Neuromorphic challenge to Nvidia?

With today's news that Nvidia has become the world’s most valuable company, it is clear that there is huge level of interest and investment in future computing technologies. Nvidia's historical focus on graphics processing has left it well placed to capitalise on the demands of artificial intelligence (AI) algorithms for highly parallel computing architectures. Power consumption remains, however, a major challenge for all providers of AI hardware.

Alternative computer architectures are also receiving significant interest, with the aim being to provide powerful computing performance, but without the high power consumption associated with traditional computing.

As highlighted in this article from the BBC, a dramatically different approach takes inspiration from the brain. In neuromorphic computing, electronic devices imitate neurons and synapses, and are interconnected in a way that resembles the electrical network of the brain. The approach itself has been a research topic for many years. SpiNNaker, a technology platform that has been developed at the University of Manchester, is an ARM-based processor platform optimized for the simulation of spiking neural networks. Companies, such as SpiNNcloud Systems, are now integrating this core technology into practical solutions in the form of neuromorphic supercomputers.

While the advance of AI algorithms into ever-expanding areas of daily life is widely reported, it can also be understood that these advances are enabled by the hardware innovations of companies such as Nvidia and SpiNNcloud, which innovations will undoubtedly be protected by patents. It remains to be seen whether Nvidia's approach, the neuromorphic alternatives, or some other computing technology altogether, will come to dominate the future of AI computing.