Pratica di Shadowing: We're Not Ready for Biocomputing - Impara a parlare inglese con i video

Caricamento...
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In a few seconds I'm going to show you one of the most disturbing things happening in science right now
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and almost no one is talking about it.
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That's why we made this video.
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You're looking at a computer in a laboratory called Cortical Labs.
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It's playing Doom.
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But look closer.
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There's nobody playing it.
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Or actually, there is.
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They just can't get out.
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They are trapped there because this computer is running on living human brain cells And those cells are the ones playing.
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So why would anyone build a computer out of brain cells?
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It basically comes down to power.
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AI uses a massive amount of electricity, and that number keeps going up.
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Amazon investing another $15 billion.
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Meta continuing its massive investments in AI, this time in the form of compute power.
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The computing power it takes to train these models roughly doubles every six months.
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Almost nothing in the real world grows that fast, but you can't build power plants that quickly.
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So there's a growing gap between what AI needs and what we can actually supply, and it keeps getting wider.
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You can see the panic in what the big companies are doing.
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They're going after energy now, not just better software.
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Old nuclear plants that got shut down years ago are being turned back on just to power them.
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Companies are signing deals to lock up huge chunks of the grid years ahead of time.
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It's not really a race for smarter AI anymore.
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It's turning into a race for electricity.
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So a few researchers went a totally different direction.
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They looked at the brain.
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Because the brain figured this out a long time ago.
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Think about what your brain is doing right now and how little it runs on.
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Everything you're thinking runs on about 20 watts.
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We're using whole power plants just to copy a small piece of what your brain does on basically nothing.
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And it learns way better than our machines too.
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To teach a computer what a dog is, you have to show it thousands of photos.
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A little kid sees a dog once or twice and just gets it.
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So how did we get from that to a dish playing Doom?
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It took three steps.
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Back in 2008, researchers grew a sheet of rat neurons and hooked it up to a little robot.
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And the cells actually drove it around.
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It sounds bigger than it was.
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The neurons just sat flat on a grid of electrodes and connected to their neighbors.
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That was pretty much it.
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This was nowhere near a real brain.
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And it wasn't even the first time someone had wired living tissue to a machine.
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One team even did it with the brain of a lamprey.
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The footage always looked a little like a horror movie.
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And from the start, people had one real doubt.
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Were the cells actually driving, or was the computer just taking their random signals and making it look that way?
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Keep that question in mind.
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We're coming back to it.
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The second step came in 2013.
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A scientist named Shinya Yamanaka showed you could reset a grown-up cell all the way back to the start.
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He found four proteins that turn a regular cell into a blank, brand new one.
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And from there, you can turn it into almost anything, including a neuron.
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That was huge.
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It meant you didn't have to take neurons out of a brain anymore.
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You could just take a bit of skin and grow them.
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There was another big step too.
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If you grow neurons on a flat dish, they only connect to the ones right next to them.
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But if you let them grow in 3D, they start to organize on their own.
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They spread out, fold into layers, and form the rough beginnings of real brain regions, kind of like an embryo does.
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One of those tiny balls of tissue is called an organoid.
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Then, in 2022, a company called Cortical Labs put all of this together into something they called DishBrain.
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They grew about 800,000 neurons, part mouse and part human, and taught them to play Pong.
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Two things about this were a big deal.
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First, a dish of cells was actually working toward a goal.
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Second, and this is the weird part, They'd figured out how to teach it.
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They could ask the cells a question and get an answer back.
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You're not supposed to be able to do that to a blob of tissue in a dish.
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So how do you teach a neuron?
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You can't give it a treat.
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So they used a basic fact about neurons.
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They hate chaos.
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If you give them a signal they can't predict, it stresses them out.
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So the setup was simple and kind of mean.
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When they missed the ball, they got hit with scrambled random noise.
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When they hit it back, the signal went calm and steady.
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The neurons have no idea what Pong is.
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They're not playing to win.
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They're just trying to make the chaos stop.
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And they didn't pick that method at random.
