How knowledge in computing and AI actually decays, consolidates, and gets reused: the evidence behind claims that skills expire fast, the cognitive-science mechanisms behind durable learning, and what happens — for an individual or a whole research field — to the knowledge that doesn't consolidate.
"The half-life of a computer science degree is five years." "AI skills expire every two years." "Medical knowledge doubles every 73 days." These numbers circulate constantly, always with the same implication: things are…
"The problem with rote learning is not that it fails to produce recall. It's that it fails to produce anything else." — a common paraphrase of the research this page is built on, not a direct quote from any one source
This page sits between two others on this site that, read separately, leave a gap worth naming directly. Memorising vs Learning makes the cognitive-science case for interleaved, spaced practice over blocked, massed…
The Half-Life of Knowledge describes ephemeral, applied, and foundational knowledge as stages in a decay chain, and treats a foundational schema as the stable end-state that's left once the volatile, specific material…
"Research and learning are the same thing, just with different audiences." — Pat Parslow
A note on register before the argument: The Half-Life of Knowledge and How Sleep Turns Ephemeral Memory Into Foundational Knowledge build on cited, checked empirical literature. This page is different in kind — it's our…
The rest of this cluster establishes the pieces separately: The Half-Life of Knowledge sets out the three tiers as a decay chain; How Sleep Turns Ephemeral Memory Into Foundational Knowledge gives the individual-scale…