Field Trainable Neuromorphic Chip

Real Artificial Intelligence • Practical Deep Learning  • from Sensors to Servers

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NeuroMem for
Next Gen Wearables

Learn normal behavior & conditions • Classify via context awareness • Detect with multiple sensors

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NeuroMem for
Next Gen Cameras, Drones, & Robots

Identify people and objects • Adaptive learning as target changes • Find new and different events

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NeuroMem for
Next Gen Industrial Sensors

Learn, classify & detect anomalies • Adapts to production changes • Reduce human inspection • Improve quality throughput

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It's Trainable

Learn on the chip, or load models previously learned and saved by the same or other chip

It's Real Time

Recognize patterns in micro-seconds regardless of the number of models stored in the neurons.

It's Energy Efficient

100,000 recognitions per second for milliWatts per 1,000 models stored in the neurons

It's Available NOW

Available on  ASICs, SOCs, and FPGAs and can be evaluated on a variety of platforms

GV Company News

nepes and GV to manufacture a new NeuroMem WCSP chip

nepes, leader in advanced semiconductor assembly and packaging technologies, and General Vision (GV), leader in the design of digital neural network and low-power AI components, have signed an agreement to develop and manufacture a new wafer chip-scale packaged (WCSP)...

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New CurieNeurons Kit from Maker Collider

Maker Collider is introducing its CurieNeurons Kit, an easy-to-use tool for makers of all levels who want to have a shot at building artificial intelligence related IoT projects. It enables users to build smart hardware capable of pattern learning and classification...

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Featured Products


Design IoT applications and smart non-connected appliances integrating autonomous pattern learning and recognition with 1024 silicon neurons. Easy to program through the Arduino IDE, Eclipse or else, the BrainCard can be interfaced to a wealth of sensors and actuators.


Develop applications which can learn and classify patterns at high speed whether they come from text, network packets, images, audio signal, biosensors, and more. The expandable network of 4096 silicon neurons can receive patterns from the USB port or directly from the reconfigurable on-board FPGA.