Donald Trump apparently is so aligned with Nvidia CEO Jensen Huang—who has become the president’s key advisor on AI—that he ignored intelligence indicating that Huang was the target of a “Chinese spy plot,” and did so partly to protect Nvidia’s stock.

The New York Times spoke with people briefed on US intelligence agencies’ surveillance and granted them anonymity to discuss findings drawn from “classified intelligence.” According to sources, about a year ago, Trump was briefed that “Beijing was getting reports from someone with direct access” to Huang. That “someone” was Alice Huang, or Huang Le, a Chinese citizen and former top executive at a Singapore cloud company called Megaspeed.

According to sources, the US had already suspected that Alice Huang—who is not related to Jensen Huang—was helping China evade export controls to gain access to high-end Nvidia chips through Megaspeed. But it alarmed investigators to discover that she may have used her role at Megaspeed to gain direct access to Jensen Huang. It’s now believed she may have leveraged that closeness to feed China intel not only on one of America’s leading AI companies, but also to influence Trump’s thinking on AI. As Treasury Secretary Scott Bessent noted last month ahead of Trump’s AI talks with China President Xi Jinping, “the president is completely aligned with Jensen Huang, the CEO of Nvidia.”

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© KENT NISHIMURA / Contributor | AFP

A top executive of a Singapore AI cloud company that was accused of illegally selling Nvidia chips to China could also have been a Chinese spy, sources have told the New York Times.

The UW Medicine Institute for Protein Design (IPD) today released a new open-source model for creating proteins with specific functions, called RFD4-Proteina. It is the first AI protein model the University of Washington has co-developed with semiconductor giant Nvidia.

The release comes on the heels of a major computing boost. Earlier this month, IPD announced it had received a large grant of computing power from Nvidia CEO Jensen Huang and his wife, Lori Huang, through their foundation. In June, the institute began accessing Nvidia graphics processing units, or GPUs, through cloud company CoreWeave. The grant is expected to support the institute for a year.

“RFD4-Proteina will open the door to new solutions in medicine, sustainability, materials and biotechnology,” David Baker, director of IPD and a 2024 Nobel laureate in chemistry, said in a statement. He earlier told GeekWire that the foundation’s grant has been “transformational” for the institute’s work.

IPD has used deep learning to develop and release a series of tools, including RoseTTAFold for predicting protein structures and RFdiffusion (RFD) for designing new proteins. The new model’s name nods to RFD and references Nvidia’s Proteina-Complexa computational models.

The team is touting RFD4-Proteina as “a considerable improvement over previous methods” that is faster and requires significantly less computational power.

The models have allowed researchers to design proteins never imagined before, with potential as drugs for challenging diseases or as tools for managing environmental waste such as toxic chemicals and plastics, among other applications. The IPD lists 11 spinout companies, including vaccine developer Icosavax and protein-design startup Archon Biosciences.

Seth Woodbury used RFD4-Proteina in his enzyme work as a , a UW bioengineering predoctoral candidate. “In just a few days we designed a pesticide-degrading enzyme that performs many fold better than my previous best, which took months to design,” he said. Woodbury last year published a paper in Nature on enzyme research.

At IPD, the RFD4-Proteina work was led by UW doctoral students Nathaniel Corley, Maxwell Kazman and Rafi Brent, along with Kieran Didi, a visiting student from the University of Oxford.

RFD4-Proteina is available through Berkeley Software Distribution. 

The UW Medicine Institute for Protein Design (IPD) has announced a giant grant of computing power from the Jen-Hsun and Lori Huang Foundation, supercharging its research into new protein discovery.

“We have made more rapid progress on methods development than any time in my career,” said David Baker, director of the IPD and a 2024 Nobel laureate in chemistry. “I mean, it’s just been totally mind-boggling.”

In June, the IPD began accessing Nvidia graphics processing units, or GPUs, through the cloud computing company CoreWeave. The grant from the foundation, which was co-founded by Nvidia CEO Jensen Huang and his wife, Lori Huang, totals nearly 7 million GPU hours. The allocation is expected to support the institute for a year.

