8 articles
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·