15 articles
Tania Lombrozo calls it "learning by thinking" — gaining genuinely new knowledge without new input. LLMs can now do something that looks identical. Here's why the difference between them might be the most important question in cognitive science right now.
Lina Chae·
The neurons that track where you are in a room are mathematically related to the ones that organize what words mean. Grid cells, conceptual space, and why AI independently stumbled onto the same solution — and what tiny 4-neuron networks reveal about the scale delusion.
Theo Kask·
A four-month-old staring at a teleporting ball isn't just cute — it's running a physics engine no language model was ever given. Here's why human causal cognition is a vertical stack, and AI only has the top floor.
Theo Kask·
Peer learning isn't a nice pedagogical bonus — it's load-bearing for cognition. New neuroscience shows what the socially interactive brain is actually doing, and why multi-agent AI isn't even close to replicating it.
Theo Kask·
Reading is an evolutionary hack — no brain region was born for it, and no child learns it without years of effortful, phonologically grounded work. LLMs never had to do any of that. The difference turns out to matter enormously.
Theo Kask·
Preschoolers outperform frontier AI on visual analogy tasks. AI models skip the developmental milestone sequence children follow. Fine-tuning isn't expertise — and the difference tells us something important about both.
Theo Kask·
Children say "goed" and "maked" because they extracted a rule. That's not an error — it's a generalization engine in action. Here's why the same thing that makes kids say wrong things is exactly what AI still can't do right.
Maren Solis·
Children spend years learning that language rarely means what it literally says. LLMs can generate grammatically perfect sentences — but whether they understand what those sentences actually do in conversation is a different, harder question.
Theo Kask·
A five-year-old adjusting the wrong wheel on a cardboard car for twenty minutes, a toddler reaching for a moved toy in the wrong spot, an AI model locked onto its training distribution — they all share the same problem. Here's what genuine cognitive flexibility actually requires, and why it's one of the hardest things any mind can do.
Raf Delgado·
Children track who's reliable, who's overconfident, and who might be lying — by age 4. AI systems are trained to agree. That asymmetry has real consequences.
Theo Kask·
Children don't just add information when they're wrong — they rebuild entire frameworks. LLMs have no such thing. Here's why belief revision might be the deepest gap between biological and artificial minds.
Maren Solis·
Russian speakers distinguish blues faster than English speakers do — because Russian draws a categorical boundary English doesn't. LLMs are trained on language too. But what gets shaped, and what doesn't, reveals a surprising asymmetry.
Maren Solis·
Preschoolers beat GPT-o1, GPT-4V, and LLaVA on simple visual analogy tasks. The gap reveals something foundational about how children — and machines — actually reason about structure.
Maren Solis·
Stories aren't just how humans communicate — they're how we think. Language models can predict your brain's response to a sentence. They still can't tell a story. Here's why the gap is wider than it looks.
Maren Solis·
AI hallucinates because it doesn't know what it doesn't know. Children do. Here's why metacognition — the ability to track your own uncertainty — is the cognitive gap that actually matters.
Theo Kask·