Scalable Ultra-Low Variation Analog-Time Neural Network (S-UATN) Accelerator W912CG-25-C-A001

An award has been issued for the Scalable Ultra-Low Variation Analog-Time Neural Network (S-UATN) Accelerator, with a total award of $3,809,997 to Northwestern University. The project involves developing a scalable accelerator for analog-time neural networks that emphasizes ultra-low variation.

This is an award notice, not a solicitation, so there are no bidding opportunities or procurement requirements described in this notice. No specific bid constraints (e.g., brand-name requirements, certifications, or site visits) are listed. Interested businesses should monitor for future opportunities if they want to bid on similar work.