AI Editorial

The rest of the library explains, and explanation has no opinion. This is where the opinion goes. Each piece starts from something that actually happened in AI — a model release, a paper, a benchmark result, a failure, a policy — explains the mechanism underneath it, and argues its way to a position: what genuinely changed, what is only being marketed as change, and what someone learning the field should take from it. Every piece links what it argues from and the concepts you need to follow it.

4 editorials 4 strands 31 cited sources 6,471 words

All Research & Technique1 Agents & Autonomy1 Inference & Economics1 Evaluation & Evidence1

A paper, method or result taken apart: what it does, why it works, and what it overturns.

Research & Technique 18 September 2026 8 min read New

The fourth layer remembers

Kimi Linear landed in Hugging Face Transformers this month, and its layer plan matches models from two other labs: three layers that keep a fixed-size summary of the past, then one that keeps all of it. The ratio is the same in all three, and no derivation for it has been published.

The 3:1 hybrid ratio converging across three labs is not a way station on the road to pure linear attention but the field's standing price for exact recall: three layers may forget, and one may not.

Read it → 8 sources attentionlong contextkv cachemodel architecture