The IPD’s work has long been rooted in computation. In 2003, Baker and fellow University of Washington researchers used their Rosetta software to design a protein with a structure unlike any known in nature. In recent years, the institute has embraced deep learning, releasing tools such as RoseTTAFold for predicting protein structures and RFdiffusion for designing new proteins.

With this technology, the institute designs previously unimagined proteins with potential for treating intractable diseases and tackling environmental challenges such as plastic waste and toxic pollutants. The tools are open source and available for public use.

Running them takes vast computing power, though, and until now the institute has lacked the resources to pay for outside cloud services. It has relied instead on its own computer cluster, which works but is limited. Baker said IPD scientists meet every Tuesday at 5 p.m. to decide what to test over the coming week, keeping capacity in mind.

To advance their protein research, the team experiments with different architectures for the AI models and tweaks the datasets used for training, sometimes expanding them or adding synthetic data. With compute restrictions, however, researchers historically have made multiple changes at once rather than testing each alteration individually, a more systematic approach that yields cleaner results.

Despite the hurdles, the IPD has produced a steady stream of breakthroughs with its models and protein designs, publishing regularly in leading scientific journals such as Nature and Science.

Google DeepMind is pursuing similar AI-driven protein research. Baker said he knew the tech giant’s team had much more computing power than the IPD, but he didn’t fully appreciate what that could unlock.

That capacity “spawns more ideas because you know you can test them,” Baker said. “So it just creates this incredibly fertile, creative environment.”

Jensen Huang, the foundation’s co-president, said in a statement that the extra computing power allows the UW researchers to train AI “on tens of millions of molecular structures, learning from virtual experiments, and finding novel protein designs that have eluded nature.”

Huang predicted that many of the most important future medicines “will come from proteins that have never existed.”

Baker said the IPD still holds its Tuesday meetings, but the new compute capabilities — which he called “transformational” — open up more options.

“The team is iterating fast,” Baker said. “We get feedback on all these different computational architecture explorations, and there’s just so many different things you can try.”

Microsoft is turning to an old friend and a familiar advantage in search of a new edge in AI.

The company and its longtime partner Nvidia on Wednesday started taking orders for a new line of high-end Windows PCs built to run large AI models independent of the cloud.

Microsoft also announced what it calls “Windows Hybrid Intelligence,” a set of features that will let its Copilot assistant read the files on a PC, take actions on the machine and opt to run AI models locally instead of in the cloud when it makes sense.

It’s not a new concept to users of such programs as Anthropic’s Claude, Perplexity and OpenClaw, which already work with the files on a user’s computer. But only Microsoft can build the features into Windows itself, along with security controls that limit what an AI agent can reach on the machine and will keep a separate record of what the agent does.

“I think agents are going to be the largest users of the file system,” Microsoft CEO Satya Nadella said during an on-stage conversation with Nvidia CEO Jensen Huang at an event in San Francisco.

Microsoft got an early jump in AI with its 2019 investment in OpenAI and the 2021 debut of GitHub Copilot, its AI coding assistant. But its Copilot products for consumers and businesses have since been overshadowed by OpenAI’s ChatGPT and Anthropic’s Claude.

Both rivals also moved quickly on AI agents that write code and carry out other tasks on a user’s computer, the kind of software Microsoft is now building into Windows. Microsoft’s own Copilot Cowork, which it introduced in March, integrates Anthropic’s Claude.

The tech giant has been reworking Copilot to catch up. Earlier this year, it put its Copilot teams for consumers and businesses under Jacob Andreou, now its executive vice president of Copilot. Last month, it released a new version of the app with tools for coding and long-running tasks.

Where Copilot is headed: Windows Hybrid Intelligence gives Copilot three new capabilities, as Andreou described them on stage. The assistant can draw on all the files on a PC, take actions such as moving files and changing settings, and hand tasks to AI models running on the machine “when cost or privacy matter more.”

Copilot will still use the cloud for the hardest tasks, Andreou said, and will act on the PC only with the user’s permission.

Microsoft said the features are expected to begin rolling out in the coming months on Copilot+ PCs, the AI-focused Windows machines it introduced in 2024.

