typed-racket VS mediKanren

Turns out, Shallow was slower than it needed to be for types of built-in math (+, *, ...). PR here: https://github.com/racket/typed-racket/pull/1316

Last weekend, I put together a working sample for how to show multiple syntax errors from Racket macros. It works in DrRacket and racket-xp-mode. It's based on Typed Racket.

https://gist.github.com/srcreigh/f341b2adaa0fe37c241fdf15f37...

The well-documented Racket `raise-syntax-error` will let you display 1 syntax error at a time. It works by throwing an exception during macro expansion hence you only get 1 error in your IDE. That code lets you highlight 2+ errors.

Please build a type system in Racket! I would love to try it out.

Helpfully, the above sample code is an example of how to store compiler-level state. So next, just wrap all your base forms, add some type declaration syntax, type inference, etc.

I would love to have a language that can be used to define a customized type system in Racket.

Typed Racket is an incredible feat. Can you imagine adding an entire type system without writing a separate compiler? Using all the batteries included with your language?

However I don't like that Typed Racket enforces soundness with Runtime checks, I much prefer TypeScript style checking. I also have run into some pretty confusing messages ie [1]. Diversity is healthy, it'd be nice to have static typechecking systems to choose from for Racket.

[1] https://github.com/racket/typed-racket/issues/1021

> I like how TS is unsound (has no runtime performance penalty for mixing untyped code), and is easily disabled via any if it's in the way.

This is already done. See https://github.com/racket/typed-racket/pull/952 for RFC and https://github.com/racket/typed-racket/pull/948 for the implementation.

Not really production, but probably THE most impressive biomedicine research work I've seen (and I'm an academic MD):

https://github.com/webyrd/mediKanren

This is a FOL theorem prover that uses medical research articles as terms. They use it to do genetics and drug repurposing metaresearch. It's like the wet dream of all the biomed machine learning fanboys out there, except that:

1. it's not machine learning

and

2. it really works

And wow, he uses logic programming to deduce a diagnostic from the facts https://github.com/webyrd/mediKanren .. and used to find out what his son had https://www.statnews.com/2019/07/25/ai-expert-writing-code-save-son/

Hi Kamaal!

I know Cisco is using core.logic, which is David Nolen's Clojure variant of miniKanren, in their ThreatGrid product. I think the Enterprisey uses of mediKanren are a bit different than the purely relational programming that I find most interesting, though.

Having said that, we are now on our second generation of mediKanren, which is software that performs reasoning over large biomedical knowledge graphs:

https://github.com/webyrd/mediKanren/tree/master/medikanren2

mediKanren is being developed by the Hugh Kaul Precision Medicine Institute at the University of Alabama at Birmingham (HKPMI). HKPMI is run by Matt Might, who you may know from his work on abstract interpretation and parsing with derivatives, or from his more recent work on precision medicine. mediKanren is part of the NIH NCATS Biomedical Data Translator Project, and is funded by NCATS:

https://ncats.nih.gov/translator

Greg Rosenblatt, who sped up Barliman's relational interpreter many order of magnitude, has been hacking on dbKanren, which augments miniKanren with automatic goal reordering, stratified queries/aggregation, a graph database engine, and many other goodies. dbKanren is the heart of mediKanren 2.

I can imagine co-writing a book on mediKanren 2, and its uses for precision medicine...

Cheers,

--Will

The Precision Medicine Institute that I now run produces mediKanren: https://github.com/webyrd/mediKanren

It's an open source logical reasoning engine (read: 1960's AI) for drug repurposing that we deploy routinely to help patients.

There is always a need for better relationalization of biological data sets that feed such tools too.

For example, SemMedDB is really showing its age for NLP of the scientific literature and yet it is still astonishingly useful for helping patients even as is.