Photonic-Assisted Hardware for Reservoir Computing (BRAIN)

We live in a complex world where we need to predict the evolution of large, nonlinear, dynamic systems; everything from the human brain to climate dynamics, the world economy, and the spread of diseases.

Hence, the ability to process large amounts of data is crucial; a development that is reinforced by the fact that more and more smart gadgets are being integrated into our daily lives.

This will require the use of artificial intelligence even in the areas where humans today still have an advantage over digital computers.

Advanced learning models, better algorithms, and higher available computing power need to be developed for applications such as self-driving cars, autonomous robotics, detection of fake news, prediction of pandemics, and so on. Reservoir Computing is a machine learning algorithm that mimics the way the human brain works.

It can be used to solve the “hardest of the hard” computing problems, such as forecasting the evolution of dynamical systems that change over time.

It has a promise to work a million times faster, with significantly fewer computing resources and less data input needed. The BRAIN project aims to develop photonic hardware tailored for Reservoir Computing.

Such analog information processing with light has the potential to simultaneously achieve ultra-high computer speed and high energy efficiency, which will be required for future applications in artificial intelligence.