Good morning. The AI revolution started in the cloud. Now it's coming home. Nvidia unveiled the first personal laptops designed to run AI agents — slim, light machines powered by a newly designed chip, RTX Spark, which the company calls “the most efficient PC chip ever built.”

The new machines, announced during the Computex conference in Taipei, will carry premium price tags, targeting creators, AI developers and gamers, Nvidia's OG-users.

The laptop news, coupled with a string of announcements that included a new AI model, underscores how quickly AI agents have upended the tech industry, the WSJ's Robbie Whelan and Amrith Ramkumar report.

Although demand for GPUs to train AI models made Nvidia the world’s most valuable company, agentic computing leans heavily on central-processing units, or CPUs. Nvidia expects these types of tasks to largely replace AI usage in the form of consumers having conversations with chatbots such as OpenAI’s ChatGPT, Google’s Gemini and Anthropic’s Claude.

Every company will be an agent company. Nvidia CEO Jensen Huang in a keynote Monday, acknowledged the growing importance of AI agents to businesses, which need more tooling and technical support as they start to implement the technology.

"Every company will be an agent company. Every company will have agents running inside. Every company will see that agents need its own operating system," he said.

As part of that vision, Nvidia also announced a new model, called Nemotron 3 Ultra, part of a series of “open” models from the chip maker and new “skills”—prepackaged technical instructions—for AI agents that integrate with its CUDA-X libraries.

Agents as the new developers. Nvidia executives last week briefed reporters, including the WSJ Leadership Institute's Belle Lin, on its new model and the CUDA-X move. 

While it’s important to build software libraries for human developers, it’s now just as important to build them for actual AI agents that write software, said Kari Briski, Nvidia’s vice president for generative AI software.  “We’re definitely starting to think of the agent as a developer.”

More news. Nvidia also said its next-generation AI computing platform, Vera Rubin, is in full production and will begin shipping to customers in the third quarter. 

Venture capital turns to hardware and beyond. A technology that analyzes relationships between data points more efficiently and cheaply than LLMs; superconductors viable for large-scale applications... These represent examples of "deep tech," a broad category encompassing advanced computing, robotics, and physical AI that's drawing growing attention from venture capitalists once known for early bets on software, internet services, and social media.

“There is a huge pivot into deep tech,” David Byrd, a general partner at BlueYard Capital tells the Journal's Kate Clark. Many investors, he said, are realizing that “the thing I was doing in the past of backing the [business] software company isn’t going to work in the future.”

Already this year companies in global robotics and physical AI raised more than $23 billion as of May 20, the Journal reports, citing PitchBook data. 

Deeper into deep tech and related fields. 

Advanced computing startups, which include chips, data centers and quantum computing, are also benefiting from the shift, raising over $20 billion so far this year, compared with $28 billion in all of 2025. And investment in U.S. critical-mineral startups hit a record $630 million last year, as artificial intelligence drives demand for the materials needed to build chips and data centers.

Survey: How entrepreneurs are approaching AI. Entrepreneurs view artificial intelligence as a key driver of productivity and growth. But while enthusiasm is high, few fast-growing businesses can directly link their AI efforts to exact financial outcomes.

Those are among the key findings of a recent EY-Parthenon survey of 300 entrepreneurs.

The WSJ Leadership Institute talked with Andrea Guerzoni, global vice chair, EY-Parthenon, about the results. Edited highlights are below.

WSJLI: Eighty percent of entrepreneurs surveyed said they plan to increase AI investment in 2026. Is that surprising?

Guerzoni: In this sample of 300 entrepreneurs there is a disproportionate amount of fast growing, recently formed companies… So maybe it's a bit skewed towards the extreme, but the trends are exactly what we are observing.

They're actually looking at agentic AI and workflows—more than just simplification and effectiveness. And actually the most sophisticated are setting up entire new businesses based on AI technology. So it's happening.

Even among entrepreneurs, AI is believed to be a technology that can not just add efficiencies, but actually increase the possibility to get new customers, to create new services, and maybe to change their operating models in a way that was unthinkable before.

And this is something that is pretty clear from the traditional CEO outlook… So I think that the times of skepticism about the return of investment are behind us.

WSJLI: Speaking about that return on investment, according to the survey, 9% of those entrepreneurs surveyed formerly connect AI impact to financial reporting and senior management review. Why so low?

Guerzoni: I think the primary reason is the level of sophistication of the financial system, the non-financial system, so operational controls, KPIs, etc.

These kinds of metrics and methodologies that have been developed very recently by larger companies really to demonstrate to their stakeholders that there is a return. It's not that embedded in companies where the stakeholders group is relatively smaller. 

WSJLI: What other unique challenges shape the approach of entrepreneur-led companies to AI?

Guerzoni: The first concerns the constraints related to skill sets. It's across the board…The other key theme is that the accessibility to capital has decreased over the last 12 months. Their perception is that capital is more scarce, which is not the case for the larger companies...

And the third and probably most interesting one, I mean, AI without alliances, it's very difficult. It's a team sport... The survey provides a clear picture regarding the fact that entrepreneurs are much more skeptical about their ability to forge alliances with tech players to speed up the process. And this has proven a fundamental success factor for larger companies.

• Chip stocks powered the S&P 500 up 16% across April and May, a two-month surge matched only four other times since 1950, according to Dow Jones Market Data. The index was higher six months later each time, by a median 17%.

• Iran's cyber operators are tapping AI models from OpenAI, Google and other western companies to develop malware and phishing attacks at a speed and scale not experienced before, experts tell the FT.

• SoftBank Group announced plans to invest at least $52 billion in a network of large-scale data centers across France, the Japanese conglomerate's biggest AI infrastructure bet in Europe to date, WSJ reports.

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Follow Isabelle Bousquette on LinkedIn, Instagram, X, and TikTok for more behind the scenes on her tech and AI coverage, and lately, her contributions to the WSJ Leadership Institute's new Executive Resilience series, where she's profiling America's top execs about their fitness and wellness habits.

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Steven Rosenbush is chief of the enterprise technology bureau at the WSJ Leadership Institute. He also has a column. You can follow him on LinkedIn.

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