Building Fixed HW Implementations of Neural Networks (Yale, Cornell et al.)


Researchers from Yale University, Cornell University, Boston University, and NTT Research have published “Physical Foundation Models: Fixed hardware implementations of large-scale neural networks”. Abstract "Foundation models are deep neural networks (such as GPT-5, Gemini~3, and Opus~4) trained on large datasets that can perform diverse downstream tasks -- text and code generation, q... » read more

AI Goes Ultra Low Power — Part 1


Based on the concept of the new Federal Agency for Jump Innovations (PSRIN-D), the BMBF initiated three pilot innovation competitions. One of them presented the participants with the task of developing the most energy-efficient AI system possible as a hardware implementation on an ASIC or FPGA. With this, a stack of hundreds of two-minute long ECG signals should be analyzed with a minimum of en... » read more