By using a special chip design and software, EnCharge AI chips work by computing data directly in the memory on the chip
Born at a Princeton University lab, EnCharge AI, a chip startup, raised $21.7 million as it looks to commercialize its computing technology that is designed to run artificial intelligence applications more efficiently, the startup said on Wednesday.
Naveen Verma, CEO and co-founder of EnCharge AI and a professor of electrical and computer engineering at Princeton, without giving a timeline for the product launch, said the startup’s first products will be cards that can be easily slotted into server racks for companies to run AI applications.
By using a special chip design and software, EnCharge AI chips work by computing data directly in the memory on the chip. More efficient computing is the key as AI models become more diverse and larger, said Verma, and bottlenecks are caused in computing, slowing things down by the traditional way of moving data in and out of memory.
The company said that the technology was originally funded by the U.S. Department of Defense’s Defense Advanced Research Projects Agency (DARPA) and R&D was funded by the Department of Defense. DARPA, which works on weapons, is credited with creating the internet and runs public contests for human-looking robots and self-driving cars.
To run AI applications, the chips will first be used in factories, warehouses and retail spaces, said Verma. He said for now they will be focused on doing inference work – for example, identifying if something is a dog or a cat rather than training a machine to learn what a dog or a cat is.
EnCharge AI said the latest funding round was led by Anzu Partners with participation from AlleyCorp, Scout Ventures, Silicon Catalyst Angels, Schams Ventures, E14 Fund and Alumni Ventures.
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