China's AI promise lures top Asia fund away from Korea and Taiwan The AI frenzy that's gripped global equity markets for months is getting a fresh look from investors, as focus shifts to finding stocks that can drive the next leg of the sector's rally or at least withstand future selloffs. A top-performing Asian money manager is boosting exposure to artificial-intelligence stocks in China while retreating from those in South Korea and Taiwan, citing relatively better valuations and outlook. "Some of the names are still quite cheap in terms of valuation," said Kelly Chung, who helps oversee the Value Partners Asian Income Fund as well as the Asian Innovation Opportunities Fund. "The capital expenditure in China to invest in AI is still very low. There is still a big room for them to actually go up in terms of AI infrastructure investment" when compared to the U.S., she said in an interview.

Note that since the function classes become more restrictive as we go down the table, the noted lower bounds are also valid for upper rows, and the upper bounds are also valid for lower rows.

Pillay is an editorial fellow at TIME. Pillay is an editorial fellow at TIME. On Wednesday, leaders in business, art, fashion, and technology gathered on the 102nd floor of New York's One World Trade Center for a TIME100 Impact Dinner. The event orbited around a panel, moderated by TIME's editor-in-chief Sam Jacobs, that discussed how AI could shape the future of fashion--particularly from a customer's perspective. The panelists were David Lauren, chief branding and innovation officer for Ralph Lauren, which sponsored the event; Shelley Bransten, corporate vice president, worldwide industry solutions, at Microsoft, which also sponsored the event; and artist and researcher Sougwen Chung, who founded Scilicet, a studio exploring human and non-human collaboration.

Using diffusion priors to solve inverse problems in imaging have significantly matured over the years. In this chapter, we review the various different approaches that were proposed over the years. We categorize the approaches into the more classic explicit approximation approaches and others, which include variational inference, sequential monte carlo, and decoupled data consistency. We cover the extension to more challenging situations, including blind cases, high-dimensional data, and problems under data scarcity and distribution mismatch. More recent approaches that aim to leverage multimodal information through texts are covered. Through this chapter, we aim to (i) distill the common mathematical threads that connect these algorithms, (ii) systematically contrast their assumptions and performance trade-offs across representative inverse problems, and (iii) spotlight the open theoretical and practical challenges by clarifying the landscape of diffusion model based inverse problem solvers.

OpenAI researcher Jason Wei is joining Meta's new superintelligence lab, according to multiple sources familiar with the matter. Wei worked on OpenAI's o3 and deep research models, according to his personal website. He joined OpenAI in 2023 after a stint at Google, where he worked on chain-of-thought research, which involves training an AI model to process complex queries step-by-step. At OpenAI, Wei became a self-described "diehard" for reinforcement learning, a method of training or refining an AI model with positive or negative feedback. It's become a promising area of AI research--one that several of the researchers Meta has hired for its superintelligence team specialize in.

An ancient-DNA revolution is turning the high-speed equipment used to study the DNA of living things on to specimens from the past. The technology is being used to create genetic maps of saber-toothed cats, cave bears, and thousands of ancient humans, including Vikings, Polynesian navigators, and numerous Neanderthals. The total number of ancient humans studied is more than 10,000 and rising fast. The old genes have already revealed remarkable stories of human migrations around the globe. But researchers are hoping ancient DNA will be more than a telescope on the past--they hope it will have concrete practical use in the present. Many artists worry about the encroachment of artificial intelligence on artistic creation.

"[Chung] comes from drawing, and then they start to work with AI, but not like we've seen in this generative AI movement where it's all about generating images on screen," says Sofian Audry, an artist and scholar at the University of Quebec in Montreal, who studies the relationships that artists establish with machines in their work. "[Chung is] really into this idea of performance. So they're turning their drawing approach into a performative approach where things happen live." Audiences watch as Chung works alongside or surrounded by robots, human and machine drawing simultaneously. The artwork, Chung says, emerges not just in the finished piece but in all the messy in-betweens.