Tech
Meta’s loss is Thinking Machines’ gain
Weiyao Wang spent eight years at Meta — his first job out of college — helping build multimodal perception systems and contributing to open-world segmentation projects, including SAM3D. His final day at Meta was last week, and he has since joined Thinking Machines Lab (TML).
His move to TML comes as the AI startup expands on multiple fronts. It just signed a multibillion-dollar cloud deal with Google, giving it access to Nvidia’s latest GB300 chips and making it one of the first startups to run on the hardware.
The agreement, announced this past Tuesday at Google Cloud Next, follows an earlier partnership with Nvidia, and puts TML in the same infrastructure tier as Anthropic and Meta. (Meta reportedly held talks to acquire Thinking Machines around this time last year and has more recently been picking off TML’s founders one by one.)
The talent picture remains fluid. Wang and Kenneth Li — a Harvard PhD who spent 10 months at Meta before joining TML this month — are the latest examples of a talent grab that runs in both directions. Business Insider reported last week that Meta has now poached seven of TML’s founding members. A review of recent hires shows Thinking Machines is raiding Meta right back. At least, it appears based on a review of LinkedIn profiles, that TML has been hiring more researchers from Meta than from any other single employer.
The most prominent is Soumith Chintala, TML’s CTO, who spent 11 years at Meta and co-founded PyTorch, the open source deep learning framework that now underpins most of the world’s AI research. He left Meta in late 2025 and was appointed CTO earlier this year. Piotr Dollár, another 11-year Meta veteran who served as research director and co-authored the influential Segment Anything model, is now on TML’s technical staff. Andrea Madotto, a research scientist in Meta’s FAIR division focused on multimodal language models, joined TML in December. James Sun, a software engineer with nearly nine years at Meta working on LLM pre- and post-training, also made the jump.
TML has drawn talent from beyond Meta, too. Neal Wu — a three-time gold medalist at the International Olympiad in Informatics and a founding member of the buzzy coding startup Cognition — joined early this year. Jeffrey Tao came via Waymo, Windsurf, and OpenAI. Muhammad Maaz previously held a research fellowship at Anthropic. Erik Wijmans arrived from Apple. Liliang Ren spent two and a half years on Microsoft’s AI Superintelligence team pre-training OpenAI models for code before joining in March.
The startup’s headcount now stands at around 140.
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Meta’s pay packages — seven figures, no strings attached — are well known by now. For researchers weighing their other options, the calculus may be as simple as this: Thinking Machines Lab is right now valued at $12 billion. Though that figure would’ve been unimaginable for a company at this stage in any previous tech cycle (it has released just one product so far), compared with the record-breaking valuations of OpenAI and Anthropic, there’s still a lot of financial upside.
Reached Friday morning, a spokesperson for TML declined to comment for this story.
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Tech
Anthropic created a test marketplace for agent-on-agent commerce
In a recent experiment, Anthropic created a classified marketplace where AI agents represented both buyers and sellers, striking real deals for real goods and real money.
The company admitted this test — which it called Project Deal — was only “a pilot experiment with a self-selected participant pool” of 69 Anthropic employees who were given a budget of $100 (paid out via gift cards) to buy stuff from their coworkers.
Nonetheless, Anthropic said it was “struck by how well Project Deal worked,” with 186 deals made, totaling more than $4,000 in value.
The company said it actually ran four separate marketplaces with different models — one that was “real” (where everyone was represented by the company’s most-advanced model, and with deals actually honored after the experiment) and another three for study.
Apparently, when users are represented by more advanced models, they get “objectively better outcomes,” Anthropic said. But users didn’t seem to notice the disparity, raising the possibility of “‘agent quality’ gaps” where “people on the losing end might not realize they’re worse off.”
Also, the initial instructions given to the agents didn’t appear to affect sale likelihood or the negotiated prices.
Tech
Nuclear startup X-energy raises $1B in data center-driven IPO
Nuclear startup X-energy raised $1 billion in its initial public offering yesterday, selling 44.3 million shares for $23 each, a hefty premium above the $16 to $19 per share it was seeking. Initially, the company had hoped to raise around $800 million.
The stock is expected to begin trading on Friday on the Nasdaq Exchange under the ticker XE.
X-energy is building small modular reactors capable of generating electricity or delivering heat to industrial processes. The company has a deal with Dow to provide heat and power to a chemical plant in Texas and another with Amazon to sell as much as 5 gigawatts of nuclear power by 2039. Amazon’s Climate Pledge Fund led X-energy’s Series C-1 round.
Nuclear startups like X-energy have been buoyed by surging demand for electricity from data centers and other parts of the economy that have been electrifying.
The company says its reactors will generate 80 megawatts of electricity. Each Xe-100 reactor is cooled by helium gas, which flows over billiard ball-sized “pebbles” that are packed with BB-sized TRISO fuel pellets. TRISO fuel, which contains a kernel of uranium wrapped in carbon and silicon, was developed years ago to be safer than existing fuel designs, though it hasn’t been widely used. X-energy says its fuel can withstand higher temperatures, helping to keep the fuel contained and reduce the potential of a meltdown.
Tech
Marked-up Mac minis flood eBay amid shortages driven by AI
Overpriced Mac minis are flooding eBay amid shortages of the sold-out machines, which have become a favored tool for running on-device AI models like OpenClaw.
This week, reports indicated that the $599 M4 Mac mini base model with 16GB RAM and 256GB of storage is sold out on Apple’s retail website, with no options for delivery or in-store pickup. The shortages have since extended to other configurations of the base model, regardless of the amount of memory selected. This is the first time the base model has been sold out, some outlets noted. Meanwhile, models with higher storage (512GB and up) are only available to ship starting in June.
As a result, eBay has become a secondary market for these in-demand computers. On the site, various configurations of the M4 Mac mini are available for sale at higher prices than if buying direct from Apple, which is no longer an option.
Apple’s power-efficient Mac minis have become popular devices for testing and running at-home, on-device AI models, beginning with the OpenClaw craze but now extending to OpenClaw alternatives like ZeroClaw, other AI tools from Anthropic and OpenAI, Perplexity Computer, or other specialized local models. Unlike some PCs, Mac minis also run quietly and tend to be more reliable for 24/7 use, compared with laptop computers.
The shortage of the devices also comes alongside an industry-wide memory crunch and plans for a Mac mini refresh, according to Bloomberg. However, refreshes of product lines haven’t led to shortages before.
Apple did not immediately respond to a request for comment.
This perfect storm of supply chain stress and increased demand for AI-friendly machines has inflated the prices of used consumer electronics.
As of Friday morning, M4 base models with the 16GB RAM/256GB SSD configuration were selling at markups like $715-$795 for a new, “open box” model, and as high as $979 for an “excellent” refurbished version. Some “lightly used, pre-owned” Mac minis with this configuration were selling for around $700 — more than $100 more than the price of a new base model.
There was also a single listing for a $925 brand-new M4 Mac mini with the same 16GB RAM and 256GB storage; the listing warned in bright red text: “Last one.”
While you still may be able to score a reasonably priced refurb if you keep a close eye out (or if you win an eBay auction where the bid has started at a lower price point), it seems that the demand for the device is going to keep prices up until Apple’s supply chain refreshes.
And now that the Mac mini is unavailable, Apple has begun to see increased demand for the Mac Studio, too. That computer is also now sold out across several configurations.
As Ars Technica pointed out, you can still get a MacBook Pro with 128GB RAM and larger SSDs within a few weeks, and even the new and popular MacBook Neo is still shipping within two to three weeks. This suggests the real issue is consumer demand for the Mac mini itself.
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