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betting

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first_img The Pentagon prohibits the U.S. military from betting on prediction markets using military information

U.S. Secretary of Defense Lloyd Austin has prohibited all Pentagon personnel from using non-public information to place bets on upcoming military operations, involving prediction market platforms such as Kalshi and Polymarket. In a memo sent to senior Pentagon officials and defense agencies on Tuesday, he stated that all Department of Defense personnel are prohibited from using non-public information for financial transactions, with the relevant restrictions covering both classified and unclassified information.Austin wrote in the memo that adversaries will observe movements in these markets, and the safety of U.S. military personnel often depends on the enemy not knowing what is about to happen. He also pointed out that, aside from operational security, financial betting can distort judgment: a logistics personnel betting on the date of an operation will be concerned about that date, and an analyst holding a position on the outcome will also be concerned about that outcome.Before this directive was issued, U.S. Army soldier Gannon Ken Van Dyke was charged in April for allegedly profiting over $400,000 on Polymarket by using classified information regarding the operation to capture Venezuelan leader Nicolás Maduro. Prosecutors claimed he participated in the planning and execution of the operation and used advance knowledge to bet on the outcome of Maduro's ousting; he pleaded not guilty to all charges. In February, Israeli authorities also arrested and charged a military reservist and a civilian for allegedly using classified information to bet on events related to Israeli strikes against Iran on Polymarket.

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 CFTC investigates Adam Kinzinger betting on his own pardon at Kalshi

According to Politico, citing three informed sources, the U.S. Commodity Futures Trading Commission (CFTC) is investigating former Illinois Republican Congressman Adam Kinzinger, related to his trading on the prediction market platform Kalshi. The relevant trades occurred between December 2024 and January 2025, completed through a Kalshi account associated with Kinzinger. He confirmed to the media that he had placed bets on contracts regarding whether he would receive a presidential pardon, while also betting on another contract about whether Biden would issue preemptive pardons before leaving office.In the final moments before Biden left office in January 2025, he issued preemptive pardons to Kinzinger and other members of the House Select Committee investigating the Capitol riot. Screenshots provided by Kinzinger show that he made a profit of $823 from approximately 25 trades, most of which were losses. He denied any wrongdoing, stating that he had been out of office for two years at the time of the bets, was neither a congressman nor a candidate, and had "no insider information." He also stated that he had read Kalshi's rules in advance and understood that they prohibit users from trading contracts directly related to their own interests. Kalshi prohibits users from betting on contracts in which they are direct participants, and the CFTC also prohibits the use of significant non-public information in its regulated markets.Kalshi had previously handled similar cases, suspending three congressional candidates in April for betting on their own campaigns, and freezing former Congressman George Santos's account, which was referred to the CFTC and the Department of Justice, leading to a lifetime ban at the end of August.

Tether released a dataset of 191.4 billion Token STEM, betting on the "explanatory ability" of local small models

The stablecoin giant Tether's Tether AI Research today released QVAC Genesis III, a synthetic training dataset aimed at the fields of science, technology, engineering, and mathematics, with a scale of 19.143 billion tokens, covering 159.6 million documents.It is reported that Tether hopes to enhance the reasoning and teaching capabilities of small AI models, allowing more AI assistants to run directly on laptops, mobile phones, and local servers, reducing the ongoing reliance on large cloud models.Genesis III continues the data lineage of Genesis I and Genesis II, covering 19 curriculum-related fields including biology, chemistry, physics, mathematics, computer science, medicine, electrical engineering, and machine learning, aimed at high school, university, and professional applications. Tether states that the dataset will focus on training models to explain problem-solving paths, identify erroneous reasoning, and provide corrections, rather than just outputting final answers.According to Tether's disclosed test results, a 1.7 billion parameter model trained with Genesis III option-level data achieved an effective answer rate of 99.45% in relevant benchmark tests. Compared to the Cosmopedia-v2 training model of similar token scale, Genesis III improved scores on the ARC-Easy, ARC-Challenge, and MMLU STEM benchmarks by 28.57, 21.35, and 15.03 percentage points, respectively.
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