It’s a dual-core, RISC-V chip running at 400MHz. There’s 6 MB of SRAM on the CPU, and there’s 2MB for convolutional neural network acceleration. There is, apparently, WiFi on some versions.

Penn Engineers have developed the first programmable chip that can train nonlinear neural networks using light — a breakthrough that could dramatically speed up AI training, reduce energy use and even ...

Penn Engineers have developed the first programmable chip that can train nonlinear neural networks using light—a breakthrough ...

The 'Ironwood' chip marks a major shift in focus for Google, as performance and efficiency are taking a backseat.

Co-fonder and CTO, Paul Masters, described a novel way to arrange the elements of a chip to do both machine learning "training" -- where the neural network is developed -- as well as "inference ...

For now, the company is selling the device as a way to train "biological AI," meaning neural networks that rely on actual neurons. In other words, the neurons can be "taught" via the silicon chip.

Why it matters: The achievement changes how scientists can study brain connectivity, enabling unprecedented insights into neural networks that ... a sophisticated CMOS chip that introduces several ...

Intel is firing back at Nvidia's growing prominence in artificial intelligence with the launch of its Nervana Neural Network processors ... NNP-T1000 and NNP-I1000 chips for deep learning training ...

This will showcase the fast and lightweight unsupervised live learning capability of the spiking neural network (SNN) and the Akida neuromorphic chip, which takes much less data than a traditional ...