Pratica di Shadowing: A.I. ‐ Humanity's Final Invention? - Impara a parlare inglese con i video
Creazione lezione...
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Humans rule Earth without competition.
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But we're about to create something that may change that.
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Our last invention, the most powerful tool, weapon or maybe even entity, artificial superintelligence.
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This sounds like science fiction.
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So let's start at the beginning.
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Intelligence is the ability to learn, reason, acquire knowledge and skills, and use them to solve problems.
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Intelligence is power and we're the species that exploited it the most.
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So much so that humanity broke the game of nature and took control.
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But the journey there wasn't straightforward.
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For most animals, intelligence costs too much energy to be worth it.
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Still, if we track intelligence in the tree of species over time, we can see lots of diverse forms of intelligence emerge.
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The earliest brains were in flatworms 500 million years ago.
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Just a tiny cluster of neurons to handle basic body functions.
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It took hundreds of millions of years for species to diversify and become more complex.
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Life conquered new environments, gained new senses and had to contend with fierce competition over resources.
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But in nature all that matters is survival and brains are expensive.
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So for almost all animals a narrow intelligence fit for a narrow range of tasks was enough.
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In some environments, animals like birds, octopuses and mammals evolved more complex neural structures.
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For them, it paid off to have more energy-consuming skills like advanced navigation and communication.
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Until 7 million years ago, the hominins emerged.
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We don't know why, but their brains grew faster than their relatives.
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Something was different about their intelligence.
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Very slowly, it turned from narrow to general, from a screwdriver to a multi-tool multi-tool, able to think about diverse problems.
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Two million years ago, Homo erectus saw the world differently from anyone before, as something to be understood and transformed.
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They controlled fire, invented tools and created the first culture.
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We probably emerged from them around 250,000 years ago with an even larger and more complex brain.
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It enabled us to work together in large groups and to communicate complex thoughts.
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We used our intelligence to improve our lives, to ask how things work and why things are the way they are.
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With each discovery, we asked more questions and pushed forward, preserving what we learned, outpacing what evolution could do with genes.
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Knowledge builds on knowledge.
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Progress was slow at first and then sped up exponentially.
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Agriculture, writing, medicine, astronomy or philosophy exploded into the world.
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200 years ago science took off and made us even better at learning about the world and speeding up progress.
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35 years ago the internet age began.
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Today we live in a world made to suit our needs, created by us, for us.
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This is incredibly new.
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We forget how hard it was to get here, how enormous the steps on the intelligence ladder were, and how long it took to climb them.
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But once we did, we became the most powerful animal in the world in a heartbeat.
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But we may be in the process of changing this.
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We're building machines that could be better at the very thing that gave us the power to conquer the planet.
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Humanity's final invention.
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Artificial Intelligence Artificial Intelligence, or AI, is software that performs mental tasks with a computer.
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Code that uses silicon instead of neurons to solve problems.
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In the beginning, AI was very simple.
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Lines of code on paper, mere proofs of concept to demonstrate how machines could perform mental tasks.
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Only in the 1960s did we start seeing the first examples of what we would recognize as AI.
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A chatbot in 1964, a program to sort through molecules in 1965.
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Slow, specialized systems requiring experts to use them.
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Their intelligence was extremely narrow, built for a single task inside a controlled environment.
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The equivalent of flatworms 500 million years ago doing the minimum amount of mental work.
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Progress in AI research paused several times when researchers lost hope in the technology.
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But just like changing environments create new niches for life, the world around AI changed.
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Between 1950 and 2000, computers got a billion times faster while programming became easier and widespread.
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In 1972, AI could navigate a room.
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In 1989, it could read handwritten numbers.
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But it remained a fancy tool, no match for humans.
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Until in 1997, an AI shocked the world by beating the world champion in chess, proving that we could build machines that could surpass us.
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But we calmed ourselves because a A chess bot is quite stupid.
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Not a flatworm, but maybe a bee, only able to perform a specialized narrow task.
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But within this narrow task, it's so good that no human will ever again beat AI at chess.
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As computers continued to improve, AI became a powerful tool for more and more tasks.
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In 2004 it drove a robot on Mars.
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In 2011 it began recommending YouTube videos to you.
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But this was only possible because humans broke down problems into easy to digest chunks that computers could solve quickly.
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Until we taught AIs to teach themselves.
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Rise of the self-learning machines.
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This is not a technical video, so we're massively oversimplifying here.
