Galaxy Brain

On this week’s Galaxy Brain episode, Charlie Warzel is joined by New York Times technology reporter Tiffany Hsu to discuss the rise of AI influencers—synthetic avatars, often indistinguishable from real people, that are flooding social-media feeds to sell supplements and promote brands. Hsu unpacks her reporting on the combination of forces converging around it, including the wellness industry, a historically fertile ground for scammers.

The pair discuss how the volume of synthetic content online is producing a new kind of epistemic exhaustion: a fatigue so deep that many people have simply stopped caring whether what they're seeing is real. So is authenticity already beside the point? And is an audience’s emotional response—rather than the truth behind the image—the only currency that matters?

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How is AI changing the way we work? This week on Galaxy Brain, Charlie Warzel is joined by Johnathan and Melissa Nightingale, two experts in management and leadership training. They discuss how chatbots and AI agents are winding their way through the workforce, offering a firsthand view of how companies are (and aren’t) adopting AI tools. The conversation covers the gap between AI hype and what’s actually happening in offices. It also touches on how overreliance on AI tools may be making bosses worse at their jobs, and how work may be one of the last bastions of sustained social connection in a period of cultural alienation and isolation.

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What is Twitter’s legacy? In this episode of Galaxy Brain, Charlie Warzel traces how Twitter, now called X, evolved from a status-update tool to one of the most culturally and politically influential—and contentious—platforms of the modern internet. Charlie is joined by early Twitter executive Jason Goldman. They explore how Twitter’s core features—many invented by users—reshaped media and politics while also enabling new forms of harassment, misinformation, and attention hijacking. Goldman reflects candidly on the company’s key inflection points—from early free-speech-maximalist decisions and underinvestment in trust and safety to Twitter’s role in events like the Arab Spring and the election of Donald Trump. The discussion culminates in Twitter’s Elon Musk era, where its logic of attention has been weaponized more explicitly. The episode reckons with what Goldman and others ultimately built: a tool with outsize cultural influence that’s broken brains and amplified some of society’s worst impulses.

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Just how are powerful AI models being used in warfare overseas? In this episode of Galaxy Brain, Charlie Warzel sits down with Wired senior writer Will Knight to discuss the rise of autonomous weapons. From the origins of Project Maven to the recent falling-out between Anthropic and the U.S. Department of Defense, they trace what’s happening as artificial intelligence moves from summarizing documents to informing decisions on the battlefield.

How do these weapons work? What are the safeguards? Who decides what values get baked into these models? As autonomous systems become harder to avoid, where exactly is the line between human judgment and machine decision making? Warzel and Knight help explain how the Pentagon and Silicon Valley are more entangled than ever and where warfare goes from here. 

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How are we still getting caught in the rain? This week’s “Galaxy Brain” explores the world of weather forecasting—specifically the apps on our phones that we have come to rely on. As climate change intensifies storms and smartphones put hyperlocal forecasts in our pockets, we’ve never had more meteorological data. And yet plenty of people lament that their weather apps can’t get it right. Charlie digs into why we obsessively refresh our weather apps, why we blame them when they’re wrong, and what it really means to forecast an inherently chaotic atmosphere.

Charlie talks with the physicist Adam Grossman, a co-creator of the cult-favorite weather app Dark Sky that redefined minute-by-minute forecasting before being acquired by Apple. Grossman pulls back the curtain on how weather predictions are made—a process that includes satellites, weather balloons, massive physics simulations, and machine-learning models—and explains why forecasts are improving even if it doesn’t always feel that way

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