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They based it on an idea of the free energy principle.
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Basically, it says every living thing is always trying to avoid surprises and keep its world predictable.
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Because being surprised usually means something's wrong.
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So that urge to calm things down isn't something the scientists added.
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It might be the most basic thing a living cell does.
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But there's a big catch.
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We can grow brain tissue in 3D and we can talk to living neurons.
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We just can't do both at the same time yet.
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So in order to talk to them, DishBrain had to keep the cells flat because the chip that reads them is a flat grid.
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If you put a round organoid on it, you only touch the bottom layer.
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So they had to flatten it out and give up the brain's real shape just to talk to it.
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And remember, this is the crude version.
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Half the design is missing.
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Which brings us to a big new.
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Cortical Labs showed off a computer that runs on brain cells.
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They call it CL1 and it plays Doom.
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This one was grown from about 200,000 human neurons.
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They took skin cells, reset them, turned them into neurons and spread them across a bed of electrodes.
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Then they tied the signals to moving and shooting the same way as before.
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When it did well, the signal stayed calm.
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When it took damage or died, the cells got flooded with chaos.
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And within about a week, it had learned the basics of moving around and shooting.
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I'm not going to pretend to be calm about this, and I don't think you should be either.
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It's amazing.
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And it kind of makes me sick.
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And I think both of those reactions are fair, Because that computer came from a real person.
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It's literally made of human cells.
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I keep imagining what it would be like to be the thing stuck in there, playing the same little piece of game over and over forever,
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not remembering anything before it, not knowing that anything else even exists.
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For these cells, there's nothing else, just the game.
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Are we making a piece of a human being whose whole world is getting shocked inside a violent video game
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just to save some electricity?
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For years, we worried about the opposite thing.
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Humans turning into machines, chips in our heads, that whole idea.
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Almost nobody expected it to happen the other way around.
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But that's kind of what's going on here.
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Now, to be fair, there was a big backlash to all of this.
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And it was kind of fair.
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When Cortical Labs published the Pong word, the title used a heavy word.
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It said the neurons showed sentience.
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Normally, that word means someone's in there having an experience.
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But the scientists meant it in a really narrow, technical way.
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Basically, anyway, the story blew up, and a lot of scientists were angry too.
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About 30 of them signed a letter saying the company had twisted the word just to get headlines
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and oversold the whole thing to help the business.
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Their worry was pretty practical.
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Too much hype leads to backlash and enough backlash could shut down a young field like this.
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And this research really matters.
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Scientists use these same cells to build living models of human diseases.
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They can watch how a disease develops and test drugs on tissue that's way closer to ours than a mouse's.
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That could save real lives and replace a lot of animal testing.
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It would be a real loss if a stunt with Pong and Doom dragged it all down.
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Doom really was kind of a stunt.
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The audience asked for it and it made great marketing.
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But it brings us right back to that doubt from 2008.
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Is the brain really playing or is the computer just cleaning up random noise and making it look good.
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Almost 20 years later, we can finally check.
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The developer behind the demo, who goes by Shun Call, released the code so anyone can read it.
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And what's inside is not just a brain in a box.
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There are three parts.
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First, a normal computer chip running an AI that watches the game and decides when to reward and when to punish.
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Second, the 200,000 human neurons.
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And third, a translator in the middle, passing messages both ways.
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Here's the uncomfortable part.
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Almost all of the actual smarts are on the chip, not in the cells.
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Reading the screen, running the learning, telling a win from a loss, that's all the computer.
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The developer was even worried his AI would get so good it wouldn't need the neurons at all.
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So he ran a simple test.
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He took the cells out and replaced them with pure random noise.
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and the learning just stopped.
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So the neurons are doing something real, even if it's a small part.
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So the truth is somewhere in the middle.
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It's not a brain playing on its own, but the cells aren't just for show either.
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It's mostly a normal computer doing the work, with living cells adding a small but real piece.
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That's where we are today, and here's where I think it goes next.
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I don't think that small biological parts stay small.
