Jonathan Ross founded Groq, an AI inference company, after working on Google’s Tensor Processing Unit. Groq announced in December 2025 that he would join NVIDIA as part of a technology licensing agreement.[1][2]
Start with Jonathan Ross on Masters of Scale →Links
Career
Groq’s December 24, 2025 announcement names Ross among staff joining NVIDIA to advance licensed inference technology. The agreement is non-exclusive: Groq says it will keep operating independently, with Simon Edwards becoming CEO and GroqCloud continuing to serve customers. The distinction matters because the technology license and staff transfer do not mean Groq itself became a NVIDIA subsidiary.[1]
Contributions
Ross’s work connects custom AI processors at Google with Groq’s Language Processing Unit. Inference means running an already trained model to answer a request. Groq built its processor and cloud around this execution stage, where response time affects whether an application can feel interactive.[2][3]
Ideas
In his Masters of Scale conversations, Ross frames speed as part of the product experience rather than a hardware statistic alone. A model that returns answers quickly can support applications that wait for several model calls or respond to a live conversation. His earlier TPU work and Groq’s LPU both use specialized hardware for neural-network computation, but the company’s inference focus addresses serving trained models rather than only the cost of training them.[2][3]
Tools, writing & talks
Writing, research & talks
Start here
Jonathan Ross on Masters of Scalemastersofscale.comThe guest page introduces Ross’s processor work and links conversations about inference speed.
Begin with the guest introduction and linked interview for an accessible account of why inference latency matters. The architecture article is a second step for readers comfortable with computer hardware.
Interview guest[2]- Groq Founder, Jonathan Ross: OpenAI & Anthropic Will Build Their Own Chips & Will NVIDIA Hit $10TRNyoutube.com
Groq's CEO argues that inference compute is the binding constraint on lab revenue, that energy gates compute, and that OpenAI and Anthropic will design their own chips.
Catalog workOriginal source - Groq Rocks Neural Networksgroq.com
A technical analysis of Groq’s processor architecture and its design tradeoffs.
Subject of analysis, not author[3]