November 16, 2020 
The research community has been talking about AI for over 50 years now. It’s been around for decades, but it’s only starting maybe 10 years ago that computers became fast enough and we had enough data that modern technology, specifically neural networks and deep learning, started to work really, really well. As this started to enter, the early adopters of this new wave of technology, including Google, [Baidu 00:00:29], Facebook, Microsoft, and so on, we started to see a lot of exciting use cases. Since then, building on the initial rise, which were created in large part by the rise of data and compute, we now have additional forces making this more possible. We have the rise of talent. One, more people are taking online courses, university courses, so more and more people are able to do AI now than ever before.
We have the rise of open source tools. Several months ago, I attended a outdoor affair where I met this kid that had traveled from India to show his robot in the Maker Fair, build a little agriculture robot using computer vision. I asked him how old he is, and he said “I’m 12 years old.” The rise of open source tools is now enabling people around the world to do projects that just a few years ago would have been great Stanford PhD thesis.
So the rise of data, compute, talent, tools, the sheer volume of knowledge that’s created and shared freely online, all of these are driving the rise of AI. With the use cases, the sometimes very valuable use cases, coming in to pull more resources onto this, I think the trend of rising AI still has a long way to go.
