The video discusses the evolution and implications of AI hardware. It notes Moore’s Law is still applicable today, albeit with implications for power consumption. The number of transistors on a chip is increasing, but individual cores don’t run faster, necessitating more parallel cores and advanced functions like tensor operations. This results in more power-hungry and warmth-producing chips, requiring novel cooling solutions. Power issues and the increasing need for parallel processing are highlighted.
The video also describes Nvidia’s strong position in the AI revolution due to its mature software ecosystem. However, many big companies and clouds like Google and Amazon are developing their own AI-accelerators, making the market more competitive. It suggests that despite a strong supply-demand dynamic, innovations and competition will reshape the future of AI hardware.
