It's inevitable ...

It's inevitable. AI now learns on its own without human intervention, which means, in time, general intelligence AI becomes the start point to super intelligence AI, Timeframe, unknown but ... as Agent Smith said to Neo, Its Invitable. To whit ...

The new system, which DeepMind is calling MuZero, is based in part on DeepMind's work with the AlphaZero AI, which taught itself to master rule-based games like chess and Go. But MuZero also adds a new twist that makes it substantially more flexible.

That twist is called "model-based reinforcement learning." In a system that uses this approach, the software uses what it can see of a game to build an internal model of the game state. Critically, that state isn't prestructured based on any understanding of the game—the AI is able to have a lot of flexibility regarding what information is or is not included in it. The reinforcement learning part of things refers to the training process, which allows the AI to learn how to recognize when the model it's using is both accurate and contains the information it needs to make decisions.

In essence, this is how we solve problems ... Observe, Orient, Decide, Act.

But MuZero also excelled at a panel of Atari games, something that had previously required a completely different AI approach. Compared to the previous best algorithm, which doesn't use an internal model at all, MuZero had a higher mean and median score in 42 out of the 57 games tested. So, while there are still some circumstances where it lags behind, it's now made model-based AI's competitive in these games, while maintaining its ability to handle rule-based games like chess and Go.

Overall, this is an impressive achievement and an indication of how AIs are growing in sophistication. A few years back, training AIs at just one task, like recognizing a cat in photos, was an accomplishment. But now, we're able to train multiple aspects of an AI at the same time—here, the algorithm that created the model, the one that chose the move, and the one that predicted future rewards were all trained simultaneously.

Partly, that's the product of the availability of greater processing power, that makes playing millions of games of chess possible. But partly it's a recognition that this is what we need to do if an AI is ever going to be flexible enough to master multiple, distantly related tasks.