Nicolas Sauvage is betting on the boring parts of AI

Nicolas Sauvage believes it takes 4 years for the finest bets to look apparent — pondering that he shared on stage final week at StrictlyVC’s San Francisco occasion, which TDK Ventures co-hosted.

It’s a idea he’s been working to show since 2019, when he based the company enterprise arm of the Japanese electronics big, which is now managing $500 million throughout 4 funds. The AI chip startup Groq, valued at $6.9 billion throughout its most up-to-date funding spherical final fall, is the highest-profile instance of this pondering.

In 2020, effectively earlier than the generative AI increase made infrastructure bets look apparent, Sauvage wrote a verify into the firm, which was based by Jonathan Ross — one of the engineers who constructed Google’s Tensor Processing Units. Groq was centered from the begin on inference: the computational heavy lifting that occurs each time a mannequin responds to a question. Ross had designed his chip by constructing the compiler first, stripping the structure down till, as Sauvage describes it, “you can’t remove one part and have it still work.”

It might need appeared area of interest to some, however figuring out what he did about his guardian firm’s constraints, Sauvage noticed asymmetry. Unlike client {hardware}, which has a pure ceiling, demand for inference retains compounding with each new utility and each new mannequin. Sauvage couldn’t know then that demand for inference would explode this yr, thanks to each AI agent that plans and acts throughout dozens of calls (the place a single question used to suffice).

But in some methods, Ross acquired fortunate, too. After all, a Japanese electronics conglomerate finest recognized for magnetic tape is not, on its face, the most evident investing companion. In truth, Sauvage describes TDK Ventures’ personal existence as not possible. But after two back-to-back Stanford lectures — one making the case for company VC, one cataloguing each cause it fails — Sauvage, who is French and joined TDK in Silicon Valley by means of an acquisition, pitched the concept to higher-ups at TDK headquarters regardless of having no apparent standing to take action. (“I’m not Japanese. I don’t speak Japanese; I don’t live in Tokyo,” he informed this editor.)

After refusing to take no for a solution, he lastly acquired the inexperienced gentle in to construct a fund whose mandate was to reply one query: What’s the subsequent massive factor for TDK, and what may kill it?

The portfolio he has since assembled is dotted with applied sciences which have grow to be extra broadly fascinating to VCs over the final yr: solid-state grid transformers, sodium-ion batteries for knowledge facilities, different battery chemistries that sidestep the geopolitical fragility of lithium and cobalt.

The self-discipline behind all of it is the identical: determine the bottleneck 4 years out, then discover the founders already working on it.

The query, of course, is what’s subsequent. For his half, Sauvage is watching bodily AI carefully — not all of robotics however robots with a extremely particular job to be completed. Agility Robotics, for instance, in his portfolio, focuses on the single, mundane process of shifting issues from one place to a different in warehouses dealing with workforce shortages. Another portfolio firm, Swiss portfolio ANYbotics, builds ruggedized robots for environments too hazardous for human staff — locations the place the job definition is basically to go the place folks can’t. The through-line is readability of objective. The robots Sauvage is betting on don’t attempt to do every part; as a substitute, they do one exhausting factor reliably.

Sauvage says he’s additionally watching the compute stack shift once more. GPUs dominated coaching — the large, parallel computation of educating a mannequin. Inference chips like Groq’s are reshaping what occurs when that mannequin speaks: sooner, cheaper, at scale. Now, Sauvage argues, CPUs are due for a renaissance. They’re not the strongest chips or the quickest. But they’re the most versatile and finest suited to the branching, decision-making logic of orchestration. When an AI agent delegates a process, checks on its progress, and loops again throughout dozens of steps, one thing has to handle the complete choreography. That one thing, more and more, appears like a CPU.

And then there’s China. A current report from Eclipse — a enterprise agency he follows carefully — documented what Sauvage describes as “vibe manufacturing” — the speedy, AI-assisted iteration of bodily {hardware} prototyping, mirroring what vibe coding did for software program. Chinese producers, the report discovered, are compressing the design-build-test cycle for bodily merchandise in methods Western provide chains aren’t but geared up to match.

For Sauvage, it’s a bottleneck sign — and one he’s already shifting on with TDK Ventures’ varied investments. One remaining unsolved downside, he says, is dexterity. Models are enhancing quick sufficient that bodily AI feels inevitable; what’s nonetheless lacking is the bodily fluency to match. The international locations and firms that work out the best way to iterate on atoms as quick as others iterate on code can have a producing benefit. That’s the wave for which he’s positioning TDK Ventures right now.