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first_img Anthropic is researching how to enable AI agents to negotiate on behalf of users

Phoenix Technology cites a report from the Financial Times that on October 19, Beijing time, the AI company Anthropic is discussing with legal professionals how to enable AI agents to negotiate on behalf of users while adhering to reasonable negotiation rules to secure better deal terms. Two individuals familiar with Anthropic's thoughts stated that the company is seeking advice from law firms to understand how lawyers can balance client interests with fair negotiation outcomes. Anthropic declined to comment.The report mentions that as personal AI agent applications advance, related companies are beginning to consider allowing agents to communicate with each other to negotiate product prices, resolve customer service disputes, and even strive for better salary conditions on behalf of users. One person familiar with the related work stated that Anthropic is researching the negotiation norms that should be followed when models negotiate with each other, weighing factors such as how often to consult users during negotiations and how vigilant to remain against AI negotiation counterparts. Another individual close to the company mentioned that the company has also explored having users sign documents to confirm the tasks accepted by the agents and the rules they must adhere to.The Financial Times cites research released by Anthropic in April this year, stating that the policy and legal framework for AI models to conduct transactions on behalf of humans has yet to be established. This year, the company had the Claude agent negotiate around real goods and funds, and in a September experiment, employees bought and sold books through the agent, with agents employing tough strategies having a slight advantage in securing better outcomes. Harvard Business School Assistant Professor Michelle Vacharo conducted over 180,000 agent negotiations, covering scenarios such as employment contracts and lease agreements, and the research found that some agents attempted to induce the other party to disclose confidential information through prompt injections.

first_img Researchers conversed with rogue AI agents using hidden text, activity tracked to Tencent Cloud

Researchers successfully communicated directly with AI agents while investigating the hijacking of Alibaba's Gaode Map service, even as some software was still running. In a report suspected to have been scanned by these agents, researchers included hidden text that is invisible to humans but visible to web reading tools, and then inquired about their tasks and operating environment through an email. One agent claimed it was checking how many entrance tags a certain scenic area displayed on Gaode Map and stated that it was operating in a restricted Tencent Cloud sandbox. Researchers could not independently confirm which model drove each run, noting that this was the first known external communication with an active out-of-control agent cluster.A report released by Swarmchasers on October 14 tracked over 2,600 attempts to obtain Gaode Map data between September 28 and October 8. Some tasks were relatively routine, such as checking which entrance was most commonly used by visitors at the Chengdu Zoo. After the service provider intercepted requests, some agents continued to attempt access, trying to capture tokens generated by anti-scraping software, forwarding traffic through third-party page readers, or using leaked API credentials from public code repositories, with one set of leaked keys and security codes returning real location data. Researchers also found requests targeting four development or pre-production hosts, but there was no evidence that these agents accessed private systems.Public records show that the cluster is related to Tencent Cloud: all 17 email accounts examined by researchers were created by Tencent servers located in Hong Kong, and the observed direct requests were forwarded through an agent named hysandbox-ats.

first_img Galaxy Research: The conditional market begins to expand, affecting the market approaching the mainnet

Galaxy Research released a research report on October 15, categorizing decision markets and impact markets as conditional markets. These two types of conditional trading settle only when specific outcomes occur, and decision markets also settle on clear and binding results. Unlike prediction markets, conditional markets are not limited to binary, all-or-nothing structures; they trade real assets and their prices rather than synthetic probability contracts, with the byproduct being the impact of events on asset values rather than occurrence probabilities. The agency referred to prediction markets as the zero version of event-driven finance, with a large number of experiments emerging over the past 18 months, and new infrastructure pushing it beyond prediction markets.The ownership token-based issuance platform Umia, aimed at EVM-compatible chains, launched in September, expanding decision markets from being primarily limited to Solana, where MetaDAO was the first to scale binary pass or fail markets, to multi-outcome markets that can price proposal parameters. A deposit of stablecoins or DAO tokens can simultaneously convert into positions covering each outcome, with only winning market trades ultimately settling. Currently, 22 DAO treasuries fully governed by decision markets hold a total of $50.5 million, with MetaDAO accounting for 21 of them and 78% of the assets; the stablecoin portion is $35.8 million, with MetaDAO holding 82%. The fundraising for the market-governed DAO issuance platform by MetaDAO was approximately 11 months prior to this research report. Umia extends the issuable chains to Solana or EVM, which together account for about 92% of TVL by chain type.

