The Twenty Minute VC (20VC): Venture Capital | Startup Funding | The Pitch cover image

20VC: Why Google Will Win the AI Arms Race & OpenAI Will Not | NVIDIA vs AMD: Who Wins and Why | The Future of Inference vs Training | The Economics of Compute & Why To Win You Must Have Product, Data & Compute with Steeve Morin @ ZML

The Twenty Minute VC (20VC): Venture Capital | Startup Funding | The Pitch

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Navigating Machine Learning Infrastructure

This chapter explores the distinct infrastructure demands for training versus inference in machine learning, highlighting the resource intensity of training and the efficiency required for inference. It discusses the challenges of compute provisioning and the importance of auto-scaling, along with the financial implications of over-provisioning in the AI industry. Using analogies and anecdotal evidence, the chapter emphasizes the need for scalable solutions and addresses concerns over outdated compute resources amid shifting market behaviors.

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