Small modular reactors and microreactors could power AI data centers and factories, but outdated rules and public fears are stalling America's nuclear energy future.

The app reads your email inbox and your meeting calendar, then gives you a short audio summary. It can help you spend less time scrolling, but of course, there are privacy drawbacks to consider.

Firewire makes the most innovative surfboards in the industry. This winter, I tried the Neutrino, Machado, and Revo Max to see if they're worth the hype. For decades, the process of making a surfboard has more or less been the same: Cut a piece of foam. Put a wooden stringer down the middle to provide structure and strength. Shape it, then wrap it in fiberglass, sand it, and leave holes for the leash and fins. That was until Firewire Surfboards came along.

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Researchers spent five years developing an AI-based model to protect freshwater fish worldwide from extinction, with a particular focus on identifying threats to fish before they become endangered. "People sometimes go in to protect species when it's already too late," said Ivan Arismendi, an associate professor in Oregon State University's Department of Fisheries, Wildlife, and Conservation Sciences. "With our model, decision makers can deploy resources in advance before a species becomes imperiled." The findings were recently published in the journal Nature Communications. Nearly one-third of freshwater fish species face possible extinction, threatening food supplies, ecosystems and outdoor recreation.

The app reads your email inbox and your meeting calendar, then gives you a short audio summary. It can help you spend less time scrolling, but of course, there are privacy drawbacks to consider.

The White House unveiled its first federal AI policy framework Friday, with officials Michael Kratsios and David Sacks urging Congress to pass a national standard this year.

The app reads your email inbox and your meeting calendar, then gives you a short audio summary. It can help you spend less time scrolling, but of course, there are privacy drawbacks to consider.

Three people associated with artificial intelligence server maker Super Micro Computer, including its cofounder, have been charged with helping smuggle at least $2.5bn-worth of United States AI technology to China in violation of export laws, according to the US Department of Justice. US prosecutors did not name Super Micro in the complaint, referring only to a "US manufacturer", but San Jose, California-based Super Micro said it was informed by federal prosecutors of the indictment on Thursday. The Justice Department said it had charged Yih-Shyan Liaw, Ruei-Tsang Chang, and Ting-Wei Sun in an indictment unsealed in federal court in Manhattan on Thursday, on allegations of a complex scheme to send US-made servers through Taiwan to other countries in Southeast Asia, where they were swapped into unmarked boxes and sent on to China. The US has had export restrictions on China for advanced AI chips since 2022. In a release, FBI Assistant Director in Charge James Barnacle said the defendants used fabricated documents, staged bogus equipment to pass audit inventories, and used a pass-through company to conceal their misconduct and true clientele list.

Obtaining the human-like perception ability of abstracting visual concepts from concrete pixels has always been a fundamental and important target in machine learning research fields such as disentangled representation learning and scene decomposition. Towards this goal, we propose an unsupervised transformer-based Visual Concepts Tokenization framework, dubbed VCT, to perceive an image into a set of disentangled visual concept tokens, with each concept token responding to one type of independent visual concept. Particularly, to obtain these concept tokens, we only use cross-attention to extract visual information from the image tokens layer by layer without self-attention between concept tokens, preventing information leakage across concept tokens. We further propose a Concept Disentangling Loss to facilitate that different concept tokens represent independent visual concepts. The cross-attention and disentangling loss play the role of induction and mutual exclusion for the concept tokens, respectively. Extensive experiments on several popular datasets verify the effectiveness of VCT on the tasks of disentangled representation learning and scene decomposition. VCT achieves the state of the art results by a large margin.