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A Deep Dive on AI Inference Startups - by Kevin Zhang

eastwind.substack.com · 2,589 words · saved by 1 readers

In my last post, Investing in the Age of Generative AI, I presented a framework for investing in Generative AI startups. One thing I highlighted was the heightened VC interest in “picks and shovels” startups. These companies range from model fine-tuning, to observability, to AI “abstraction” (e.g. AI inference as a service). The bet here is that as startups and enterprises add AI to their product offerings, they might be unwilling or unable to build these capabilities in-house, and would prefer a buy vs. build approach. In this post, I conduct a deep dive on AaaS (AI-as-a-Service) startups, specifically focusing on AI inference startups (see the red box below). I’ll cover the following: Why there’s even a need for AI inference abstraction The convergence of developer experience, performance, and price among inference abstraction platforms implies rapid commoditization The brutal competitive dynamics and the fact that the current available TAM is actually highly constrained What an inve

A Deep Dive on AI Inference Startups Kevin Zhang Jul 10, 2024 107 11 12 Share In my last post, Investing in the Age of Generative AI , I presented a framework for investing in Generative AI startups. One thing I highlighted was the heightened VC interest in “picks and shovels” startups. These companies range from model fine-tuning, to observability, to AI “abstraction” (e.g. AI inference as a service). The bet here is that as startups and enterprises add AI to their product offerings, they might be unwilling or unable to build these capabilities in-house, and would prefer a buy vs. build appro

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