AI Secures $100M to Advance Energy-Efficient AI Chips

The startup's analog in-memory computing chips promise to dramatically reduce energy consumption and costs for AI applications.

EnCharge AI raised $100 million in a Series B funding round led by Tiger Global, with participation from investors including Samsung Ventures, Foxconn, and In-Q-Tel.
The company's analog in-memory computing chips claim to use up to 20 times less energy than leading AI chips, aiming to address growing energy demands from AI data centers.
EnCharge plans to bring its AI accelerator chips to market later this year, focusing on deployment in client computing and edge devices.
The chips process AI data directly on devices, reducing reliance on cloud-based data centers, lowering latency, and cutting costs.
EnCharge's technology builds on research from Princeton University and has received support from DARPA, the Department of Defense, and semiconductor manufacturer TSMC.