Chasing the world’s first Brain-on-Chip AI computer

Besides being the most intelligent computing system ever, the brain is also very energy efficient. It uses orders of magnitude less energy than traditional computers, which makes it attractive for future sustainable computing hardware. TU/e researchers led by Regina Luttge and Bert de Vries recognize the revolutionary potential for a hybrid computer consisting of brain cells and silicon microchips, which could be used to solve real world problems such as low-power wearables, IoT devices, and advanced controllers for AI technologies.  

BayesBrain

In other words, the researchers want to build a device where brain cells work with a silicon-based computer to enhance ultra-low power wearables, IoT devices, or controllers with AI technology in the future.

“The unescapable truth is that our modern computers consume too much power, but brain cells use orders of magnitude less power,” explains Luttge. “And with our computing demands increasing, we need more sustainable computing. Studying brain cells in this context offer a potential solution.”

Energy matters

Combining a silicon-based computer with brain cells in BayesBrain is definitely not a publicity stunt. If this approach can be scaled-up, it could have far-reaching consequences for machine learning in the future.

“Right now, the training of some artificial neural networks by DeepMind and Google incurs huge financial and energy costs. On the other hand, the brain uses many orders of magnitude less power to function, but we can’t achieve the same orders of magnitude change with current computers. To attain this, we need a paradigm switch, and hybrid computing involving brain cells could be the answer,” says De Vries.

You can read the full press release here.