And it seems that John Tromp's diagrams originate from David C. Keenan's Mockingbird (1996),
and Bubble Notation comes from Wayne Citrin's Visual Expressions (1995)
discarded1023 1 days ago [-]
Thanks for the link! Some very pretty stuff there.
Missing AFAICT are categorical string diagrams. I'm only sort-of familiar with the notation for Haskell Arrows [1,2] but a quick google for "lambda calculus string diagrams" turns up some recent work by Dan Ghica and others that may be of interest.
Really cool approach. The "Ollama for classical ML" framing makes it instantly clear what this does.
I've been building CLI-first tools myself and the pattern of wrapping complex workflows into simple terminal commands is underrated. Most devs I know would rather type one command than spin up a Jupyter notebook for a quick prediction.
Curious about the model format — do you plan to support a registry where people can publish pre-trained models, like Ollama's library? That would be the killer feature for adoption.
bntr 24 hours ago [-]
Seems like it went to the wrong post.
bntr 2 days ago [-]
You can also construct your own puzzles and share them via URL.
John Tromp's Lambda Diagrams (via 2swap): https://www.youtube.com/watch?v=RcVA8Nj6HEo&t=1346s
Bubble Notation: https://www.youtube.com/watch?v=aRgu8S3Pnb8
And it seems that John Tromp's diagrams originate from David C. Keenan's Mockingbird (1996),
and Bubble Notation comes from Wayne Citrin's Visual Expressions (1995)
Missing AFAICT are categorical string diagrams. I'm only sort-of familiar with the notation for Haskell Arrows [1,2] but a quick google for "lambda calculus string diagrams" turns up some recent work by Dan Ghica and others that may be of interest.
[1] https://en.wikipedia.org/wiki/String_diagram
[2] Ross Paterson "A New Notation for Arrows" (2001)
I'd love to see them smoothly animated.
I've been building CLI-first tools myself and the pattern of wrapping complex workflows into simple terminal commands is underrated. Most devs I know would rather type one command than spin up a Jupyter notebook for a quick prediction.
Curious about the model format — do you plan to support a registry where people can publish pre-trained models, like Ollama's library? That would be the killer feature for adoption.
Example: https://bntre.github.io/visual-lambda/#workspace=H4sIAAAAAAA...