Share

cover art for Babbage: Sam Altman and Satya Nadella on their vision for AI

Babbage from The Economist

Babbage: Sam Altman and Satya Nadella on their vision for AI

OpenAI and Microsoft are leaders in generative artificial intelligence (AI). OpenAI has built GPT-4, one of the world’s most sophisticated large language models (LLMs) and Microsoft is injecting those algorithms into its products, from Word to Windows. 


At the World Economic Forum in Davos last week, Zanny Minton Beddoes, The Economist’s editor-in-chief, interviewed Sam Altman and Satya Nadella, who run OpenAI and Microsoft respectively. They explained their vision for humanity’s future with AI and addressed some thorny questions looming over the field, such as how AI that is better than humans at doing tasks might affect productivity and how to ensure that the technology doesn’t pose existential risks to society.


Host: Alok Jha, The Economist's science and technology editor. Contributors: Zanny Minton Beddoes, editor-in-chief of The Economist; Ludwig Siegele, The Economist’s senior editor, AI initiatives; Sam Altman, chief executive of OpenAI; Satya Nadella, chief executive of Microsoft. 


If you subscribe to The Economist, you can watch the full interview on our website or app


Essential listening, from our archive:


Daniel Dennett on intelligence, both human and artificial”, December 27th 2023


Fei-Fei Li on how to really think about the future of AI”, November 22nd 2023


Mustafa Suleyman on how to prepare for the age of AI”, September 13th 2023


Vint Cerf on how to wisely regulate AI”, July 5th 2023


“Is GPT-4 the dawn of true artificial intelligence?”, with Gary Marcus, March 22nd 2023


Sign up for a free trial of Economist Podcasts+. If you’re already a subscriber to The Economist, you’ll have full access to all our shows as part of your subscription. For more information about how to access Economist Podcasts+, please visit our FAQs page or watch our video explaining how to link your account.

More episodes

View all episodes

  • Babbage: How to save coral reefs

    37:49
    Scenes of ghostly white coral reefs are among the most iconic images of the climate crisis. This year a mass coral bleaching event has hit the Great Barrier Reef, as global warming and the El Niño climate cycle have heated the Pacific Ocean to new extremes. Our science correspondent travels to Australia to meet some of the researchers on the frontlines of the fight to save these ecosystems. Host: Alok Jha, The Economist’s science and technology editor. Contributors: Abby Bertics, The Economist’s science correspondent; Joanie Kleypas of the National Center for Atmospheric Research; Annika Lamb of the Australian Institute of Marine Science.Listen to what matters most, from global politics and business to science and technology—subscribe to Economist Podcasts+For more information about how to access Economist Podcasts+, please visit our FAQs page or watch our video explaining how to link your account.
  • Babbage: The hunt for new worlds

    41:08
    Three decades ago, the discovery of the first planet outside the solar system launched a new field: exoplanet astronomy. It also energised the search for life beyond Earth. Since then, more than 5,500 exoplanets have been identified. Scientists believe there could be trillions more—and experts and amateurs alike are trying to locate them. How will the discovery of these new worlds shape scientists’s understanding of how the solar system (and life) evolved?Alok Jha, The Economist’s science and technology editor, talks to Jessie Christiansen, lead scientist of the NASA Exoplanet Archive at the California Institute of Technology.Listen to what matters most, from global politics and business to science and technology—subscribe to Economist Podcasts+For more information about how to access Economist Podcasts+, please visit our FAQs page or watch our video explaining how to link your account.
  • Babbage: The science that built the AI revolution—part four

    49:07
    What made AI models generative? In 2022, it seemed as though the much-anticipated AI revolution had finally arrived. Large language models swept the globe, and deepfakes were becoming ever more pervasive. Underneath it all were old algorithms that had been taught some new tricks. Suddenly, artificial intelligence seemed to have the skill of creativity.  Generative AI had arrived and promised to transform…everything.This is the final episode in a four-part series on the evolution of modern generative AI. What were the scientific and technological developments that took the very first, clunky artificial neurons and ended up with the astonishingly powerful large language models that power apps such as ChatGPT?Host: Alok Jha, The Economist’s science and technology editor. Contributors: Lindsay Bartholomew of the MIT Museum; Yoshua Bengio of the University of Montréal; Fei-Fei Li of Stanford University; Robert Ajemian and Greta Tuckute of MIT; Kyle Mahowald of the University of Texas at Austin; Daniel Glaser of London’s Institute of Philosophy; Abby Bertics, The Economist’s science correspondent. On Thursday April 4th, we’re hosting a live event where we’ll answer as many of your questions on AI as possible, following this Babbage series. If you’re a subscriber, you can submit your question and find out more at economist.com/aievent. Listen to what matters most, from global politics and business to science and technology—subscribe to Economist Podcasts+For more information about how to access Economist Podcasts+, please visit our FAQs page or watch our video explaining how to link your account.
  • Babbage picks: SpaceX’s Starship reaches orbit

    09:01
    An article from The Economist read aloud. Our science and technology section reports on the recent test flight of Elon Musk’s Starship. While the rocket failed to return to Earth, it’s a step nearer to the stars.For more on Starship, check out our Babbage podcast from 2022.
  • Babbage: The science that built the AI revolution—part three

