Princeton Spinout EnCharge AI Raises $21.7M in Series A Funding

EnCharge AI, a company building advanced computers for AI at the Edge, has raised $21.7 million in series A financing. EnCharge will leverage the funding to further develop and commercialize its semiconductor hardware and software stack.

EnCharge’s charge-based in-memory computing technology was born out of the Defense Advanced Research Projects Agency- and Department of Defense-funded R&D. In the six years since, the company has completed demonstrations of AI performance with orders-of-magnitud-higher compute efficiency and density than has been achieved by both best-in-class digital accelerators, such as GPUs or TPUs, according to EnCharge, as well as recent concepts for beyond-digital accelerators, based on optical or analog computing. Several generations of test chips with end-to-end programmable model execution capability have been demonstrated. EnCharge is targeting applications that have been limited by power and energy requirements and space constraints including automotive sensing, advanced manufacturing, smart retail, smart warehouses and logistics, industrial robotics, and drones, the company said.

EnCharge reported that its test chips and hardware can achieve over 150 TOPS/W for 8-b compute.
The company said that it will will deliver platforms that provide over 20× higher performance per Watt and over 14× higher performance per dollar compared to best-in-class digital AI accelerators implemented in the most advanced technology nodes.

Following this series A round, EnCharge is positioned to develop products to engage with customer applications in production at the forefront of AI, said Naveen Verma, CEO and co-founder of EnCharge AI. The foundational technology for EnCharge’s products was developed at Princeton University, where Verma is a professor of electrical and computer engineering.