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In a nutshell, the sheer power of supercomputers was combined with the almost endless
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data collected in the information age to make a new generation of AI.
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AI experts began drastically improving forms of AI software called neural networks,
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enormously huge networks of artificial neurons that start out being bad at their tasks.
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They then used machine learning, which is an umbrella term for many different training techniques
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and environments that allows algorithms to write their own code and improve themselves.
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The scary thing is that we don't exactly know how they do it and what happens inside them,
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It's just that it works and that what comes out the other end is a new type of AI.
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A capable black box of code.
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These new AIs could master complex skills extremely quickly with much less human help.
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They were still narrow intelligences, but a huge step up.
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In 2014, Facebook AI could identify faces with 97% accuracy.
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In 2016, an AI beat the best humans in the incredibly complex game of Go.
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In 2018, a self-learning AI learned chess in four hours just by playing against itself, and then defeated the best specialized chess bot.
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Since then, machine learning has been applied to reading, image processing, solving tests and much more.
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Many of these AIs are already better than humans for whatever narrow task they were trained, but they still remained a simple tool.
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AI still didn't seem that big of a deal for most people.
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Then came the chatbot ChatGPT.
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The work that went into it is massive.
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It trained on nearly everything written on the internet to learn how to handle language, which it now does better than most people.
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It can summarize, translate and help with some maths problems.
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It's incredibly more broad than any other system just a few years ago, not crushing any single benchmark, but all of them at once.
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Many large tech companies are spending billions to build powerful competitors.
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AI is already transforming customer service, banking, healthcare, marketing, copywriting, creative spaces and more.
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AI-generated content has already taken hold of social media, YouTube and news websites.
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Elections are expected to be inundated by propaganda and misinformation.
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No one is sure how much good or harm can come from adopting AI everywhere.
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Change is scary.
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There will be winners and losers.
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One of the biggest questions governments and corporations have now is how to manage the transition to an AI-boosted economy.
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All these potential gains or risks are just the result of today's AI.
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ChatGPT's intelligence is a major step up, but it remains narrow.
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While it can write a great essay in seconds, it doesn't understand what it's writing.
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But what if the AIs stopped being narrow?
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General AI What makes humans different from current AI is our general intelligence.
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Humans can technically absorb any piece of knowledge and start working on any problem.
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We're great at many very different skills and tasks, from playing chess to writing or solving science puzzles.
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Not equally, of course.
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Some of us are experts in some fields and beginners in others, but we can technically do all of them.
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In the past, AI was narrow and able to become good at one skill, but was rather bad in all the others.
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Simply by building faster computers and pouring more money into AI training will get us new, more powerful generations of AI.
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But what if the next step for AI is to become a general intelligence like us?
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An AGI.
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If the AI improvement process continues as it has been, it's not unlikely that AGI could be better in most or even all skills that humans can do.
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We don't know how to build AGI, how it will work, or what it will be able to do.
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Since narrow AIs today are capable of mastering one mental task quickly, AGI might be able to do the same with all mental tasks.
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So even if it starts out stupid, an AGI might be able to become as smart and capable as a human.
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While this sounds like science fiction, most AI researchers think this will happen sometime this century, maybe already in a few years.
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Humanity is not ready for what will happen next, not socially, not economically, not morally.
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Earlier we defined intelligence as the ability to learn, reason, acquire knowledge and skills and use them to solve problems,
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all things humans excel at.
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An AGI as intelligent as even an average human would already disrupt modern civilization
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because they are not bound by the same limitations as we are.
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Today's These AIs like ChatGPT already think
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and solve the tasks they were made for at least 10 times faster than even very skilled humans.
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Maybe HEI will be slower, but it may also be faster, maybe much faster.
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And since HEIs are software, you could copy them endlessly as long as you have enough storage and run them in parallel.
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There are 8 million scientists in the world.
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Now imagine an HEI copied a million times and put to work.
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One million scientists working 24-7, thinking 10 times faster than humans, without being distracted, only focused on the task they've been given.
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What if, suddenly, AGI could do all intelligence-based jobs in the world, from interpreting law, to coding, to creating animated YouTube videos,
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better, faster and much cheaper than humans?
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Would whoever controls this AGI suddenly own the economy?
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And thinking bigger, human progress is our intelligence applied to problems.
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So what could a million AGI's achieve?
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Solve fundamental questions of science, like dark energy.
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Invent new technology that gives us limitless energy, fix climate change, cure aging and cancer.
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But then again, sadly, humans apply their intelligence not just for the benefit of all.
