NVIDIA’s Growth is Stalling: Why We’re Not Worried

Our 2020 piece on Investing in Artificial General Intelligence talked about the Bugatti of computing – Microsoft’s AI supercomputer which was solely developed for OpenAI. At the time, it was a single system using more than 285,000 CPU cores, 10,000 GPUs, and 400 gigabits per second of network connectivity for each GPU server, making it one of the top five fastest publicly disclosed supercomputers in the world. Just over two years later, ChatGPT emerged from that monster machine and took the world by storm.

Our article proposed a scenario that’s being considered by the world’s greatest minds – the emergence of an artificial super intelligence that will surpass humankind in intelligence and quickly become dangerously intelligent.

Our ability as humans to perform recursive self-improvement suffers from a hardware limitation – the human brain. After we achieve AGI, the only limitation will be how fast the biggest semiconductor manufacturer in the world, NVIDIA, can churn out GPUs.

Credit: Nanalyze

Should that AGI decide to pursue its goal of increasing intelligence by any means, it will then begin to focus on how it can obtain more GPUs as quickly as possible. It may start sending emails directly to Jensen Huang, suggesting that perhaps they begin working more closely together in designing better and more efficient GPUs.

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