AI 2041: Ten Visions for Our Future - Couverture souple

Lee, Kai-Fu; Qiufan, Chen

Couverture souple

ISBN 10 : 0593238311 ISBN 13 : 9780593238318

Editeur : Crown, 2024

Synopsis

How will AI change our world within twenty years? A pioneering technologist and acclaimed writer team up for a “dazzling” (The New York Times) look at the future that “brims with intriguing insights” (Financial Times). This edition includes a new foreword by Kai-Fu Lee.
 
A BEST BOOK OF THE YEAR: The Wall Street Journal, The Washington Post, Financial Times
 
Long before the advent of ChatGPT, Kai-Fu Lee and Chen Qiufan understood the enormous potential of artificial intelligence to transform our daily lives. But even as the world wakes up to the power of AI, many of us still fail to grasp the big picture. Chatbots and large language models are only the beginning.
 
In this “inspired collaboration” (The Wall Street Journal), Lee and Chen join forces to imagine our world in 2041 and how it will be shaped by AI. In ten gripping, globe-spanning short stories and accompanying commentary, their book introduces readers to an array of eye-opening settings and characters grappling with the new abundance and potential harms of AI technologies like deep learning, mixed reality, robotics, artificial general intelligence, and autonomous weapons.

A propos du livre

À propos de l?auteur

Kai-Fu Lee is the CEO of Sinovation Ventures and New York Times bestselling author of AI Superpowers. Lee was formerly the president of Google China and a senior executive at Microsoft, SGI, and Apple. Co-chair of the Artificial Intelligence Council at the World Economic Forum, he has a bachelor’s degree from Columbia and a PhD from Carnegie Mellon. Lee’s numerous honors include being named to the Time 100 and Wired 25 Icons lists. He is based in Beijing.

Chen Qiufan (aka Stanley Chan) is an award-winning author, translator, creative producer, and curator. He is the president of the World Chinese Science Fiction Association. His works include Waste Tide, Future Disease, and The Algorithms for Life. The founder of Thema Mundi, a content development studio, he lives in Beijing and Shanghai.

Extrait. © Reproduit sur autorisation. Tous droits réservés.

I believe it’s indisputable that computers simply “think” differently from our brains. The best way to increase computer intelligence is to develop general computational methods (like deep learning and GPT-3) that scale with more processing power and more data. In the past few years, we’ve seen the best NLP models ingest ten times more data each year, and with each factor of ten, we saw qualitative improvements. In January 2021, just seven months after the release of GPT-3, Google announced a language model with 1.75 trillion parameters, which is nine times larger than GPT-3. This continued the trend of language model prowess growing by about ten times per year. This language model has already read more than any one of us could in millions of lifetimes. This progress will only grow exponentially.

While GPT-3 makes many basic mistakes, we are seeing glimmers of intelligence, and it is, after all, only version 3. Perhaps in twenty years, GPT-23 will read every word ever written and watch every video ever produced and build its own model of the world. This all-knowing sequence transducer would contain all the accumulated knowledge of human history. All you’ll have to do is ask it the right questions.

So, will deep learning eventually become “artificial general intelligence” (AGI), matching human intelligence in every way? Will we encounter “singularity” (see chapter 10)? I don’t believe it will happen by 2041. There are many challenges that we have not made much progress on or even understood, such as how to model creativity, strategic thinking, reasoning, counter-factual thinking, emotions, and consciousness. These challenges are likely to require a dozen more breakthroughs like deep learning, but we’ve had only one great breakthrough in over sixty years, so I believe we are unlikely to see a dozen in twenty years.

In addition, I would suggest that we stop using AGI as the ultimate test of AI. As I described in chapter 1, AI’s mind is different from the human mind. In twenty years, deep learning and its extensions will beat humans on an ever-increasing number of tasks, but there will still be many existing tasks that humans can handle much better than deep learning. There will even be some new tasks that showcase human superiority, especially if AI’s progress inspires us to improve and evolve.

What’s important is that we develop useful applications suitable for AI and seek to find human-AI symbiosis, rather than obsess about whether or when deep-learning AI will become AGI. I consider the obsession with AGI to be a narcissistic human tendency to view ourselves as the gold standard.

Détails de l'édition

• Éditeur: Crown
• Date d'édition: 2024
• Langue: anglais
• ISBN 10: 0593238311
• ISBN 13: 9780593238318
• Reliure: Broché
• Nombre de pages: 496
• Coordonnées du fabricant: non disponible
• Personne responsable: non disponible