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all over are racing to grow this tissue in full 3D and connect to it properly.
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And it's already turning into a business, a huge business.
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A Swiss company called FinalSpark rents out living human neurons over the internet.
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You pay a monthly fee, log in from anywhere in the world and run experiments on 16 tiny human mini-brains that they keep alive in their lab.
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And their whole pitch is the same thing we started with, energy.
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They say these living chips can run on up to a million times less power than a normal one.
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So this weird one-off experiment is basically becoming a product you can subscribe to.
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And I believe, sooner or later, someone's going to connect a full 3D mini-brain and close that last gap.
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But let's go back to that Doom machine for a second.
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Most of the smarts are in the computer, the cells only do a little, so it would be easy to hear that and just ignore it.
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But But being smart was never the scary part here.
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Being smart and being awake are two different things.
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You can be great at solving problems and still not feel anything at all.
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So the real question isn't whether those cells are clever, it's whether anyone's actually in there.
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And it turns out being able to feel might not need a big smart brain at all.
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A renowned neuroscientist, Mark Solms, argues almost the opposite of what we were taught.
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Solmes says feeling isn't something that sits on top of intelligence.
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He thinks it comes first, underneath everything else, and that it comes straight out of the basic drive to stay alive.
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Think about what came first in evolution.
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It wasn't logic or language.
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The earliest living things weren't solving anything.
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They were just doing something much simpler and older, moving toward what kept them alive and away from what didn't.
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So something like feeling was already around long before thinking showed up.
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Now think back to how these cells get trained.
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Chaos when they fail, calm when they succeed.
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That's the free energy principle again.
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That same drive every living thing has to avoid surprise and keep itself steady.
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And if Songs is right, that drive isn't just close to feeling.
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It might be where feeling actually starts.
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So maybe we've had it backwards this whole time.
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We're not slowly building a mind and waiting for it to wake up at the top.
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We might be poking at the exact thing feeling comes from, right at the bottom, from the very first moment we turn the dish on.
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And if something in there did start to feel, we'd probably miss it completely.
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We can barely spot it in each other.
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In 2006, a scientist named Adrian Owen studied a young woman who everyone had given up on.
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They'd called her vegetative.
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He put her in a brain scanner and asked her to imagine playing tennis.
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And her brain lit up exactly like yours would.
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She was completely awake and aware.
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She just couldn't move or speak to show it.
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And a later study found out that about one in four patients written off like that are actually still aware.
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So if we could miss a fully conscious person lying right in front of us, what chance do we have of spotting it in a clump of cells?
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We like to tell ourselves that feeling needs the right parts.
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Pain receptors, certain brain structures, but even that is shaky.
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Insects don't have a visual cortex, and they clearly see, so feeling might run on parts Parts that look nothing like ours, parts we'd never even think to check.
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When the noise in the dish gets too loud, the cells turn their response down like they're trying to block it out.
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Something in pain would do that, but so would something that feels nothing at all.
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Backing away from a bad signal isn't the same as suffering.
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And from the outside, there's no test that can tell the two apart.
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This is what the philosopher David Chalmers called the hard problem.
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We can map every single cell in a brain and still have no idea how it turns into an actual feeling.
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So let me be honest about both sides of this.
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Think about what this research could give us.
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It could help us finally understand diseases.
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It could replace a lot of animal testing.
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And all of it comes from a tiny few cells sitting in a dish, playing a game that's older than most of the people in the lab.
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It looks like nothing, but it might be the start of something huge.
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For almost the entire history of the universe, there was just matter and nobody around to feel any of it.
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Then at some point, some of that matter arranged itself in a way that did something completely new.
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It started to feel.
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We've always thought of that as the rarest thing there is, something it took billions of years of evolution to make.
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And now we're basically trying to do it again in a lab on purpose.
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We take some cells, we wire them up, we train them with calm and chaos, and we watch to see what happens.
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And don't forget where those cells came from.
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They started as ordinary skin from a real living person who's still out there right now.
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We were never really trying to copy human thinking.
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That was never the scary part.
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The scary part is that somewhere in that dish, a piece of that person might start to feel And nothing on the outside will change.
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The game will just keep playing and nobody would ever know.