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What if the AGI's are tasked to guide drones or pull the triggers in war?
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Or to engineer a virus that only kills people with green eyes?
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Or to create the most profitable social media so addictive that people starve in front of their screens?
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The creation of AGI could reasonably be as big of an event as taming fire
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or electricity and give whoever invents it equally as much power.
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But now let's go one step further.
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What if the potential of AGI doesn't stop here?
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Intelligence Explosion.
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Intelligence and knowledge build and accelerate each other, but humans are limited by biology and evolution.
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Once we evolved the right hardware, our software outpaced evolution by orders of magnitude, and within a heartbeat we ruled this planet.
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But our software basically hasn't changed much since then, which is why we have obesity and destroy the climate for short-term gains.
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Since AGI is software on a computer, once it's smart enough to do AI research, the rate of AI progress should speed up a lot.
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And that results in better AI that's better at AI research without much human involvement.
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It may even be possible that AI could learn how to directly improve itself, in which case some experts fear this feedback loop could be incredibly fast.
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Maybe just months or years after the first self-improving AGI is switched on.
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Maybe it would actually take decades.
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We simply don't know.
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This is all speculative.
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But such an intelligence explosion might lead to a true super-intelligent entity.
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We don't know what such a being would look like, what its motives or goals would be, what would go on in its inner world.
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We could be as laughably stupid to a super-intelligence as squirrels are to us, unable to even comprehend its way of thinking.
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This hypothetical scenario keeps many people up at night.
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Humanity is the only example we have of an animal becoming smarter than all others, and we have not been kind to what we perceive as less intelligent beings.
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AGI might be the last invention of humanity.
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It's possible that it could become the most intelligent and therefore most powerful being on Earth.
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A god in a box that could exercise its power to bring unimaginable wealth and happiness to humans while securing our future.
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it could subvert civilization and bring about our end, with humanity unable to come up with a way to stop it.
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We'll look at some of these potential futures in more videos, but for now, let's wrap up.
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The only thing we know for sure is that today, right now, many of the largest and richest companies in the world are racing to create ever more powerful AIs.
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Whatever our future is, we are running towards it.
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Who knows how long we have until we must confront our AI future.
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Luckily, you still have plenty of time to prepare for it, if you're learning on Brilliant, that is.
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Brilliant will make you a better thinker and problem solver in just minutes a day,
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with thousands of bite-sized, hands-on lessons on just about anything you may be curious about, including AI.
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Their latest course, How LLMs Work, takes you under the hood of real language models models.
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It demystifies technologies like ChatGPT with interactive lessons on everything from how models build vocabulary to how they choose their next word.
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You'll learn how to tune LLMs to produce output with exactly your desired tonality, whether it's poetry or a cover letter.
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And you'll understand why training is really everything by comparing models trained on Taylor Swift lyrics
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and the legal speech of Big Tech's terms and conditions.
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It's an immersive AI workshop allowing you to experience and harness the mechanics of today's most advanced tool.
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We've also partnered with Brilliant to create a series of lessons to take your scientific knowledge to the next level.
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These lessons let you further explore the topics in our most popular videos, from rabies and mammalian metabolism to climate science and supernovae.
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Each lesson on Brilliant is interactive, like a one-on-one version of a Kurzgesagt video.
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And you can get started whenever, wherever, right from whatever device you'd like.
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To get hands-on with Kurzgesagt lessons and explore everything Brilliant has to offer, from AI and programming to maths,
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science and beyond, start your free 30-day trial by signing up at brilliant.org slash nutshell.
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There's even an extra perk for Kurzgesagt viewers.
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Anyone signing up through our link will get 20% off an annual membership once their trial ends.
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Thank you.
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Vocabolario e note di pronuncia per questa lezione
Questa lezione di conversazione di livello C1 si basa sul video “A.I. ‐ Humanity's Final Invention?”. Le parole che ritornano più spesso: intelligence, task, Agi, narrow. Questo video contiene 184 frasi e 2575 parole da ripetere con lo shadowing. Il parlato dura 16:42. Chi parla ha un ritmo naturale di circa 154 parole al minuto, vicino a una conversazione quotidiana. Solo il 81% delle parole rientra nelle 3.000 più comuni dell’inglese, quindi il lessico è impegnativo.