    38:59
    What made AI take off? A decade ago many computer scientists were focused on building algorithms that would allow machines to see and recognise objects. In doing so they hit upon two innovations—big datasets and specialised computer chips—that quickly transformed the potential of artificial intelligence. How did the growth of the world wide web and the design of 3D arcade games create a turning point for AI?This is the third episode in a four-part series on the evolution of modern generative AI. What were the scientific and technological developments that took the very first, clunky artificial neurons and ended up with the astonishingly powerful large language models that power apps such as ChatGPT?Host: Alok Jha, The Economist’s science and technology editor. Contributors: Fei-Fei Li of Stanford University; Robert Ajemian and Karthik Srinivasan of MIT; Kelly Clancy, author of “Playing with Reality”; Pietro Perona of the California Institute of Technology; Tom Standage, The Economist’s deputy editor.On Thursday April 4th, we’re hosting a live event where we’ll answer as many of your questions on AI as possible, following this Babbage series. If you’re a subscriber, you can submit your question and find out more at economist.com/aievent. Listen to what matters most, from global politics and business to science and technology—subscribe to Economist Podcasts+For more information about how to access Economist Podcasts+, please visit our FAQs page or watch our video explaining how to link your account.
  • Babbage: The science that built the AI revolution—part two

    42:33
    How do machines learn? Learning is fundamental to artificial intelligence. It’s how computers can recognise speech or identify objects in images. But how can networks of artificial neurons be deployed to find patterns in data, and what is the mathematics that makes it all possible?This is the second episode in a four-part series on the evolution of modern generative AI. What were the scientific and technological developments that took the very first, clunky artificial neurons and ended up with the astonishingly powerful large language models that power apps such as ChatGPT?Host: Alok Jha, The Economist’s science and technology editor. Contributors: Pulkit Agrawal and Gabe Margolis of MIT; Daniel Glaser, a neuroscientist at London’s Institute of Philosophy; Melanie Mitchell of the Santa Fe Institute; Anil Ananthaswamy, author of “Why Machines Learn”.On Thursday April 4th, we’re hosting a live event where we’ll answer as many of your questions on AI as possible, following this Babbage series. If you’re a subscriber, you can submit your question and find out more at economist.com/aievent. Get a world of insights for 50% off—subscribe to Economist Podcasts+If you’re already a subscriber to The Economist, you’ll have full access to all our shows as part of your subscription. For more information about how to access Economist Podcasts+, please visit our FAQs page or watch our video explaining how to link your account.
  • Babbage picks: How smart are “smart-drugs”?

    04:24
    An article from The Economist read aloud. Our business section reports that brain-boosting substances are all the rage but their utility is debatable.
  • Babbage: The science that built the AI revolution—part one

    42:57
    What is intelligence? In the middle of the 20th century, the inner workings of the human brain inspired computer scientists to build the first “thinking machines”. But how does human intelligence actually relate to the artificial kind?This is the first episode in a four-part series on the evolution of modern generative AI. What were the scientific and technological developments that took the very first, clunky artificial neurons and ended up with the astonishingly powerful large language models that power apps such as ChatGPT?Host: Alok Jha, The Economist’s science and technology editor. Contributors: Ainslie Johnstone, The Economist’s data journalist and science correspondent; Dawood Dassu and Steve Garratt of UK Biobank; Daniel Glaser, a neuroscientist at London’s Institute of Philosophy; Daniela Rus, director of MIT’s Computer Science and Artificial Intelligence Laboratory; Yoshua Bengio of the University of Montréal, who is known as one of the “godfathers” of modern AI.On Thursday April 4th, we’re hosting a live event where we’ll answer as many of your questions on AI as possible, following this Babbage series. If you’re a subscriber, you can submit your question and find out more at economist.com/aievent. Get a world of insights for 50% off—subscribe to Economist Podcasts+If you’re already a subscriber to The Economist, you’ll have full access to all our shows as part of your subscription. For more information about how to access Economist Podcasts+, please visit our FAQs page or watch our video explaining how to link your account.
  • Babbage: Could a vaccine finally end multiple sclerosis?

    39:13
    Multiple sclerosis (MS) is a debilitating condition, affecting 1.8m people worldwide. It occurs when a patient’s immune system attacks the fatty tissue that insulates the nerve cells. In 2022, scientists identified the trigger for this reaction: Epstein-Barr virus (EBV), a common pathogen that causes glandular fever (the “kissing disease”). That discovery opened up new treatment options for MS and raises a tantalising question—could the disease one day be eliminated entirely with a vaccine?Host: Alok Jha, The Economist's science and technology editor. Contributors: Petros Iosifidis, who describes his experience living with MS; Evan Irving-Pease of the University of Copenhagen; Ruth Dobson of Queen Mary University of London; Jessica Durkee-Shock of the National Institutes of Health. Get a world of insights for 50% off—subscribe to Economist Podcasts+If you’re already a subscriber to The Economist, you’ll have full access to all our shows as part of your subscription. For more information about how to access Economist Podcasts+, please visit our FAQs page or watch our video explaining how to link your account.