The great step of artificial intelligence: use what you learned in one task for the next

Shortly after we told you how robots learn by reinforcement, imitation and deep learning, there was a expected news in the world of artificial intelligence: DeepMind, the AI of Google, I could already use what I learned from one task and take it to another.

Until now, AIs have broken records by squeezing to the maximum a series of rules or norms in a specific field, but it is impossible to bring the gains from one application to another.DeepMind can do so thanks to a mechanism called consolidation elastic weight .AI now have memory , or the beginning of one.

AI and learning

Without repeating ourselves in what we have already said about reinforcement, imitation or profound learning, we can summarize that until now artificial intelligences have learned as humans do in the early stages of life .And they have done it in watertight compartments without any permeability.

To understand it, let's think of a baby crawling on the floor and whose goal is to reach a bottle.Being a human, it already has a brain as a series that allows deep learning , of course.But even if you have reached the coveted prize ( reinforcement learning ) ten times before, and even if you have optimized your crawling algorithm by looking at your parents ( learning by imitation ), you will not know how to open the bottle if you have never tried.For the baby, the bottle will be a new problem with new rules.

That was the state of the art of artificial intelligence until March 2017: he knows how to crawl but that doesn't help him open the bottle.What he learned by solving each problem didn't help them for anything.Next problem: With each new challenge you had to return to the starting position, fail, iterate, fail again, take a different path, fail, try again...

The great step of artificial intelligence: use what you learned in one task for the next

But now artificial intelligence has one more human tool, the elastic weight consolidation (EWC), which allows you to go further in your learning.Or, at least, reach that away in less time and using fewer resources.What is already an achievement in itself.

Elastic weight consolidation, what is that?

Let's do a quick review through the great milestones of artificial intelligence in the discipline "beating human beings." No, we do not talk about Cylons seeing how humans are inside , but of board games that are now AI domain:

1990: AI Chinook is second to the ladies against Marion Tinsley.

1995: after his death, Chinook comes to mind still unbeatable.

1997: the AI DeepBlue wins Kasparov to chess, and without the option of excuses.Logistello defeats Murakami 6 to 0 in the same year.

2016: AI AlphaGo defeats the game go to Lee Sedol.

2017: AI Libratus wins poker without limit Texas Hold'em.

Yes, the news could be that «artificial intelligences are leaving us without specialized jobs and without board games», but there is something else.

Until now, artificial intelligences have had to be designed expressly to win each of these games, however, we can say with certain certainty that Go Sedol himself could become a good chess player.of AI, it is not necessary for your parents to generate another Lee for it.

That that humans had but not AI (among other elements) is the elastic weight consolidator (EWC): a mechanism that rescues fragments of code used in applications similar to applications present .

In the case of games, the EWC is that part of the human software that sneaks us: "Hey! Have you noticed that the chess pawn moves in a similar way to the ladies?" It is the same type of algorithm that whispers to babies: «Hey, you, little one, the legs that you have used to sweep the floor help you stand up, and they will work more or less as badly».

The great step of artificial intelligence: use what you learned in one task for the next

As neurologist David Eagleman says, "the human brain is a multipurpose machine." Although AI processors are technically also (the same is solved by one operation than another), their starting software is not.

The EWC of artificial intelligence and the EWC of humans

The elastic weight consolidator is the mechanism that activates the stored memory, even time ago, and uses that prior knowledge to build more knowledge in solving a problem.But even humans have the EWC parameter set very under (except in exceptional cases).

Just as a human uses 10% of his brain (if we used 100% we would not be LUCY, but an epileptic), he usually cannot access 100% of his memory and what he has learned., nobody remembers everything.Reason why many times we find the optimal answer hidden in our memory a long time after having patched a problem with a second solution.

"Ah, it's true, it was like that !", we thought.And we lied to ourselves: "I remember that next time."

Imagine the access to the EWC as a percentage from 0 to 100.A very low elastic weight consolidator, 0.01%, does that the AI or the human does not relate a previous learning with a new problem.A very high one, close to 99.99%, causes it to block or even end up bleeding from the nose, because an elevated EWC would make any process heavy .

The great step of artificial intelligence: use what you learned in one task for the next

"What a clever AI", we could say by looking at the processor power consumption data.Without realizing that you spend all your computing power checking the relationships between the new problem and all the previous problems instead of solving the problem.What is known as Paralysis by analysis , applied to artificial intelligence.

So, are AI more clever now?

Yes and no, at the same time, although rather maybe .It is unlikely that we will reach a consensus, especially considering that it is difficult for us to define words widely used today as intelligence .

If solving the same problem faster with less power is a sign of intelligence, then yes, artificial intelligences are probably at the root of DeepMind more lists .

But, except for television programs, we do not consider a human with quick answers more intelligent (even if they are correct).We say that he has a good memory and, if he is solving a problem, we simply say that it is resolutive.We relate intelligence to speed, and we do not even say that it is wiser.

The elastic weight consolidator mechanism is a system that helps to reach a partly known solution .So at most we could say that AI is more wasted realizing that part of the problem was already solved.

For many, that AI becomes intelligent is a technophobia attack.But according to experts these fears are unfounded.First, because our artificial intelligences are in honeycombs and, second, because the most intelligent thing an AI can do is to pass from humans (and for now they continue to play our arcade when we ask for it).Very intelligent they are not.

Images | iStock/Voyagerix, iStock/IPGGutenbergUKLtd, iStock/IPGGutenbergUKLtd, iStock/solvod

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