Developers will get a version first. An experimental release coming later this month will let GitHub Copilot automatically send simpler coding tasks to an AI model on the PC and harder ones to the cloud.

In one example depicted on stage, Copilot’s Autopilot agent found an email from Andreou’s accountant, gathered tax documents scattered across his PC, renamed and sorted them into folders, bundled them into a zip file and drafted a reply with it attached, pausing for his approval before sending. The sorting was handled by AI models on the laptop, he said, so the tax details weren’t sent to the cloud.

Running AI models on the PC reduces the usage charges that come with AI in the cloud. Nadella wrote on X that Microsoft is bringing “unmetered intelligence to every desk and every home,” echoing the company’s original mission of “a computer on every desk and in every home.” A slide in the presentation said local models would run tasks on the PC “at no extra cost.”

Microsoft is also adding thousands of quick actions to the search box on the Windows 11 taskbar, such as switching to dark mode, arranging windows or sending a text message. Those start rolling out Wednesday to people in the Windows Insider testing program.

An option to get Copilot answers in the search box will be opt-in and will arrive in select markets later this year, according to the company.

The Recall precedent: Microsoft has run into trouble before with AI that looks at what’s on a PC. Recall, a feature that takes periodic screenshots of a user’s activity to make it searchable, drew objections from security researchers when it was announced in 2024. Microsoft delayed it and made it opt-in before releasing it widely in 2025.

Recall didn’t come up at Wednesday’s event. Microsoft’s blog post says Copilot’s access to local content, which it describes as “files and recent activity,” will require the user’s permission.

Limits on AI agents: Pavan Davuluri, Microsoft’s executive vice president of Windows and Devices, said the AI agents that run on PCs today are “fundamentally insecure because they have broad system access.”

Microsoft’s answer is a technology called Microsoft Execution Containers, now generally available in Windows 11, which lets an organization set which files and networks an AI agent can reach. Microsoft said OpenAI’s Codex and OpenClaw already support it, and that Anthropic’s Claude Code and Perplexity plan to.

Meta’s Muse agent is coming to Windows as an app that uses the technology, as well.

The new PCs: The machines are built around Nvidia’s RTX Spark chip and aimed at developers and creative professionals who want to run large AI models on their own computers.

Microsoft’s Surface Laptop Ultra, a 15-inch laptop with up to 128GB of memory, starts at $2,599 and will be available Oct. 16, the same day similar laptops from Asus, Dell, HP, Lenovo and MSI begin shipping.

A desktop version for developers, the Surface RTX Spark Dev Box, costs $5,999 and ships in the U.S. in November.

Microsoft is pitching the laptops against Apple. It says machines with the Nvidia chip start producing AI responses up to 2.1 times faster than a 16-inch MacBook Pro with Apple’s M5 Pro chip and generate AI images up to 4.3 times faster, citing tests it commissioned or that Nvidia ran on preproduction machines.

The company is also offering up to $1,000 back to buyers who trade in a MacBook Pro.

Huang said the chip took more than 4,000 engineering years and started with a conversation he had with Nadella four years ago.

Nvidia’s Windows roots: Sriram Krishnan, the venture capitalist and former White House AI advisor who moderated the conversation, asked Huang for a favorite memory of working with Microsoft. Huang said Nvidia owes its existence to Windows.

He recalled a moment in late 1992, when Windows 3.1 was new and he and his co-founders, who had worked mostly on workstations, started imagining a PC with 3D graphics that could run games and design software. They started the company the next year.

“If not for Windows, Nvidia wouldn’t have been founded,” Huang said.

He traced a line from there to the AI boom. Windows brought graphics chips to the PC, he said, which led to Nvidia’s GeForce chips and its CUDA software, which gave AI researchers the computers they needed for deep learning.

Nadella joked that Huang was “now going to do a little transfer of market cap back to me.” Nvidia is the world’s most valuable company, at about $5.8 trillion. Microsoft is worth about $3.9 trillion.

“Windows has been with me for 34 years,” Huang said at the end of the conversation. “Looks like it’s going to be with me for 34 more.”

“There you go,” Nadella added before they walked off the stage.