A couple of weeks ago, this column wrote 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. The realization that the war in AI is not just about the data, but also the ability to process it effectively through new hardware, has not been lost on the large tech giants. Microsoft, Amazon, Google and Facebook are huge buyers of hardware, and each has toyed with many start-ups such as AlphaICs to see whether a new class of chip would be required to handle AI tasks. Facebook has said in the past that it might try to design new types of chips for its own use.

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.