Why NVIDIA Hardware Struggles on Large Model Decode | Jason Goodison
transcript
show notes
General Compute co-founder and CTO Jason Goodison breaks down their $100M Series A to build a dedicated inference cloud on Cerebras wafers. He explains why fast inference requires moving away from standard GPU racks, how the industry is shifting from a dial-up era to broadband interactivity, and why open-source models will drive the next generation of real-time AI agents. Check out our sponsor Lovable: https://lovable.dev. Turn ideas into software people love.
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Timestamps:
(00:00) Introduction
(00:54) The $100M Series A Announcement
(01:49) Why Fast Inference Needs Custom Silicon
(03:56) The Broadband Moment for AI
(05:23) Bringing Fast Inference to Open Source
(08:07) High-Stakes Use Cases for Speed
(09:49) When Fast Tokens Become the Norm
(13:01) What Comes Next for General Compute
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Note: This podcast is not investment, legal, or tax advice, and is intended for informational and entertainment purposes only. Hosts and guests may hold positions in the companies and securities discussed; do your own research before acting on anything you hear.
