Extopic, an advanced start-up of a new type of Chip-based computer that uses proquabilistic chips, has produced its first working hardware and proof that the advanced processes will tackle tasks useful in artificial intelligence and scientific research.
The launch chips work in a different way than the chips from Nvidia, AMD, and others, and they promise to be thousands of times more efficient when they go up. With AI companies pouring billions of dollars into building dates, a completely new approach could provide a cost-effective alternative to conventional chip programming.
Extopic calls its processors procermodynamic samplers, or tsus, as opposed to central processing units (CPUS) or graphics processing units (GPUS). Tsus uses silicon components to move thermodynamic Electron dynamics, shaping them into models of possibilities for various complex systems, such as weather, or AI models capable of generating images, text, or videos.
The first extopic chip has now been shared with several partners including AI Frontier labs, Climate Modeling Startups, and several government representatives. (Extopic declined to provide names.)
“This allows all kinds of developers to kick the tires, who find disagreements in the world of technology like polosophy with opposites called Beff Jeff and E / Acc before founding the startup. Verdon and his Cofounder Trever McCourt, CTO of Extopic, who previously worked on quantum computers at Google before following their computer path.
One of those now testing the new hardware is Johan Mathe, CEO of Atmo, a start-up that uses AI prediction at a higher resolution than is often the case for clients including the Department of Defense. Mathe says that the extopic chips should enable you to calculate the odds of different weather conditions much more accurately than is usually the case.
Extopic also releases software called trhml that makes it possible to synchronize the behavior of the extopic chip to the GPU. Mathe has used this software and the real chip. “I was able to run a few p-bits and see that they behave as they should,” Mathe said.
The company’s hardware, called XTR-0, consists of a Field Programmable Gate Array (FPGA) chip, which can be reprogrammed with different functions, combined with its first chip, X-0, each of which contains a few qugits.
Instead of the usual bits that correspond to 1 or 0, the new chip includes bits of p-bits or p-bits that model is uncertain. Although limited in scale, the new chip shows the power of the company’s new approach.
“We have the first machine learning machine that works much better than matrix multiplication,” McCourt said. “The question is how do you build something at the scale of chatgpt or midjourney.”
