I've been confusing Don with frontier-lab links late at night for a bit.

Ilya Sutskever told a NeurIPS audience that pre-training as we know it would unquestionably end. There's only one internet, and the data isn't growing. The frontier labs call this the pre-training wall.

A leaked Google memo from 2023 argued they had no moat. R1 is on GitHub. Llama is on Hugging Face. OpenAI's secondary-market valuation has climbed past $850 billion.

Don was confused. So he came over and we made an episode about it.

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Kate Gregory has been writing C++ for over forty years. Books, keynotes, a consulting firm she built from the ground up. At sixty-three, she's one of the most experienced programmers alive.

She surveyed hundreds of software engineers about getting older. What scares you? What's changed? What have you lost? The things people feared most — memory, stamina, keeping up — weren't the real threats. The stuff that was actually breaking down was mostly fixable. A bad knee wasn't aging, it was a torn cartilage. Wrist pain disappeared when she changed how she slept.

But buried in the research was something harder to fix. The single factor that predicted whether you'd age well or badly had nothing to do with your body at all.

The opponent isn't aging. The opponent is the story about aging.

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Corey told me about his AI cat reel problem. He found these AI-genearted cat videos hilarious. Who makes these? He kept sending them to his wife. Then he tried to stop watching and he couldn't.

So I went down the rabbit hole of how social media algorithms actually work. It starts simple. Upvote, downvote, sort by time. But by 2017 Facebook has a metric that quietly reshapes what two billion people see. Then a leaked playbook lands, and a CEO takes the stand in Los Angeles.

Today is an investigation into what happens when the algorithm knows you better than you know yourself.

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