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An annotated photo of who attended the tech dinner at the White House.
(Photo illustration: Sherwood News; Photo: Alex Wong/Getty Images)

An interactive who’s-who of the tech execs at Trump’s White House dinner

The White House invited a gaggle of top founders and tech executives for an intimate dinner at the White House.

Jon Keegan

A who’s-who of tech executives and AI power players sat side by side at a long table in the White House on Thursday evening to lather President Trump with praise for his leadership on AI.

Billed by White House spokesperson Davis Ingle as “the hottest place to be in Washington, or perhaps the world,” the exclusive dinner was packed with “the most brilliant people,” according to Trump, who said, “This is a high-IQ group.”

Proximity is power, and none of the tech figures were closer to Trump than Meta’s CEO, Mark Zuckerberg. Photos from the dinner showed the two laughing and chumming it up, a remarkable turn of fortune for Zuckerberg, who Trump once famously warned might “spend the rest of his life in prison” if he interfered in the 2024 presidential election.

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Meta CEO Mark Zuckerberg and President Trump at the White House (Saul Loeb/Getty Images)

Attendees included:

  • Dylan Field, Figma CEO

  • Sunny Madra, Groq president

  • Jason Chang, CSBio CEO

  • Alexandr Wang, Meta’s chief AI officer

  • Nathalie Dompé

  • Chamath Palihapitiya, Social Capital CEO

  • David Sacks, the White House’s “AI and crypto czar”

  • Mark Zuckerberg, Meta CEO

  • President Trump

  • First Lady Melania Trump

  • Bill Gates, Microsoft cofounder

  • Safra Catz, Oracle CEO

  • Gal Tirosh

  • Jamie Siminoff, Ring founder

  • David Limp, Blue Origin CEO

  • Mark Pincus, Zynga cofounder

  • John Hering, Lookout cofounder

  • Lisa Su, Advanced Micro Devices CEO

  • Meredith O’Rourke

  • Susie Wiles, White House chief of staff

  • Shyam Sankar, Palantir CTO

  • Sergey Brin, Google cofounder

  • Gerelyn Gilbert-Soto

  • Tim Cook, Apple CEO

  • Sam Altman, OpenAI CEO

  • Greg Brockman, OpenAI president

  • Anna Brockman

  • Tony Fabrizio

  • Sanjay Mehrotra, Micron CEO

  • Vivek Ranadivé, former TIBCO Software CEO and current CEO of Sacramento Kings

  • Satya Nadella, Microsoft CEO

  • Sundar Pichai, Google CEO

  • Jared Isaacman, Shift4 CEO

Notable absences

Perhaps more interesting than who was invited to the dinner was who didn’t attend.

Never one to hold a grudge, former “First Buddy” and Tesla CEO Elon Musk posted on X that he was invited, but would send a representative. It’s unclear if the Musk/Trump beef is heating up again.

Also absent was a representative from the company that is powering all of the AI that everyone was gushing about and recently struck a remarkably unusual trade deal with the White House: Nvidia. CEO Jensen Huang was notably missing from the gathering, but maybe he prefers one-on-one dinners at Mar-a-lago.

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Jon Keegan

DeepSeek releases new V4 series models highlighting efficiency and long context

Chinese AI lab DeepSeek has released a major new version of its eponymous open-source AI models that are nipping at the heels of leading frontier models in some areas.

The most significant DeepSeek-V4 Pro and DeepSeek-V4 Flash both have a 1 million-token context — the amount of information the model can actively work with in a single session — which is a crucial feature for complex, long-running coding tasks.

DeepSeek rebuilt how the models process information under the hood, making them substantially more efficient — and that efficiency is what makes the large context window actually usable.

Also, the new models’ coding skills have closed the gap with the major frontier models from Anthropic, OpenAI, and Google.

The authors of the model acknowledge some of V4’s shortcomings, such as its lower scores on reasoning benchmarks, saying that V4 “trails state-of-the-art frontier models by approximately 3 to 6 months.”

As open-weight models, V4 can be run on any user’s own hardware, making the V4 models among the top-performing open-source models out there. V4’s large context and token efficiency are especially significant among open-source models.

