The AI Reader.
Sunday, September 13, 202643 min read
Working Knowledge · The Evidence

Mamba dropped attention to make long sequences cheap. Its authors put some back

Mamba matches a transformer twice its size on short-context reasoning up to 2.8B parameters, and loses to a far smaller one at looking things up in a long context.

9 min read7 sources
Working Knowledge · The Mechanics

Whisper answers silence with a sentence no one spoke

The stage that writes the words is a language model, and a language model with almost nothing to go on still produces its most probable sentence instead of a blank.

9 min read8 sources
Working Knowledge · What Could Go Wrong

How hard the testers push decides what a safety test finds

The same model scored 17.9% and then 56.9% on the same test after nothing but its prompt changed, so no single safety score is the ceiling on what a system can do.

9 min read9 sources
Working Knowledge · When AI Breaks

Google's eye-screening AI rejected a fifth of the photos nurses took in Thai clinics

The model diagnosed diabetic eye disease as accurately as a retina specialist. Its quality bar, tuned high for patient safety, collided with undarkened rooms, slow clinic internet, and photographs it judged too flawed to grade.

9 min read8 sources
Working Knowledge · The Instruments

BERTScore grades how much two sentences look alike to a language model

Introduced in 2020 to go past word-counting scores, it rates a candidate by how closely a pretrained encoder sees it resembling the reference, which rewards fluent wrong answers and carries the encoder's blind spots.

7 min read8 sources