I'm intrigued by the idea of deep learning systems 'hallucinating' high resolution images from low res. It makes sense: if it's a photo of known type (e.g. people, birds) you have a lot of additional data to interpolate intelligently.
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Really cute approach to reporting type errors: when there's a type error, show an example of a runtime error that the type check has prevented!
Data-Driven Techniques for Type Error Diagnosis https://escholarship.org/uc/item/59s4h4pv
Playing with optional type signatures in Python, I realise that the return type is the most important to me.
I'd much rather have a function with only a return type instead of a function with only parameter types. It's often quick to add too.
An interesting feature of the Grok TiddlyWiki interface: it has the sidebar on the right.
I see a sidebar on the left way more often, but arguably it makes more sense on the right for a wiki? The content is effectively more prominent.
https://groktiddlywiki.com/read/