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In Athens, where ancient ideas once created the foundations of logic and cause, today’s important scientific mind came back to talk about a variety of intelligence. Deep Mind’s CEO, and the latest Dimmets of the Nobel Prize win, were not interested in looking back. Its focus was firmly on what is coming forward: through artificial intelligence, a world is being newly shaped, which not only can we force us to re -consider what we learn, but how we learn it.
He talked about the pace of change – AI is already rewriting the science, research and engineering rules. Models now move faster than most institutions. In his view, the most valuable skills will not be deep technical training, but regardless of your field, you do not have the ability to continue to learn repeatedly.
And the calculation is not just guessing. He has been the focus of AI’s biggest moments – from Alfago’s world’s best go player to shocking to protein, from Alpha Fold, which changed the way the biologists turn to drug development and have the highest honor in chemistry.
He too did not come from a discipline. Its background combines neuroscience, computer science, and even competitive chess. It is a mixture that makes it right where many of today’s successes are taking place. So when he talks about what AI can happen, people listen.
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When asked about the future, Roubai acknowledged that it was difficult to predict how matters would be created. “It is very difficult to predict the future, such as 10 years from now, in ordinary matters,” he said. “It is still difficult today, seeing how fast the AI is changing, even a week to a week. The only thing you can say is that there is a huge change.”
He explained that this change would not only come in the form of new tools or sharp machines – it would make people rebuild how people approach themselves. As AI contributes to heavy lifting in science and engineering, the real advantage for humans will lie in how quickly we can axis, absorb ignorant ideas, and apply them in new ways.
According to the calculation, there is no one article to move the original skills – it is learning itself. Not only to memorize the facts, but also to find out how to deal with new problems, how to reach high -speed in unknown areas, when things change even when it is curious.
He calls them “meta skills”, and made it clear that they are more important than ever. When AI keeps moving the ground under your feet, knowing how to maintain learning can be the only thing that is really sticking.
This meta skills are already in process. A scientist is taking basic coding to run his models. An engineer is finding out how to work with a new fake platform after his phase. A doctor who learns to realize the diagnosis of AI-generation. These are not a great shift or completely new skill of career to learn. However, they are a sign that the usual thing is being done, which is entering something unfamiliar and detects it anyway. When he says “learning to learn”, this is exactly what it means.
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One thing made clear: We will not be enough for the world we learn today. Our educational systems were designed for a lazy world, where the career followed the line straight and the knowledge remained useful for decades. This is not the case now, especially in science and engineering, where AI is rapidly renewing how problems are solved and discoveries are made.
What is most important is no longer knows everything – it knows how to learn and mold. We can have a habit of learning not only once, but permanently because technologies continue to develop.
The calculation also talked about where it was going. He suggested that artificial general intelligence (AGI) – like humans, can argue with various problems like humans – less than ten years can be far away. If this happens, the speed of discovery can be accelerated by ways that are difficult to make. Medical research, climate science, energy system – the entire area of work can move forward faster than ever. He called it the future of “radical abundance”, where the boundaries are no longer about tools or data, but about how much we are ready to use.
The Prime Minister of Greece, Carekos Matsotaks, who joined the conscience for the program, highlighted what we can expect in the near future at a different angle. He warned that if people do not see personal gain, none of them will matter. If the wealth and progress created by the AI are piled up in a handful of companies, confidence will be lost.
He said that when most people see a wide range of fortunately created by a few and little change in their lives, anger arises. And in its view, this path is not a majority but a cause for unrest.
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