Casey Newton is the editor of Platformer, a CNBC Contributor, and a friend of Big Technology Podcast. He joins us for our final show of the year, where we look back on the biggest stories of 2021 and predict what's coming in 2022. Join us for a conversation about Big Tech's year of transition, the upcoming Web3 wars, and whether the cult of the founder is falling apart.

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The Big Technology Podcast takes you behind the scenes in the tech world featuring interviews with plugged-in insiders and outside agitators. Alex Kantrowitz, a Silicon Valley journalist who's interviewed the world's top tech CEOs — from Mark Zuckerberg to Larry Ellison — is the host.
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Folge vom 29.12.20212021 In Review, 2022 Predictions — With Casey Newton
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Folge vom 22.12.2021The Theranos Trial Concludes — With NPR's Bobby AllynBobby Allyn is an NPR tech reporter based in San Francisco. He's been waking up at 2 a.m. to watch the trial of ex-Theranos CEO Elizabeth Holmes from the courthouse. In this episode, Allyn breaks down the case for and against Holmes, the biggest moments in the trial, and the potential outcomes now that the jury is deliberating.
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Folge vom 15.12.2021Apple Nears $3 Trillion + The Truth About Web3 — With Benedict EvansBenedict Evans is an independent analyst who covers big tech and the broader technology landscape. He joins Big Technology Podcast to discuss Apple's move to $3 trillion, how the rest of the Big Tech companies stack up, what Web3 is really all about, and his former employer Andreessen Horowitz. Stick around for the third segment where he answers questions from Twitter.
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Folge vom 08.12.2021Getting AI To Think And Learn Like Humans — With Daniel Kahneman and Yann LeCunDaniel Kahneman is a Nobel prize-winning psychologist and economist and author of Thinking, Fast and Slow, a landmark book that decodes human decision-making. Yann LeCun is the chief AI scientist at Meta (Facebook) and a pioneer in the field of deep learning, which the cutting edge of AI is based on today. The two come together on Big Technology Podcast this week to discuss how machines and humans learn, whether there are parallels, and what each field can learn from each other.