Can we afford AI?

Of all the concerns surrounding artificial intelligence these days -- and no, I don't mean evil robot overlords, but more mundane things like job replacement and security -- perhaps none is more overlooked than cost. This is understandable, considering AI has the potential to lower the cost of doing business in so many ways. But AI is not only expensive to acquire and deploy, it also requires a substantial amount of compute power, storage, and energy to produce worthwhile returns. Back in 2019, AI pioneer Elliot Turner estimated that training the XLNet natural language system could cost upwards of $245,000 – roughly 512 TPUs running at full capacity for 60 straight hours. And there is no guarantee it will produce usable results.