Edge Computing Semiconductors Startups funded by Y Combinator (YC) 2026

The world generates petabytes of video every day, and almost none of it is readable to machines. Frontier VLMs that can unlock this (like Gemini) are too expensive to run at the volume real industries have, too generic for any single task, and can't be deployed on-prem where sensitive video lives. We are building an auto vision factory: take video plus a customer's objective, distill a frontier model, and post-train a small open model that is SOTA on that one task and serve it blazingly fast. Our first product, Marlin, is a 2B-parameter open-weights video VLM that matches Gemini-2.5-flash on dense captioning and temporal grounding at a fraction of the cost.

We want to push machines to where humans cant go. Presidential early career award winning Duke Semiconductor ECE Faculty Tania Roy and Sanjeev Chauhan are building a frontier semiconductor research lab. Their focus is on solving physical AI challenges from the semiconductor device level and building products around the moat of impossible to copy innovation. Their first work is on a new vision sensor that can run neural network filters right in the camera pixels and only collect data that machines care about. As physical AI develops, machines needs to understand the world around them if they aim to interact with them.

Stellon Labs is an AI research lab that is building tiny frontier AI models that can run on edge devices like smartphones, wearables and embedded systems. Our first open source model, KittenTTS, is a super-tiny text-to-speech model, that got 8K Github stars and 45K model downloads within 2 weeks of launching.