US prosecutors just charged a man with smuggling NVIDIA chips to China, and government officials are saying the company isn't doing all it could to stop the illegal activities, Bloomberg reported. Earlier this year, officials released a surveillance video showing someone using a red hair dryer to peel serial number stickers off NVIDIA server boxes in an effort to sneak AI chips to China. And yesterday, federal authorities arrested a man named Greg Lui for smuggling servers containing 300 million worth of AI chips to China, in violation of US export laws. Those efforts reportedly show how an expanded network of criminals is attempting to reroute NVIDIA's AI chips to China, profiting from Washington's export controls that make the contraband silicon valuable. NVIDIA says it has abided by the rules and the company has never been accused of abetting smuggling.

Nvidia boss rejects AI extinction fears as'doomsday narratives' Nvidia CEO Jensen Huang has described warnings that AI could lead to humanity's extinction by the next decade as doomsday narratives. There is 0% chance that's going to be the end of the world, Huang said in an interview with CBS News, the BBC's US partner. Huang added: Scaring people is unnecessary. Warnings from researchers in recent weeks about potential risks posed by the technology escalated the debate about AI safety, with some industry executives calling for a slowdown in developing models. His remarks follow claims posted on social media by former Anthropic researcher Jacob Coxon that AI developers believe the technology could kill us all by the end of the decade.

Who gets to decide how quickly AI moves? Share Who gets to decide how quickly AI moves? on social media Artificial intelligence (AI) has stirred up more controversy than most things in the past five years. Ever since the introduction of accessible generative AI in 2022, institutions, universities, students, scholars, activists, cognitive specialists, public policymakers and members of the public have all been divided over the ethics of its use. As of the beginning of this month, even the founders of AI companies have taken the same stance. Dario Amodei, chief executive of Anthropic, released an essay calling on AI companies to slow the development of their most advanced models, as the safeguards currently in place are unable to keep up.

Happening now: Join staff writer Ian Bogost for a live Q&A about his latest stories; his course, Ordinary Extraordinary; and more. Click on Discussions to enter! For AI doomers, signs and portents are everywhere. When OpenAI introduced ChatGPT, almost four years ago, it couldn't do basic arithmetic. Now the company has unreleased models that are more fluent in higher mathematics--the language of the universe--than all but the most highly trained mathematicians.

Anthropic's CEO calls for AI slowdown as Nvidia's urges acceleration Anthropic's CEO took to the stage at a conference in San Francisco on Tuesday to reiterate his call for a slowdown of AI development. Following shortly after, Nvidia's CEO argued against such deceleration. Dario Amodei used an automotive analogy to make his point: when a competing car company has a safety incident like brake failures, it is a moment for all car companies to stop and review their own practices, he said at Salesforce's Dreamforce convention on Tuesday. "It's very tempting to attack your competitor and say these guys are unsafe," he said. "But I think the more responsible way to respond to it is to say, let's look at our own record. We may not have had this big, high-profile incident, but I'm sure we're not perfect."

Look Up Trending Now Good Connection: Uplifting stories for a digital age Creator Playbook Say More Mashable's Best: E-readers, robovacs, laptops, earbuds, smart home and more Switch Off Mashable Voices Mashable Selects Safety Net Versus Gift Ideas For Everyone On Your List All Series Nvidia's Hugging Face purchase confirmed at $13 billion The open source platform that was recently hacked by rogue OpenAI agents is now owned by the AI industry leader. The open source AI platform Hugging Face has been acquired by Nvidia. It's official: Nvidia has acquired the open-source AI platform Hugging Face for $13 billion. Or, according to Nvidia CEO Jensen Huang, the acquisition was for $12,930,300,000, to be exact. In a post on Nvidia's website on Thursday, Huang confirmed that the chipmaker turned AI industry giant has officially purchased Hugging Face after reports said an acquisition was in the making last week.

The unexpected interruption came hours before the president wrote a congratulatory post on Truth Social about the company's most recent earnings report. US President Donald Trump listens as Nvidia CEO Jensen Huang speaks at the White House during an event on "Investing in America" on April 30, 2025 in Washington, DC. President Donald Trump interrupted Nvidia's all-hands staff meeting on Thursday morning when he called CEO Jensen Huang midway through, three sources who witnessed the interaction tell WIRED. Nvidia's all-hands meetings typically involve Huang presenting or answering questions, on stage, to in-person staff at the company's Santa Clara, California, headquarters, while thousands of remote employees tune in to a virtual livestream. During the meeting on Thursday, Huang received a call on his mobile phone, which he stepped aside to take.

Say More Look Up Switch Off Mashable's Best: E-readers, robovacs, laptops, earbuds, smart home and more Creator Playbook Mashable Voices Trending Now Mashable Selects Safety Net Versus Gift Ideas For Everyone On Your List In My Bag All Series Nvidia CEO Jensen Huang says AGI is already here -- and the milestone is'senseless' Nvidia's focus is now on'productive work' and'profitable tokens.' Nvidia CEO Jensen Huang says the company has already achieved AGI but it doesn't matter. Some AI industry leaders, such as OpenAI CEO Sam Altman, are obsessed with artificial general intelligence, or AGI. While the term has no universally agreed-upon definition, it generally refers to AI that can match or even surpass human cognitive abilities across a large range of tasks. In a recent interview, Altman shared that OpenAI believes it will achieve AGI by the end of the year.

Modern engineering, spanning electrical, mechanical, aerospace, civil, and computer disciplines, stands as a cornerstone of human civilization and the foundation of our society. However, engineering design poses a fundamentally different challenge for large language models (LLMs) compared with traditional textbook-style problem solving or factual question answering. Although existing benchmarks have driven progress in areas such as language understanding, code synthesis, and scientific problem solving, real-world engineering design demands the synthesis of domain knowledge, navigation of complex trade-offs, and management of the tedious processes that consume much of practicing engineers' time. Despite these shared challenges across engineering disciplines, no benchmark currently captures the unique demands of engineering design work. In this work, we introduce EngDesign, an Engineering Design benchmark that evaluates LLMs' abilities to perform practical design tasks across nine engineering domains. Unlike existing benchmarks that focus on factual recall or question answering, EngDesign uniquely emphasizes LLMs' ability to synthesize domain knowledge, reason under constraints, and generate functional, objective-oriented engineering designs. Each task in EngDesign represents a real-world engineering design problem, accompanied by a detailed task description specifying design goals, constraints, and performance requirements. EngDesign pioneers a simulation-based evaluation paradigm that moves beyond textbook knowledge to assess genuine engineering design capabilities and shifts evaluation from static answer checking to dynamic, simulation-driven functional verification, marking a crucial step toward realizing the vision of engineering Artificial General Intelligence (AGI).

Instead of injecting 3D representations, we unlock VLMs using spatially relevant 2D images. To this end, we introduce a novel 2D spatial data generation and enables annotation the creation pipeline of a b di uilt verse upon set scene of spatial data tasks, with 3D ranging ground-truth.