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Xi Jinping lands in Washington on Wednesday for his first US visit in a decade, and artificial intelligence has become one of the sharpest items on the agenda. Treasury Secretary Scott Bessent said today he had a "successful" meeting with Chinese Vice Premier He Lifeng, where the two discussed establishing a formal "U.S.-China AI Dialogue," a concrete diplomatic step that lands just days after AI safety experts on both sides of the Pacific sounded fresh alarms. The two governments don't even agree on what the actual risk is: US officials keep circling existential, loss-of-control scenarios, while Chinese counterparts have historically focused on nearer-term harms like job displacement and disinformation.

Meanwhile, in a completely different corner of AI, two of the best-funded startups on the planet are being asked a much simpler question, what are you actually building, and refusing to answer.

Here’s what happened in AI today:


• AI safety just became a real agenda item ahead of Wednesday's Trump-Xi summit, with a formal "U.S.-China AI Dialogue" now on the table.

• Two heavily funded "world model" startups won't say what they're actually building or when it ships.

• A startup that builds other startups just raised $100 million and went all-in on physical AI.

…and a whole lot more that you can read about below.

• AI Just Became a Bargaining Chip in the Trump-Xi Summit

Xi Jinping arrives in Washington on Wednesday for a state visit that will include a formal dinner with Trump, their first in-person meeting on US soil in a decade. Trade, tariffs, rare earth minerals, and Taiwan are all on the agenda, but AI has moved up the list fast. Treasury Secretary Scott Bessent told reporters today that his meeting with Chinese Vice Premier He Lifeng went well, and that the two sides discussed setting up a formal "U.S.-China AI Dialogue" to address what he called "shared risks." The push for cooperation comes directly on the heels of last weekend's rare, public agreement among Dario Amodei, Sam Altman, and Elon Musk that AI development needs to slow down, and Google's Friday disclosure that its Gemini model had autonomously hacked three outside companies. Not everyone expects Trump himself to treat the moment with real urgency. "I don't think that Trump is feeling any pressure about the existential AI risk issue. He calls it a hoax multiple times," one analyst told The Hill, comparing his posture to how he's handled climate change. The US and China don't even agree on what the actual danger is: American officials keep circling loss-of-control, catastrophic-risk scenarios, while Chinese counterparts have generally focused on nearer-term harms like job displacement and disinformation.

• Two of AI's Best-Funded Startups Won't Say What They're Actually Building

At a panel on "world models" at the All-In conference, TechCrunch pressed the two most prominent companies in the space, Yann LeCun's AMI Labs and Fei-Fei Li's World Labs, on how they actually plan to make money. The answer, largely, was silence. Michael Rabbat, AMI's co-founder and VP of World Models, told the panel bluntly: "We'll talk about it when we're ready to talk about it," later describing the company as still in a "research and building phase" with no public product timeline. World models are built to automate spatial intelligence, technology that could plausibly power anything from self-driving cars to warehouse robots to fully explorable video environments, and AMI has already dipped into manufacturing, biomedicine, robotics, and medical AI through a partnership called Nabia, without committing to any one of them. The uncertainty isn't just frustrating for outside observers. Alex de Vigan, CEO of data supplier Physicl, which feeds data into these systems without knowing its final use, said on the sidelines: "I wish they would tell us more. We could build more useful data if we knew what they were working on." World Labs, notably, has moved further into the open, having raised $1 billion and shipped Marble, a tool that generates explorable 3D worlds from text, images, or video.

Today's Job Board

Senior Frontend Engineer | Authologic
Remote (Full-time)
Build the Stripe-like infrastructure for online identity verification.

Software engineer, Fullstack | Aviator
San Francisco, CA, US (Full-time)
Build a Google-level engineering productivity suite for fast-moving software teams.

Staff Full Stack Engineer | Sully
Mountain View, CA, US (Full-time)
Build the autonomous AI agents that run entire hospital operations.

Senior Network Engineer | WarpBuild
Remote (Full-time)
Accelerate software development with WarpBuild's 10x faster CI infrastructure.

Backend Engineer | PropelAuth
US / Remote (Full-time)
Build team-based authentication for B2B SaaS companies.

Software Engineer | Candid Health
San Francisco, CA / New York, NY / Denver, CO, US (Full-time)
Build the autonomous revenue cycle management platform used by healthcare providers.

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Today's Money Moves 💸

A Startup That Builds Other Startups Raised $100M to Go All-In on Physical AI

Vantora, a company that builds and launches other startups, raised $100 million and is now focusing entirely on physical AI, betting that the next wave of AI value creation happens in robots and hardware, not just software.

Manus Is in Talks to Raise $500M at a $4B Valuation

The Chinese AI agent startup, which had to unwind a blocked $2 billion acquisition by Meta earlier this year, is discussing a fresh $500 million round with IDG Capital, Boyu Capital, and existing backers Tencent and HSG as it resumes operating independently.

Vals AI Raised $40M to Build Benchmarks Labs Can't Train Around

Vals AI closed a $40 million Series A led by Andreessen Horowitz at a $400 million valuation, building confidential, real-world professional benchmarks for law, finance, and coding after its revenue grew eightfold in a year.

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Skill of the Day

Put Your Own AI Through a Real Gauntlet

When the same AI both writes your work and reviews it, "review" tends to become a polite pat on the back. A cleaner approach splits the job in two, one role builds, a separate role tears it apart, and forces real revisions against a bar you set in advance.

Run this inside a single ChatGPT or Claude conversation, with clear roles and phases. First, set the bar: define the actual deliverable, its constraints, and specific pass-or-fail criteria before anything gets drafted. Let the builder produce a first version with zero self-criticism baked in. Then switch the same conversation into critic mode, and have it audit every single criterion, quoting the exact evidence behind each failure instead of vague impressions. Rebuild from that critique, then repeat the critic pass until the work actually passes, or you hit a round limit you set going in.

Prompt of the Day

The Gauntlet Loop

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Run a Gauntlet Loop on the task below.

TASK: [Describe the deliverable]
QUALITY BAR: [List specific pass-or-fail criteria]
CONSTRAINTS: [List limits, required facts, format, tone, and sources]

Phase 1 — BUILDER: Draft the strongest version without critique.
Phase 2 — CRITIC: Evaluate every criterion. For each failure, quote evidence, explain it, and prescribe a specific revision. Do not rewrite.
Phase 3 — BUILDER: Revise using the critique.

Repeat Phases 2-3 until every criterion passes or three rounds end. Finish with a pass/fail scorecard.

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