Tech giants chart different courses for artificial intelligence

Until now, most firms have been using the Graphical Processing Unit (GPU) architecture, originally developed for video games by firms such as Nvidia, to build out their Artificial Intelligence (AI) programmes. The GPU is much more capable of handling voluminous data than the humble Central Processing Unit (CPU) that is at the heart of most computers that you and I are familiar with. A couple of weeks ago, I wrote in this column about a new hardware chip design for AI, and referenced a start-up firm called AlphaICs, which counts the renowned Vinod Dham among its founders. AlphaICs is trying to redefine the type of chip used for AI applications by designing a chip among a new class of processors called Tensor Processing Units (TPUs) that allow for several more pieces of data to be simultaneously processed on their chips. Hungry AI monster programmes need to crunch through enormous data stores in order to be able to continuously "learn", and the hope is that this new class of TPU chips, which are themselves an extension of GPUs, will be sufficient to handle the vast amount of data flying in from various devices that connect to the Internet.