AI leaders worry antitrust law could stand in the way of what they view as an increasingly urgent push to coordinate a slowdown in AI development. OpenAI has asked members of Congress in recent weeks for clear guidance about whether orchestrating an industry-wide slowdown on frontier AI development would be legal, people close to the company tell WIRED. Substantive coordination on safety between AI labs may risk running afoul of antitrust law, the people say, which poses a significant obstacle to bringing major tech giants on board with the effort. Last weekend, OpenAI's chief scientist, Jakub Pachocki, published a blog post arguing that the best path forward for the AI research world includes "coordinating to slow down future development," which he thinks will be key to ensuring that self-improving AI systems are safe. In the short term, he expects " voluntary slowdowns to become commonplace until shared safety bars are established."

US judge rejects bid to break up Google's ad business Share US judge rejects bid to break up Google's ad business on social media Alphabet's Google has escaped a breakup of its advertising technology business, marking the third time in recent years that United States antitrust enforcers have tried to force a Big Tech breakup and lost. US Judge Leonie Brinkema in Alexandria, Virginia, on Wednesday declined to make Google sell AdX, where publishers pay Google a 20 percent fee to sell ads in auctions that happen instantly when users load websites. The judge accepted behavioural remedies. The reasoning behind today's decision was not immediately made public. Brinkema filed her opinion under seal for 14 days, leaving the details of how Google must change its ad business unknown for now.

Taiwanese authorities have indicted nine people, including employees of Nvidia and Super Micro Computer, over their alleged involvement in the illegal export of artificial intelligence servers to China. Eight of those indicted, including one employee of Nvidia's Taiwan unit and two employees of Supermicro's Taiwan unit, were charged with breach of trust and document forgery in connection with the illegal export of high-end AI servers, prosecutors in the port city of Keelung said in a statement on Monday. An additional 56 servers were seized at Taiwan's border, the statement said. Three of the defendants have been charged with embezzlement. Semiconductor powerhouse Taiwan is the world's largest producer of advanced chips used in AI applications.

Mashable's Best: E-readers, robovacs, laptops, earbuds, smart home and more Look Up Say More Mashable Selects Mashable Voices Safety Net Creator Hub Versus Gift Ideas For Everyone On Your List Switch Off Trending Now In My Bag All Series Deliberately destroying rare books might be the final straw in the eyes of the Federal Trade Commission. Earlier this month, we reported on the disturbing trend of AI companies using physical copies of books to train their agentic AI, in a practice so eerily reminiscent of book burning that it's spooking even devotees of artificial intelligence . Well, according to Axios, the FTC is now being urged to investigate the practice, not, as we might like, for crimes against humanity, but for violations of antitrust law, since every book destroyed is one less book available for competing AI agents to use. SEE ALSO: AI companies keep destroying old books. Axios reports that [m]ore than a dozen civil society groups, including Demand Progress Education Fund, the Consumer Federation of America, and the Institute for Local Self-Reliance, are urging the FTC to investigate these practices, particularly those involving rare books.

The European Commission claims that Google boosted its own apps and products to the top of search rankings to the detriment of its competitors. The European Commission has levied a $1 billion penalty against Google over alleged competition law violations. An EC investigation found that Google had abused its dominance in the European Union's search and app store markets to funnel people toward its own apps and services, in violation of the EU's Digital Markets Act . The body has ordered Google to refrain from giving preferential treatment to its own services--such as shopping, accommodations, transport, and flights--in search rankings. Google must also allow app developers to communicate and transact with users outside the Play Store, where it takes a commission on sales .

The European Union has fined Google 890 million euros ($1bn), saying the technology giant broke digital antitrust rules by steering users of Google Play and its search engine towards its own services and apps at the expense of rivals. Thursday's penalty is the latest in Brussels' crackdown on Big Tech, which has seen the bloc lead the world in reining in the largest firms from Silicon Valley to Beijing. The European Commission, the bloc's executive branch, said it was acting in the interest of consumers. "The best products should succeed because they're better, not because they're owned by the company running the search engine. And European consumers have a right to be told by app developers where to sign up to the best offers, even when the app store owner does not get a cut," said Teresa Ribera, the commission's executive vice president for clean, just and competitive transition.

Things to Do in L.A. Tap to enable a layout that focuses on the article. This is read by an automated voice. Please report any issues or inconsistencies here . See more from the L.A. Times in Google Search. A new federal lawsuit by California drivers accuses major gas chains, including Walmart and 7-Eleven, and technology company Kalibrate of using AI software to collude and keep pump prices artificially high.

Firms' algorithm development practices are often homogeneous. Whether firms train algorithms on similar data or rely on similar pre-trained models, the result is correlated predictions. In the context of personalized pricing, correlated algorithms can be viewed as a means to collude among competing firms, but whether or not this conduct is legal depends on the mechanisms of achieving collusion. We investigate the precise mechanisms through a formal game-theoretic model. Indeed, we find that (1) higher correlation diminishes consumer welfare and (2) as consumers become more price sensitive, firms are increasingly incentivized to compromise on the accuracy of their predictions in exchange for coordination. We demonstrate our theoretical results in a stylized empirical study where two firms compete using personalized pricing algorithms. Our results demonstrate a new mechanism for achieving collusion through correlation, which allows us to analyze its legal implications. Correlation through algorithms is a new frontier of anti-competitive behavior that is largely unconsidered by US antitrust law.

While Large Language Models (LLMs) show great promise, their tendencies to hallucinate pose significant risks in high-stakes domains like finance, especially when used for regulatory reporting and decision-making. Existing hallucination detection benchmarks fail to capture the complexities of financial benchmarks, which require high numerical precision, nuanced understanding of the language of finance, and ability to handle long-context documents. To address this, we introduce PHANTOM, a novel benchmark dataset for evaluating hallucination detection in long-context financial QA. Our approach first generates a seed dataset of high-quality "query-answer-document (chunk)" triplets, with either hallucinated or correct answers - that are validated by human annotators and subsequently expanded to capture various context lengths and information placements. We demonstrate how PHANTOM allows fair comparison of hallucination detection models and provides insights into LLM performance, offering a valuable resource for improving hallucination detection in financial applications. Further, our benchmarking results highlight the severe challenges out-of-the-box models face in detecting real-world hallucinations on long context data, and establish some promising directions towards alleviating these challenges, by fine-tuning open-source LLMs using PHANTOM.1

'Creepy' Listening Tool for Targeted Ads Didn't Actually Work, FTC Says Three firms will pay nearly $1 million for selling "Active Listening" technology that they claimed tapped people's phones for advertising. The FTC alleges the "tech" was just pricey email lists. The Federal Trade Commission announced on Thursday that Cox Media Group and two other marketing companies, MindSift LLC and 1010 Digital Works, have agreed to collectively pay nearly $1 million to settle allegations that they deceived their customers--other businesses--by claiming that they could help target ads based on audio recordings collected from consumers' smart devices via a marketing service called Active Listening. In a statement to WIRED, a spokesperson for CMG says, "We are pleased to have this matter resolved. Our local marketing team relied on marketing materials provided to us by a third-party vendor about their product. We withdrew the materials expeditiously and stopped further use of the product."