Nvidia's chip gains are outpacing any historical comparison.

Why it matters: Without these gains — which are drawing increased attention as AI transforms society — physics would slam the brakes on the data center boom.

Driving the news: Jensen Huang said Nvidia expects at least $1 trillion in revenue from its newest chips through 2027.

• It posted record sales last month, driven by Big Tech data center demand.

By the numbers: Nvidia has historically dominated the market. But its cumulative share has dropped from 100% in the first quarter of 2022 to 65% in the fourth quarter of last year, according to the research and consultancy firm SemiAnalysis.

Yes, but: Nvidia faces a threat as the industry shifts from one type of AI — training — to another — inference. Its chips are optimized for the former.

• "All this inference stuff is incredibly threatening to Jensen, because it's all efficiency-driven," Paul Kedrosky, a venture investor and fellow at MIT's Initiative on the Digital Economy, told the WSJ.
• "He's desperately trying to find a way to extend the franchise into inference."

Zoom out: Energy efficiency has long been a boring but important component of technology.

• We might think of energy-efficient appliances or a Toyota Prius — saving money and helping the planet.

But that's not what's happening with the AI boom. Energy efficiency is no longer a nice-to-have, it's a must-have.

• Electricity is physically limited. AI demand appears unlimited.
• That makes efficiency the backbone of AI's growth.

The intrigue: It's like going from a Model T to a Tesla in under a decade — instead of more than a century.

• If cars' fuel efficiency had improved as swiftly as chips, "we'd be driving to the moon and back in one gallon of gas," said Josh Parker, head of sustainability at Nvidia, the world's leader in AI computation.

Flashback: In 1865, British economist William Stanley Jevons observed that when England made coal steam engines more efficient, they actually used more — not less — coal.

• This has become known as the Jevons paradox, where energy efficiency — inherently a term to describe saving energy — often creates more demand for energy.

AI is putting the Jevons paradox on steroids.

• "The absolute footprint of AI, in terms of energy consumption, we do see it growing year over year, and we expect that trend to continue," Parker said.

How it works: Two essential components of a chip's efficiency are its energy consumption and how it's cooled.

• Physics dictates that electricity powering a chip ultimately becomes heat, which then needs to be cooled down.

Catch up fast: Cooling technologies broadly break down into two ways.

• Traditional air-cooled data centers often rely on evaporative cooling, which can consume significant amounts of water.
• Newer liquid-cooled systems can reduce that water use — though total demand still depends on design and location.

"If you have chips and servers, they're useless if you don't have power and you don't have cooling," said Rich Whitmore, who leads Motivair, Schneider Electric's liquid-cooling business, which works with Nvidia.

Zoom in: Each generation of Nvidia's chips — named after famous scientists — posts massive efficiency gains over the last.

• The latest chip on the market — called Blackwell — redesigned the whole architecture of computing to get more performance and efficiency, said Dion Harris, senior director of AI infrastructure at Nvidia.

What's next: If we went from a Model T to a Tesla in the past decade, imagining what comes next — in just the next few years — feels almost absurd.

• "Maybe some kind of hovercraft," Parker said, joking (maybe).

Sen. Marsha Blackburn (R-Tenn.) released a federal AI policy draft meant to shape Trump's promised "one federal rulebook."

Why it matters: Lawmakers on the Hill are vying to shape the Trump administration's AI agenda, and Blackburn is making her case to lead the effort.

Driving the news: Blackburn has been working with the White House on the draft and knows it'll be an ongoing negotiation as Congress and the White House hash out details, a source familiar with the discussions said.

What's inside: The new discussion draft text builds on a summary that Blackburn released last December, as she looks to build support for her proposal.

• It incorporates Blackburn's Kids Online Safety Act and the NO FAKES Act she co-sponsored with Sen. Chris Coons (D-Del.).
• The draft would impose a "duty of care" that would require AI developers to take reasonable steps to mitigate harms stemming from design features, along with chatbot safety provisions.
• It would also sunset Section 230 of the Communications Decency Act — a step further than the previous version, which called for reforms.

Between the lines: Blackburn frames the bill on what she and some conservatives call the "4 Cs" — children, creators, conservatives and communities.

• That maps closely to Trump's executive order, which mentions children, censorship, copyrights and communities.
• The draft bill adds provisions to codify Trump's "woke" AI executive order and his ratepayer protection pledge.

Context: Trump's order directs advisers to propose a "uniform" federal framework that would preempt conflicting state AI laws.

• An AI-generated version of the late actor Val Kilmer will appear in a new film, with the approval of his estate. (AP)
• Meta confirmed that internal use of an AI agent led to a security incident in which company and customer information was temporarily made available to a broader swath of employees than intended. (The Information)
• Google's Logan Kilpatrick said on X that the company will debut a new vibe coding experience within the company's AI Studio that has been in development for the past four months.
• Snowflake debuted "Project SnowWork," a more autonomous version of its AI data platform. (Axios)

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