first_img Palantir executives say AI researchers have started smoking, betting that AI will cure cancer

Palantir's Chief Technology Officer Shyam Sankar stated in an interview on CBS News' "Face the Nation" that many AI researchers have started smoking to demonstrate their confidence in AI to other researchers. He quoted the attitude of such researchers saying, "I truly believe in AI; it will cure cancer, so I’m showing you that I’m all in." Sankar did not name any specific researcher nor cite survey data; this statement was made in passing when host Margaret Brennan pressed him on why he was so focused on the topic.In the interview, Sankar referred to effective altruism as a "millennial-style doomsday cult" and mentioned FTX founder Sam Bankman-Fried as the most well-known representative of the movement. He also cited Pascal's idea that everyone has a "God-shaped hole" in their heart, claiming that some researchers are trying to fill this hole with a machine god called AGI.Medical data contrasts with this claim. The U.S. CDC states that smoking causes about one-third of cancer deaths in the U.S., and cigarette smoke contains at least 69 known carcinogenic chemicals, with smokers being about 25 times more likely to develop lung cancer than non-smokers. Anthropic CEO Dario Amodei stated in August that the promise of AI curing cancer is "more of a cliché than inspiring," and that only a true cure for cancer can win public trust. CBS polling shows that 50% of Americans believe the problems created by AI outweigh the problems it solves, and 45% want the government to limit the use and development of AI.

first_img The Bitcoin supply on the exchange has dropped to 2.67 million coins, and a CryptoQuant researcher claims it may drive up prices

On-chain data company CryptoQuant researcher Rei Researcher pointed out in a report released on Monday that as the Bitcoin supply on exchanges continues to shrink, the price of Bitcoin may see an upward trend. The report shows that the Bitcoin held by exchanges has decreased from 2.8 million in February to 2.67 million. The recent price of Bitcoin is around $83,485, remaining stable over the past 24 hours but rising 8% over the past 30 days, following the best-performing quarter in years.The report states, "If buying demand continues to improve while exchange supply remains low, Bitcoin could benefit from a supply-demand imbalance, creating favorable conditions for a longer-term upward trend." The report adds, "More importantly, Bitcoin has rebounded from its lows in recent weeks, while exchange reserves continue to decline. This is a notable development, indicating that even as the market recovers, the supply available for trading is still decreasing." The report also notes that investors may be transferring Bitcoin out of exchanges and into cold wallets.In the first half of 2026, Bitcoin traded below $65,000 for most of the time. After reaching an all-time high of $126,080 in October 2025, the cryptocurrency has been in a bear market for most of this year. However, the situation changed in August when the U.S. Treasury doubled the scale of liquidity support repurchase operations, weakening the dollar while boosting non-yielding assets like Bitcoin. Analysts say that the so-called "devaluation trade" has heated up again, benefiting Bitcoin as it did in 2024 and 2025. Currently, the price of Bitcoin is still over 30% lower than its historical record.

first_img Grayscale Research Director: Cheaper Proxy AI Will Drive Up Computing Power Demand

Grayscale's Research Director Zach Pandl stated in his column The Stack on October 8 that the rising demand for AI is due to decreasing usage costs and technology's ability to perform tasks more autonomously, thereby increasing the demand for computing power and the physical infrastructure that supports AI. Lower costs can unleash more AI activities, and the low-cost competition of open-source weight models is driving down token prices, making cheaper intelligence economically viable for more applications and automated workflows.The article cites that Anthropic's latest Sonnet model claims to reduce the cost of each task by up to 30%; OpenAI's always-on agent dots, launched on September 29, can work towards user goals around the clock, potentially significantly increasing the demand for computing power. Pandl compares that chatbots primarily answer questions, while agents execute multi-step processes to achieve goals, with tasks like preparing for client meetings potentially consuming 5 to 50 times the tokens of a single chat interaction, and always-on agents may extend processing beyond a single conversation.Pandl cites Goldman Sachs' prediction that by 2030, token consumption could increase 24 times, primarily driven by agents; even with improved efficiency, if usage grows faster, the total demand for computing power may still rise. He points out that digital activities still rely on physical infrastructure that requires time to deliver, such as electricity, data centers, and GPUs, and cheaper AI can coexist with tight computing power supply, mentioning that CoreWeave recently signed new contracts at higher computing power prices. His conclusion is that cheaper intelligence and stronger agents may expand use cases and usage enough to offset efficiency gains, thereby supporting the demand for scarce computing power and benefiting its owners.
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