Part 7/15:
Cutress argues that while other players—including AMD with their MI series and startups like Cerebrus—are innovating, they are mostly targeting niche markets or building specialized hardware for specific use cases. Nvidia’s platform remains the generalized industry standard, especially for large-scale training and inference.
The Evolving Nature of AI Workloads and Hardware Needs
One of the core discussions revolves around training versus inference, two fundamental AI computing tasks:
- Training involves processing enormous datasets through complex models to develop intelligent systems. This is power-intensive and demands massive memory bandwidth, especially with large models like GPT-6 and GPT-7.