What’s next? Human brain-scale AI Human brain-scale computing is now looming on the horizon, and it could change your life more than electricity.

Funded by the Slovakian government using funds allocated by the EU, the I4DI consortium is behind the initiative to build a 64 AI exaflop machine (that’s 64 billion, billion AI operations per second) on our platform by the end of 2022. This will enable Slovakia and the EU to deliver for the first time in the history of humanity, a human brain-scale AI supercomputer. Meanwhile, almost a dozen other countries are watching this project closely, with interest in replicating this supercomputer in their own countries.

There are multiple approaches to achieve human brain-like AI. These include machine learning, spiking neural networks like SpiNNaker, neuromorphic computing, bio AI, explainable AI and general AI. Multiple AI approaches require universal supercomputers with universal processors for humanity to deliver human brain-scale AI.

For example, the EU’s 1 billion euro Human Brain Project is a large, 10-year scientific research effort, and its goal is to provide the infrastructure tools to enable researchers across Europe to conduct research in the fields of neuroscience, computing and brain-related medicine.

Retired Manchester University professor Steve Furber, the inventor of the ubiquitous ARM processor and a leading researcher on the Human Brain Project, has been using Spiking Neural Nets to model high-level brain functionality.

AI is having a rapidly increasing impact on all of our lives, but there is still a great deal to learn from biology if we are to realize the full potential of AI in the future.

Steve Furber

The SpiNNaker machine, made up of 1 million ARM processors, is designed to mimic human brain functions and has modelled a mouse’s brain functionality in real time. In order to model the functionality of a human brain, it will take 1,000 times more computational power.

There were also experiments by IBM in 2009 in which it used 147,456 processors and 144 terabytes of DRAM at NNSA’s Lawrence Livermore National Lab and claimed to simulate a neural network the size of a cat brain — which is 4.5% of human brain capacity and runs 643 times slower than real time. Its model would require a machine with 23 times more capacity and be 643 times faster to approach human brain-scale AI.

Europe is dedicated to becoming an AI powerhouse. The EU, which uses 30% of the world’s computational resources, controls only 5% of those resources. To achieve technological sovereignty, the EU is now funding projects aimed at providing indigenous computational resources for the EU to move into an AI-intensive future.

Germany and France, along with other EU participants, have created a 7 billion euro HPC project and a 10 billion euro EuroCloud project — the goal of which is to design the next generation of a federated European “cloud” by specifying common requirements for an EU data infrastructure specified by Gaia-X.

While Europe is stepping into the AI supercomputing arena with significantly increased funding for several key projects, the U.S. is working on its own exascale machine. El Capitan, DOE’s $600 million, two-exaflop machine, is slated to come online at Lawrence Livermore Labs in 2023.

Dominance in the field of AI is not only crucial to GDP growth and our quality of life, but it’s also a national security priority. The U.S., China, Russia and the EU are in an AI arms race to see who will dominate the AI landscape.

Any way you slice it, the explosive growth in AI technology means that consumers, corporations and government agencies will soon be able to exploit highly advanced AI systems in order to create life experiences that we can only dream of today. Human brain-scale computing is now looming on the horizon, and it could change your life more than electricity.