TechCrunch Desktop Logo TechCrunch Mobile Logo LatestStartupsVentureAppleSecurityAIAppsDisrupt 2026 EventsPodcastsNewsletters SearchSubmit Site Search Toggle Mega Menu Toggle Topics Latest AI Amazon Apps Biotech & Health Climate Cloud Computing Commerce Crypto Enterprise EVs Fintech Fundraising Gadgets Gaming Google Government & Policy Hardware Instagram Layoffs Media & Entertainment Meta Microsoft Privacy Robotics Security Social Space Startups TikTok Transportation Venture More from TechCrunch Staff Events Startup Battlefield StrictlyVC Newsletters Podcasts Videos Partner Content TechCrunch Brand Studio Contact Us Image Credits:Slava Blazer Photography for TechCrunch/StrictlyVC Venture Nicolas Sauvage is betting on the boring parts of AI Connie Loizos 12:10 AM PDT · May 4, 2026 Nicolas Sauvage believes it takes four years for the best bets to look smart — thinking that he shared onstage last week at StrictlyVC’s San Francisco event, which TDK Ventures co-hosted. It’s a theory he’s been working to prove since 2019, when he founded the corporate venture arm of the Japanese electronics giant, which is now managing $500 million across four funds. The AI chip startup Groq, valued at $6.9 billion during its most recent funding round last fall, is the highest-profile example of this thinking.
In 2020, well before the generative AI boom made infrastructure bets a go-to place to direct capital, Sauvage wrote a check into the company, which was founded by Jonathan Ross — one of the engineers who built Google’s Tensor Processing Units. Groq was focused from the start on inference: the computational heavy lifting that happens every time a model responds to a query. Ross had designed his chip by building the compiler first, stripping the architecture down until, as Sauvage describes it, “you can’t remove one part and have it still work.” It might have looked niche to some, but knowing what he did about his parent company’s constraints, Sauvage saw opportunity.
Unlike consumer hardware, which has a natural ceiling, demand for inference keeps compounding with every new application and every new model. Sauvage couldn’t know then that demand for inference would explode this year, thanks to every AI agent that plans and acts across dozens of calls (where a single query used to suffice). But in some ways, Ross got lucky, too.
After all, a Japanese electronics conglomerate best known for magnetic tape is not, on its face, the most natural investing partner. In fact, Sauvage describes TDK Ventures’ own existence as very unlikely. But after two back-to-back Stanford lectures — one making the case for corporate VC, one cataloguing every reason it fails — Sauvage, who is French and joined TDK in Silicon Valley through an acquisition, pitched the idea to higher-ups at TDK headquarters despite having no clear standing to do so. (“I’m not Japanese.
I don’t speak Japanese; I don’t live in Tokyo,” he told this editor.) After refusing to take no for an answer, he finally received the green light to build a fund whose mandate was to answer one question: What’s the next big thing for TDK, and what might kill it? Image Credits:Slava Blazer for TechCrunch/StrictlyVC The portfolio he has since assembled is dotted with technologies that have become more widely interesting to VCs over the last year: solid-state grid transformers, sodium-ion batteries for data centers, alternative battery chemistries that sidestep the geopolitical fragility of lithium and cobalt. var playerInstance_jwplayer_6a7d79964049b = jwplayer( "jwplayer_6a7d79964049b" ); playerInstance_jwplayer_6a7d79964049b.setup(); The discipline behind all of it is the same: identify the bottleneck four years out, then find the founders already working on it. The question, of course, is what’s coming next.
For his part, Sauvage is watching physical AI closely — not all of robotics but robots with a highly specific job to be done. Agility Robotics, for example, in his portfolio, focuses on the single, mundane task of moving things from one place to another in warehouses facing workforce shortages. Another portfolio company, Swiss portfolio ANYbotics, builds ruggedized robots for environments too hazardous for human workers — places where the job definition is essentially to go where people can’t.
Extract — continue reading at the source.
