The connection between type systems and neural net structure is underexplored in practice. One thing I'd add: when you're dealing with multi-modal inputs in production — say, mixed structured and unstructured content — the type-safety problem compounds. You end up with implicit contracts at inference boundaries that are very hard to enforce.
Has the author written anything on how this applies to transformer architectures specifically? The attention mechanism seems like a place where a richer type theory would be genuinely useful.
Previously worked in edtech. Interested in developer tooling, online learning design, and email infrastructure at scale.