Erik J. Larson warned yesterday in Metro Silicon Valley that we shouldn’t overestimate what machine intelligence can do:

Human intelligence emerges because we are deeply embedded in our environments—a constant feedback loop of interaction that gives us a perpetual advantage. The machine model, no matter how well-trained, doesn’t operate within this dynamic system. It not only isn’t learning in real-time, it’s not inferring from outliers but from best-fit.

I use LLMs to spit out facts and figures that don’t come to my mind—I’m not a calculator. I don’t use them to say something interesting. The more I interact with today’s AI, the more I realize we’re not much further along—thinking about real intelligence—than decades ago. We’re still messing around with machines and shit-talking ourselves.

“Why Human Intelligence Thrives Where Machines Fail,” January 15, 2025

Larson, author of The Myth of Artificial Intelligence: Why Computers Can’t Think the Way We Do (2021), warns,

But we’re all missing the eight-hundred-pound gorilla in the room: true intelligence is found by moving away from larger datasets and away from statistical norms. Yes, there are statistical norms, and we make use of them in inference. It’s not that such inferences are non-existent but rather that they tell us very little about what we’re trying to understand: intelligence.

We know neural networks can handle patterns that crystallize in large enough datasets. Unfortunately, that entire exercise has very little to do with AGI in the first place. Good luck with that. Silver lining: since people are pretty disastrously bad at discerning patterns in mountains of data, AI will always play a role in our broader cognitive story.

We’ve built these systems to optimize the world as we know it. But the world we know is just the start. When will researchers stop obsessing over training data and start talking about the one thing that makes us us: the ability to handle what we haven’t seen before? Until then, AI systems are playing catch-up—nay, better, they’re pretending to catch-up—to a game we’ve been playing since day one. ”Where Machines Fail,” January 15, 2025