[londons_explore]

This is how I explain AI to clients...

Think of your best employee. You show them how to operate the videoconferencing system, and that's done.

Now think of your worst employee. You have to show them how to operate the videoconferencing system 3 times because they keep getting it wrong or not understanding how to start a meeting. Eventually, when they've got the hang of it, they're fine too.

AI is like an employee that needs to be shown how to do it a million times. Unless you have the time or the data to show the AI how to do a simple task millions of distinct times, or someone else has already done it, AI can't help you.

Here deepmind is just showing that for slightly more complex tasks, that ~1e6 factor turns to ~1e11...

[antpls]

That's only the current state of the art however. The goal is transfer learning, meaning that when the AI learns something somewhere, it will improve its knowledge on other taks too.

A better analogy would be a baby and an adult. The adult is full of past experiences and can use that experience to learn some other tasks faster.

Currently, our AI technology isn't even at the "baby" stage, as it is not able to transfer knowledge between arbitrary tasks. This is an active research domain.

[AndrewKemendo]

I think that's a really cogent explanation and fits a narrative that I've seen work when I try to tell non-technical leaders why they probably aren't ready to do ML/DL.