A chip 10,000x more energy efficient than GPU -- Trevor McCourt, Extropic скачать в хорошем качестве

A chip 10,000x more energy efficient than GPU -- Trevor McCourt, Extropic

For AI to process all media we interact with daily, we need hundreds of thousands of today’s energy supply. GPUs get about 2x more energy efficiency every two years, and hyperscalers adding more GPUs won't meet demand. Startups building new compute paradigms need 1,000–10,000× to win long-term. @trevormccrt1 shares how Extropic is doing it - it uses thermal noise in transistors to build a probabilistic chip that samples from distributions (similar to how transformers do it) and generates random numbers at least 10,000x more efficiently than pseudo number generators like CPUs. Their prototype shows 4 orders of magnitude more efficiency than GPU-based algorithms like GANs and VAEs. They think they can go much further. If you’re interested in probabilistic HW, feel free to reach out to us or Trevor directly.