Applied Brain Research

Oh, you want to know what we actually do?

At ABR we develop a new kind of AI that exploits spiking in neural networks. Our algorithms and the hardware we use ranges from the conventional (CPUs, GPUs, deep networks, ANNs) to the unconventional (spiking ASICs, FPGAs, adaptive controllers, SNNs). We have deep expertise in using neuromorphic hardware and software to solve AI problems. We have developed a software platform, Nengo, that flexibly combines all these methods to get you the lowest power, fastest speeds, and highest accuracy.

Our story

Want to see some stuff we make?

Nengo

Our flagship suite of software tools to build and simulate large-scale neural systems.

Try it out >

Brain Board

The first and only commercially-available reprogrammable neuromorphic hardware.

See purchase options >

Adaptive Control

Our patented adaptive control method to improve standard industrial control.

Tell me more >

Explore all products

You’re taking this to the next level with how it thinks, how it learns, and how it reacts…the simulated neural networks you’re creating through this can apply to this [robot] – it’s just a great visualization – but of course this applies to thousands of things.

Major players operating in the neuromorphic computing market include IBM Corp.(U.S.), HP Corp. (U.S.), Samsung Electronics Ltd. (South Korea), Intel Corp. (U.S.), HRL Laboratories, LLC (U.S.), General Vision Inc. (U.S.), Applied Brain Research Inc. (U.S.), and BrainChip Holdings Ltd. (U.S.).

The typical CPUs most smartphones use could never handle a system like Siri on the device. But Dr. Chris Eliasmith, a theoretical neuroscientist and co-CEO of Canadian AI startup Applied Brain Research, is confident that a new type of chip is about to change that.

Eliasmith and his team are keenly focused on building tools that would allow a community of programmers to deploy AI algorithms on these new cortical chips.

Spaun […] stands apart from other attempts to simulate a brain, such as the ambitious Blue Brain Project, because it produces complex behaviours with fewer neurons.

The system is explicitly designed for real-world applications. On a five-year timescale, says Boahen, “we envision building fully autonomous robots that interact with their environments in a meaningful way, and operate in real-time while [their brains] consume as much electricity as a cell phone”. Such devices would be much more flexible and adaptive than today’s autonomous robots, and would consume considerably less power.

But the point of Spaun is not to build an artificial brain either. It’s a test-bed for neuroscience—a platform that we can use to understand how the brain works. Does Region X control Function Y? Build it and see if that’s true. If you knock out Region X, will Spaun’s mental abilities suffer in a predictable way? Try it.