“This signal on the oscilloscope may seem simple at first glance, but it demonstrates a key building block for our platform, representing the birth of the world’s first scalable, mass-manufacturable, and energy-efficient probabilistic computing platform,” says Guillaume Verdon, CEO of Extropic and the man behind the wildly popular, provocative, and sometimes controversial online persona Based Beff Jezos.
One of Extropic’s innovations is a way of controlling thermodynamic effects in conventional silicon to perform calculations without extreme cooling. Efforts to compute thermodynamically have traditionally relied on superconducting electronic circuits, but Verdon and his cofounder, Trevor McCourt, are using fluctuations of electric charge in regular silicon instead.
Extropic says its hardware is perfect for running Monte Carlo simulations, a class of computation that involves sampling probabilities that is widely used in areas like finance, biology, and AI. These computations are important for building reasoning models like OpenAI o3 and Gemini 2.0 Flash Thinking from Google.
“The reality is that the most computationally-hungry workloads are Monte Carlo simulations,” Verdon says. “We are not just interested in AI, but also applications in simulations of stochastic systems in high-performance computing at large.”
Extropic’s founders concede that the idea of taking on Nvidia and other chipmakers might seem, on the face of it, absolutely insane. Nvidia’s chips are still the best for training AI, and switching to a completely alien architecture would be costly and time consuming.
But we are at a unique moment when AI companies need so much computer power for AI that they are building datacenters next to nuclear power stations, when nation states are set to spend wild amounts on AI, and when the technology’s environmental impact is only getting worse. Perhaps, given all this, it is more nuts not to try to reinvent how computers work.
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