Name: 「モラベックのパラドックス」って何？5段階のレベルで説明 | 5 Levels | WIRED jp
Uploaded: 2025-02-22T10:10:26.000Z
Duration: 19 min 35 s
Description: VoiceTubeの動画で発音を聞きながら英語表現を覚えよう！学べる英語：

Today, I've been challenged to explain a topic in five levels of difficulty.

Today, we're talking about Moravec's Paradox, which says that the things that are really, really easy and second nature for humans are actually really difficult to program into AI systems and robots.

It's an important topic because it means that when we program robots, some of the really basic stuff that we take for granted is actually quite difficult.

Today, we'll talk a little bit about a concept called Moravec's Paradox.

Something that explains what's hard and what's easy for a robot.

If it's this way, then it's easy, but if it's this way, you need to balance it.

It turns out that stacking these two cups, it's actually really hard for robots to do that.

So let's think about how we might have a robot stack these two cups.

You could program the robot to move its hand right here and then program the robot to close its hand around the cup and then program the robot to move over here and open its hand.

That seemed pretty simple for the robot to do.

Do you think the robot would still be able to stack the cups?

So we program the robot to move to the same exact position as before.

When we gave it instructions, did we tell it to look at where the cup was or did we tell it to just move over here?

So Moravec's paradox is something that means that these really simple things like stacking cups is really, really hard for robots, even though it's really easy for us, while robots are actually really good at really complicated and really difficult things.

Think about the task of multiplying two really big numbers together.

Does that seem like a hard task or an easy task?

You're good at multiplying big numbers together?

But it's actually really easy for a computer to do that.

So how fast were you able to stack the two cups?

It took me like a couple of days when I learned how to stack cups.

Yeah, so it took you a couple of days when you learned how to stack cups, but before that, you already knew how to grasp objects, right?

And so you could use that when you were learning to stack cups.

We're trying to be inspired by how humans learn to do tasks to allow robots to do the same kind of things that are very simple for people, like stacking cups.

We want robots to be able to do something like that too.

Have you heard of something called Moravec's paradox?

Typically, you would think that things that are easy for humans are also easy for robots and computers to do, and things that are hard for humans should also be hard for robots and humans to do, but it turns out that it's actually the opposite.

So I have a penny in my hand, and I'd like you to pick it up with your right hand and put it into your left hand.

We're gonna make this a little bit harder now.

So can you put these on, and we'll try to do the same thing again with your eyes closed.

Let's try that one more time and see if you can do any better.

Yeah, so with a bit more practice, you're able to figure it out.

When it fell on the ground, how did you know to pick it up off the ground?

So when a robot tries to do something like pick up an object, not only do you need to program exactly what the motors should do, the robot also needs to be able to see where the object is.

And this is what's called a perception action loop in robotics.

So if the object moves, the robot can then adapt what it's doing and change what it's doing to successfully pick up the object.

It's really important for robots to be able to leverage not just the past hour of experience, but also ideally many years of experience in order to do the kinds of things that you did.

It's kind of hard for me to understand why robots can do all these crazy calculations, but they can't do all the simple stuff.

In order to survive, we need to pick up objects and everything.

Basically, many, many billions of years of evolution actually created humans and the ability to manipulate objects like that.

So it actually turns out that things that are really basic for us are actually just really complex tasks in general.

So in reinforcement learning, the robot tries the task and then it gets some sort of reinforcement, some sort of feedback, similar to how you might train a dog.

So it won't necessarily know itself, especially on the first few tries, but it's trying to figure out what the task is even.

Does a robot see how we see or does it just see a program or something?

We give robots a camera and the camera produces this array of numbers.

Basically, each pixel has three different numbers, one for R, for G, and for B.

And so the robot sees this really massive set of numbers and it has to be able to figure out from that massive set of numbers what is in the world.

There is a number of different ways to have the robot see, but we use a technique called neural networks that tries to take in those big numbers and form representations of the objects in the world and where those objects are.

If you program the robot to follow exact motions and follow a very specific program, then it won't go off that program.

But if something unexpected happens that the program wasn't designed to handle, then the robot might go off course.

Do you think robots will take over the world?

I think that robotics is really, really hard.

Having robots do even really basic stuff like pick up objects is really, really hard.

So if they do take over the world, I think it'll be a very, very, very, very long time from now.

So today we'll talk a bit about robotics and machine learning and artificial intelligence.

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「モラベックのパラドックス」って何？5段階のレベルで説明 | 5 Levels | WIRED jp

stuff

perspective

assume

perception