Cheaper LLM labelling

Sometimes we want to run a classification task at high rate, but the classifier is either slow, expensive, or both. When that happens, we can slot a logistic regression in front of the classifier, and train it through gradient descent with the labels returned from the slow classifier.

I did not expect that to come out to less than 40 lines of plain Perl, with no support from complicated maths libraries or anything. So cool.

Full article (8–19 minute read): Cheaper LLM labelling

Flashcard of the week

We saw historical inference in last week's newsletter, and we'll continue on the same theme today. Last week's question might even help you guess the answer to this week's! This is from Gould's magnum opus.

What argument does Darwin build on observations from the Galápagos Islands?

The Galápagos Islands are somewhat isolated from each other, and each offers a slightly different environment. The common misunderstanding goes that Darwin observed birds were uniquely adapted to the islands they lived on, ergo evolution.

But that's not the important part. The important part is the reverse side of the same coin:

Each island's species are shaped largely by their mainland ancestors, rather than optimally designed for their current environment.

This is the real argument for evolution!

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