With software becoming more important than ever, hardware is following suit.
As the world generates more data, unlocking the full potential of AI means a constant need for faster and more resilient hardware.
But how much does this all really cost? In this final segment of our AI hardware series, we tackle that question head on.
Be sure to check part 1 and 2, where we explore the emerging architectures and the momentous competition for AI hardware.
Topics Covered:
00:00 – The cost of compute
02:20 – Is this sustainable?
03:23 – The cost to train a model
05:39 – Computation requirements
09:05 – The relationship between compute, capital, and technology
11:15 – GPT4 commenting on the technology with help from ElevenLabs
Resources:
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