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Tencent released Buddy One, connecting multiple office applications and points

Tencent officially launched Buddy One, integrating WorkBuddy, Tencent Docs, Tencent Meeting, Tencent Cloud Drive, and ima into a unified AI office system. After linking accounts, users can directly let WorkBuddy search for information and consolidate data across applications without needing to repeatedly authorize or copy and paste. For example, it can generate new plans by combining meeting minutes from Tencent Meeting, old proposals from Tencent Docs, and the ima knowledge base, along with sources of information.The points system has been unified, and WorkBuddy points can be used interchangeably in Tencent Docs, ima, and Tencent Cloud Drive. Points purchased separately in each application will not be merged. The Buddy One VIP official website currently lists a price of 700 yuan/month, which includes 50,000 universal points per month, 1TB of shared space across products, as well as benefits such as the flagship version of WorkBuddy, the professional version of Tencent Meeting, and the super member Plus of Tencent Docs.At the same time, Tencent Cloud Drive is responsible for providing unified storage. Currently, it mainly implements account linking, cross-application retrieval, and point sharing, while cross-application memory sharing has not yet been launched. WorkBuddy PC version must be upgraded to 5.9.0 or above to use it; account linking is free, but unbinding is not currently supported.

The Gate event market has a cumulative trading volume of approximately 909 million USD, ranking second among the channels connected to Polymarket

According to the latest data from Polymarket Builders, the Gate event market has a cumulative trading volume of approximately $909 million, ranking second among all access channels on Polymarket and consistently remaining at the forefront of major trading entrances.The Gate event market has launched a quarterly earnings prediction challenge, setting a total reward of 90,000 USDT around the earnings events of popular companies such as Microsoft, Apple, and Amazon. Activities include new trader transactions, inviting friends, and profit rankings, with the top of the leaderboard eligible for a reward of up to 5,000 USDT.Gate is the first to layout the event market, creating a one-stop trading experience for global hot events. Users can participate in trading directly through the Gate App, placing orders using USDT from their spot accounts without the need for on-chain operations. The platform has launched the Combo prediction feature and introduced a macro market topic page related to the U.S. midterm elections, focusing on displaying market probabilities and trading data for key macro topics such as Federal Reserve interest rate decisions, inflation, employment, and economic growth. At the same time, it continues to improve features such as intelligent monitoring, AI analysis, profit and loss analysis, and quick trading, enriching the trading scenarios and information service capabilities of the event market.

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.
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