With this focus, the startup has developed Sohu, a specialized ASIC chip designed exclusively ... machine learning models like Convolutional Neural Networks (CNNs), Recurrent Neural Networks ...

Examples like Intel's Loihi chips tend to get competitive performance out of far lower clock speeds and energy use, but they ...

This component combines photonics with traditional computing to keep all neural network processing on the chip. At the beginning of each calculation, MIT's experimental system encodes data into ...

The presentation ends with a demonstration of BrainChip’s Akida™ neural processor IP, enabling high performance and ultra-low power on-chip inference and learning and MosChip’s ASIC platform for smart ...

Kneron NPU IP Series are neural network processors that have been designed ... low-cost and low-power processor ideal for integration into ASIC and/or FPGA designs. It offers similar performance to ...

If they do an ASIC, they should be able to adapt it ... We believe it is a red herring that you need an array of MACs to do neural network processing. If you think about the computation the neural ...

Quadric’s architecture delivers machine learning (ML) inference, but, unlike other neural network accelerators ... without the need for a companion processor paired with the NPU. Target applications ...

"This ASIC was purposefully designed with distributed ... more efficient inference compute with the Intel Nervana Neural Network Processor for inference and to extend support for our state-of ...

Activation functions play a critical role in AI inference, helping to ferret out nonlinear behaviors in AI models. This makes them an integral part of any neural network, but nonlinear functions can ...

A month after Intel made a big splash about its new Nervana neural network processors, the semiconductor giant announced it has acquired Habana Labs, a startup making artificial intelligence chips ...