We may be in an AI bubble, but a bubble of over exuberance, not hype. i.e. the 2000 dot com bubble was not wrong about the future potential of the Internet, it was just wrong about the speed.

So it is with AI. We think we’re doing better than we are, because AI has evolved so quickly since its breakout in 2017.

We are not, however, in a bubble like the semi mythical tulip bulb bubble, which is now mostly fictionalised as a story rather than understood as reality.

An important, and often missed point in this evolution is that we are moving from an era of general computing (the CPU) to specialist computing, AI (GPU), Quantum and ASIC compute such as Bitcoin mining. AI has yet to travel this journey, still mostly relying on GPUs for its compute. 

Bitcoin is a good lesson for us here. Bitcoin mining moved from CPU mining at first, to GPU mining and now almost 100% of it is done on specialist ASICs. 

AI has made some moves into Application Specific Integrated Circuit, chip sets such as Google’s TPUs (Tensor Processing Units), Fujitsu’s DLU (Deep Learning Unit), Intel’s AI ASICs, and specialised chips like Habana Labs Gaudi and Cerebras Wafer Scale Engine. But we have yet to see a dominant general purpose GPU beating AI ASIC. This will come and it may not come from Nvidia.