline consumption with fiat or digital assets, further bridging asset allocation and daily payment scenarios.Regarding the accelerated integration of digital assets and traditional finance, Dr. Han also explored the roles of stablecoins and asset tokenization in cross-border capital flow, on-chain settlement, and financial service innovation. As user demands extend from single transactions to investment management, fund transfers, and daily consumption scenarios, Gate will continue to expand the asset categories, payment methods, and service capabilities of Gate Money, enriching the application of digital assets in diverse financial scenarios and providing users with a more integrated financial service experience.

Tencent's internal testing personal investment analysis assistant "Rena Lancaic", supports connecting to WeChat

According to "Du Jia," Tencent is conducting a small-scale test of its personal investment analysis assistant "Rena Lan Cai," which has a PC version and a WeChat mini-program, supporting connection to WeChat. This product is positioned as an AI assistant for individual investors, helping users obtain and understand market and company information, and is currently in a small-scale testing phase.The web version breaks down the investment research workflow into visual modules, with core features including market quick reads, individual stock tracking, and AI Q&A. The market quick read summarizes global market dynamics, continuously updated in the morning, noon, closing, and evening, and associates market information with the user's watchlist; the left sidebar allows users to customize stocks of interest and displays real-time market data, while the right side features an intelligent Q&A panel linked to the day's quick read content, supporting follow-up questions about industry rankings, cash flow in financial reports, and more. In addition to the PC version, Rena Lan Cai is also launched as a WeChat mini-program, with basic functionality aligned across both platforms and conversation records shared. The product also appears in the WeChat chat list as a WeChat ClawBot intelligent entity, allowing users to directly access investment research capabilities in the chat window.The report states that Alibaba is also internally testing its AI investment research product Qovest, and Baidu's previously released Kuku AI is also focusing on investment research, as major companies collectively enter the personal investor AI investment research space. Rena Lan Cai essentially serves as an investment research assistance tool, not providing investment advice and avoiding direct trading compliance red lines.
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