LLMs understand nullability

The visualisation of how the model sees nullability was fascinating.

I'm curious if this probing of nullability could be composed with other LLM/ML-based python-typing tools to improve their accuracy.

Maybe even focusing on interfaces such as nullability rather than precise types would work better with a duck-typed language like python than inferring types directly (i.e we don't really care if a variable is an int specifically, but rather that it supports _add or _sub etc. that it is numeric).

> we don't really care if a variable is an int specifically, but rather that it supports _add or _sub etc. that it is numeric

my brother in christ, you invented Typescript.

(I agree on the visualization, it's very cool!)

I am more than aware of Typescript, you seem to have misunderstood my point: I was not describing a particular type system (of which there have been many of this ilk) but rather conjecturing that targeting interfaces specifically might make LLM-based code generation/type inference more effective.