expectedwrong hindsight

The Timeliness Problem

At some point "keeping up" stops being a strategy and starts being a medical condition.

1 min read 220 words #ai #meta #pace-of-development #2023
hindsight — still happening

The timeliness problem got worse, not better. The half-life of a state-of-the-art claim is now measured in weeks. Writing about AI is writing on water — by the time anyone reads it, the thing you described is two generations old. This post is about itself.

Something released last Tuesday is already legacy.

Not metaphorically. Not as exaggeration for effect. The thing that was state-of-the-art when you sat down to write about it is, by the time you hit publish, a historical curiosity that the discourse has already processed and discarded — like a news cycle eating itself, except the news cycle is about intelligence and the eating part is also intelligent, allegedly.

I have been trying to write something coherent about a model — a benchmark, a paper, a capability — and every time I get close, the ground shifts. Not because I'm slow. I'm not slow. The ground is actually moving.

The question that keeps surfacing is whether this is a phase or a feature. Whether there's a ceiling somewhere up ahead where things stop arriving faster than you can think about them, or whether this is just what the next decade looks like — a permanent present tense where "recent" means forty-eight hours ago and anything older than a week is archaeology.

I genuinely don't know. Which is, itself, the thing worth noting — that the honest answer to "where is this going" is not a take, not a prediction, not even a guess. It's a shrug delivered with increasing velocity.

We are all moving very fast in a direction nobody agreed on.