BigTech companies already dominate in GenAI infrastructure with their cloud services and hardware chips. Microsoft and Google are well-positioned in the US cloud market, while Baidu and Alibaba are well-positioned in China. Their massive supercomputer cloud infrastructure is engineered to run GenAI's complex, expensive, large text, visual, and audio Foundational Models. There are already many developers using their cloud AI API services and tools to build apps, and this trend is expected to accelerate as entrepreneurs rush to address virtually limitless GenAI use cases. Amazon has been quiet on Foundational Models, so a big question is how will they respond. GenAI uses massive amounts of computational power to generate creative outputs.

I originally published a version of this post in June 2016. This update, with the recent news, further confirms some of the assumptions I made back then. The tweet above confirms something we're all quite aware of, which is that there is still a lot to do before we get self driving cars onto our roads. But why is this the case? Aren't these companies the ones with the technical know how and unlimited resources required to make our self-driving car fantasies reality?

What is the time lag from Science Fiction to reality? Arthur C. Clarke wrote about geostationary satellites in 1945 and it became reality 20 years later, but Clarke's work was more grounded in science than the Kubrick classic 2001 featuring the Hal AI computer. That was released in 1968 – 48 years ago. It is such an easy fiction trick to imagine a machine as smart as a human, but the reality of AI has been much harder. It is now getting a lot easier.