Prime impressioni: perché questo video è ottimo per parlare inglese

Questo video non è solo affascinante per il suo contenuto scientifico, ma è anche un materiale perfetto per esercitare la lingua inglese. La narrazione è chiara, con un tono conversazionale ma informativo, e combina vocaboli tecnici (come "biocomputing" o "neuroni") con frasi semplici. Questo mix ti aiuta a familiarizzare con l'uso pratico della lingua, sia in contesti formali che informali. Inoltre, la velocità del parlante è ideale per il shadowing: non troppo veloce, ma sufficiente per stimolare l'orecchio e la pronuncia.

Scomponiamo il testo: frasi naturali e come usarle

Ecco tre frasi chiave e perché suonano genuine:

  • "In a few seconds I'm going to show you one of the most disturbing things happening in science right now": La struttura "in a few seconds" è un modo colloquiale per anticipare qualcosa, molto usato nella vita quotidiana. "Disturbing" è un aggettivo potente ma semplice, perfetto per esprimere sorpresa o preoccupazione.
  • "It basically comes down to power": "Comes down to" è un phrasal verb che significa "riassumersi in", estremamente comune nel parlato. Usarlo rende le tue frasi più fluide e meno formali.
  • "Think about what your brain is doing right now and how little it runs on": "Think about" invita il listener a riflettere, creando un collegamento diretto. "How little it runs on" è una struttura concisa per esprimere quantità minima, molto utile in contesti esplicativi.

Una routine di pratica: shadow speech per migliorare la pronuncia

Prova questo semplice loop per esercitarti con il video:

  1. Guarda un frammento di 10-15 secondi e ascolta attentamente l'intonazione e la pronuncia.
  2. Ripeti immediatamente dopo il parlante, cercando di imitare il ritmo e le pause: questo è il shadowing in inglese, o "shadow speak". Non ti preoccupare se sbagli: l'importante è l'immissione.
  3. Registra te stesso e confronta con il video. Nota le differenze nella pronuncia di vocaboli come "neurons" o "electricity" e ripeti finché non ti senti a tuo agio.
  4. Ripeti il processo con frammenti più lunghi, aumentando gradualmente la difficoltà. Questo metodo aiuta a rafforzare la memoria muscolare per la lingua e a rendere la tua pronuncia più naturale.

Con la pratica regolare del shadowing, noterai che la tua confidenza nel parlare inglese cresce, e le frasi ti verranno più facilmente. Ricorda: ogni errore è un passo verso il miglioramento! 🚀

Cos'è la tecnica dello Shadowing?

Shadowing è una tecnica di apprendimento delle lingue supportata da studi scientifici, originariamente sviluppata per la formazione dei traduttori professionisti e resa popolare dal poliglotta Dr. Alexander Arguelles. Il metodo è semplice ma potente: ascolti un audio in inglese di madrelingua e lo ripeti immediatamente ad alta voce — come un'ombra che segue il parlante con un ritardo di solo 1–2 secondi. A differenza dell'ascolto passivo o degli esercizi di grammatica, lo shadowing costringe il tuo cervello e i muscoli della bocca a elaborare e riprodurre simultaneamente i modelli di discorso reale. La ricerca dimostra che migliora significativamente la precisione della pronuncia, l'intonazione, il ritmo, il discorso connesso, la comprensione dell'ascolto e la fluidità del parlato — rendendolo uno dei metodi più efficaci per la preparazione alla prova di speaking dell'IELTS e per la comunicazione reale in inglese.