But like with earlier DeepSeek models, don’t ask it about Tiananmen Square.

DeepSeek Unveils Flagship AI Model a Year After Breakthrough

DeepSeek Unveils Flagship AI Model a Year After Breakthrough

DeepSeek rebuilt how the models process information under the hood, making them substantially more efficient — and that efficiency is what makes the large context window actually usable.

Also, the new models’ coding skills have closed the gap with the major frontier models from Anthropic, OpenAI, and Google.

The authors of the model acknowledge some of V4’s shortcomings, such as its lower scores on reasoning benchmarks, saying that V4 “trails state-of-the-art frontier models by approximately 3 to 6 months.”

As open-weight models, V4 can be run on any user’s own hardware, making the V4 models among the top-performing open-source models out there. V4’s large context and token efficiency are especially significant among open-source models.

But like with earlier DeepSeek models, don’t ask it about Tiananmen Square.

$28.5T
Rani Molla

SpaceX thinks its total addressable market (TAM) is a whopping $28.5 trillion for its businesses, according to an S-1 filing for its upcoming IPO reviewed by Reuters. And most of that market isn’t rockets. The company says roughly 90% could come from AI — largely selling artificial intelligence tools to businesses.

“We believe that our enterprise strategy, which is focused on serving the digital needs of the world’s largest industries with Al solutions, positions us competitively to pursue this rapidly ⁠growing opportunity,” ​SpaceX said in the filing. “We believe we have identified the largest actionable total addressable market in human ​history.”

TAM, of course, assumes capturing every possible customer. But even a small slice of a $28.5 trillion market would be enormous.

tech
Rani Molla

Tesla Cybercab production has begun

On Tesla’s earnings call earlier this week, CEO Elon Musk said production of the company’s steering-wheel-less Cybercab had begun. Since then, Musk and Tesla have posted videos showing the gold two-seater rolling off the line at its Texas Gigafactory and onto the road.

The Cybercab — meant both for consumers and Tesla’s Robotaxi network — is widely seen as central to the company’s future. “The future of the company is fundamentally based on large-scale autonomous cars and large scale and large volume, vast numbers of autonomous humanoid robots,” Musk said last year.

Whether these cars actually make it to consumers is another question. For now, regulations generally require steering wheels, and Tesla still has to prove the vehicles can reliably drive themselves.

On the earnings call, Musk said production would be “very slow” but would ramp up and go “kind of exponential towards the end of the year and certainly next year.”

tech
Rani Molla

Meta signs deal to use Amazon Graviton chips

Meta said it will deploy “tens of millions” of Amazon Web Services Graviton CPU cores to power so-called “agentic” AI systems — tools that can reason, plan, and act on their own. The move makes Meta one of the largest customers of Amazon’s in-house chips.

The deal also underscores a broader shift in AI infrastructure, as companies move beyond Nvidia GPUs and use different chips for different tasks.

Meta, which is working on its own custom inference chips, also has chip deals with Advanced Micro Devices and Nvidia.

Meta Partners With AWS on Graviton Chips to Power Agentic AI

Meta Partners With AWS on Graviton Chips to Power Agentic AI

The deal also underscores a broader shift in AI infrastructure, as companies move beyond Nvidia GPUs and use different chips for different tasks.

Meta, which is working on its own custom inference chips, also has chip deals with Advanced Micro Devices and Nvidia.

tech
Rani Molla

Oracle rises after Wedbush’s Dan Ives calls the stock a buy with 25% upside

Oracle extended its premarket gains Friday after Wedbush Securities’ Dan Ives initiated coverage with an “outperform” rating and a $225 price target — about 25% upside to its pre-initiation level — calling the enterprise software and cloud infrastructure company a “foundational infrastructure provider for the AI revolution.”

Ives argues investors are misreading Oracle’s heavy capital spending and negative free cash flow as risky, despite being backed by a massive $553 billion backlog of contracted demand. He says the company’s “secret sauce” is a two-part strategy: building high-performance cloud infrastructure for AI workloads while connecting those models directly to companies’ own data.

“We believe Oracle is in the early innings of a significant repositioning as it executes on this generational opportunity,” Ives wrote.

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