Vocaboli chiave di questo video
Le 15 parole più avanzate del video, con pronuncia e significato:
| Parola | Pronuncia | Significato |
|---|---|---|
| chess sostantivo | /t͡ʃɛs/ | scacchi |
| neuron sostantivo | /ˈn(j)ʊɹɑn/ | neurocito |
| specialize verbo | /ˈspɛʃəˌlaɪz/ | specializzare |
| emerge verbo | /ɪˈmɝd͡ʒ/ | emergere, venire fuori |
| invention sostantivo | /ɪnˈvɛnʃən/ | invenzione |
| flatworm sostantivo | /ˈflæt.wəɹm/ | platelminte, verme piatto |
| nutshell sostantivo | /ˈnʌt.ʃɛl/ | guscio di noce |
| heartbeat sostantivo | /ˈhɑɹtˌbit/ | battito |
| neural aggettivo | /ˈnʊɹəl/ | neurale |
| conquer verbo | /ˈkɑŋkɚ/ | conquistare, sconfiggere |
| researcher sostantivo | /ˈɹiˌsɝ.t͡ʃɚ/ | ricercatore, ricercatrice |
| civilization sostantivo | /ˌsɪv.ɪ.laɪˈzeɪ.ʃən/ | civiltà |
| transform verbo | /tɹænsˈfɔɹm/ | trasformare, modificare |
| interactive aggettivo | /ˌɪn.tɚˈæk.tɪv/ | interattivo |
| mammal sostantivo | /ˈmæməl/ | mammifero |
I phrasal verb che sentirai
| Parola | Pronuncia | Significato |
|---|---|---|
| speed up verbo | /spiːdˈʌp/ | stringere i tempi |
| come up with verbo | ideare, escogitare | |
| get off verbo | scendere | |
| take off verbo | togliere | |
| wrap up verbo | imballare, impacchettare |
La grammatica di questo video
Le strutture che chi parla usa di più, con le parole esatte del video:
| Struttura | Nel video |
|---|---|
| Forma passiva be + participio passato — conta ciò che accade, non chi lo fa | be understood · was combined · has been applied |
| Present perfect have/has + participio passato — un’azione passata che conta ancora adesso | has been applied · has already taken · has been |
| Frasi relative who / which + frase — un’informazione in più su una persona o una cosa | learning, which is · then, which is |
Pronuncia a cui fare attenzione
Chi parla usa 22 contrazioni e forme ridotte, come don't, we're, doesn't. Pronunciale nella forma breve, così come le senti.
- I suoni “th”: hypothetical /ˌhaɪpəˈθɛtɪkəl/, algorithm /ˈælɡəɹɪðm̩/
- I suoni “sh” e “zh”: specialize /ˈspɛʃəˌlaɪz/, invention /ɪnˈvɛnʃən/, nutshell /ˈnʌt.ʃɛl/, civilization /ˌsɪv.ɪ.laɪˈzeɪ.ʃən/, benchmark /ˈbɛn(t)ʃmɑːk/
- Parole lunghe — attenzione all’accento: civilization /ˌsɪv.ɪ.laɪˈzeɪ.ʃən/, interactive /ˌɪn.tɚˈæk.tɪv/, hypothetical /ˌhaɪpəˈθɛtɪkəl/, astronomy /əˈstɹɑ.nə.mi/, accelerate /ɪkˈsɛl.əˌɹeɪt/
I suoni difficili per chi parla italiano:
- /h/ — va soffiata, non è muta: heartbeat /ˈhɑɹtˌbit/, hypothetical /ˌhaɪpəˈθɛtɪkəl/, harness /ˈhɑɹ.nəs/, comprehend /ˌkɑmpɹɪˈhɛnd/
- Consonante finale — senza aggiungere una vocale dopo: chess /t͡ʃɛs/, specialize /ˈspɛʃəˌlaɪz/, emerge /ɪˈmɝd͡ʒ/, chatbot /ˈtʃætbɑt/, heartbeat /ˈhɑɹtˌbit/
- /æ/ — più aperta della “e”: chatbot /ˈtʃætbɑt/, flatworm /ˈflæt.wəɹm/, transform /tɹænsˈfɔɹm/, interactive /ˌɪn.tɚˈæk.tɪv/, animate /ˈæn.ə.mət/
Come esercitarsi con questo video
- Ascolta tutto il video una volta senza parlare e annota le parole che non conosci.
- Inizia a velocità 0,75×, fai shadowing frase per frase e torna alla velocità normale quando diventa facile.
- Registrati e confronta con l’originale, facendo attenzione a parole come chess, neuron, specialize.
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.