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This episode explores the intersections between various flavors of math and programming, and the ways in which they can be mixed, matched, and combined. Michael Arntzenius, "rntz" for short, is a PhD student at the University of Birmingham building a programming language that combines some of the best features of logic, relational, and functional programming. The goal of the project is "to find a sweet spot of something that is more powerful than Datalog, but still constrained enough that we can apply existing optimizations to it and imitate what has been done in the database community and the Datalog community." The challenge is combining the key part of Datalog (simple relational computations without worrying too much underlying representations) and of functional programming (being able to abstract out repeated patterns) in a way that is reasonably performant.
This is a wide-ranging conversation including: Lisp macros, FRP, Eve, miniKanren, decidability, computability, higher-order logics and their correspondence to higher-order types, lattices, partial orders, avoiding logical paradoxes by disallowing negation (or requiring monotonicity) in self reference (or recursion), modal logic, CRDTS (which are semi-lattices), and the place for formalism is programming. This was a great opportunity for me to brush up on (or learn for the first time) some useful mathematical and type theory key words. Hope you get a lot out of it as well -- enjoy!
The transcript for this episode was sponsored by Repl.it and can be found at https://futureofcoding.org/episodes/040#full-transcript
Support us on Patreon: https://www.patreon.com/feelingofcomputing
See omnystudio.com/listener for privacy information.
By Ivan Reese, Jimmy Miller, and Lu Wilson4.9
2727 ratings
This episode explores the intersections between various flavors of math and programming, and the ways in which they can be mixed, matched, and combined. Michael Arntzenius, "rntz" for short, is a PhD student at the University of Birmingham building a programming language that combines some of the best features of logic, relational, and functional programming. The goal of the project is "to find a sweet spot of something that is more powerful than Datalog, but still constrained enough that we can apply existing optimizations to it and imitate what has been done in the database community and the Datalog community." The challenge is combining the key part of Datalog (simple relational computations without worrying too much underlying representations) and of functional programming (being able to abstract out repeated patterns) in a way that is reasonably performant.
This is a wide-ranging conversation including: Lisp macros, FRP, Eve, miniKanren, decidability, computability, higher-order logics and their correspondence to higher-order types, lattices, partial orders, avoiding logical paradoxes by disallowing negation (or requiring monotonicity) in self reference (or recursion), modal logic, CRDTS (which are semi-lattices), and the place for formalism is programming. This was a great opportunity for me to brush up on (or learn for the first time) some useful mathematical and type theory key words. Hope you get a lot out of it as well -- enjoy!
The transcript for this episode was sponsored by Repl.it and can be found at https://futureofcoding.org/episodes/040#full-transcript
Support us on Patreon: https://www.patreon.com/feelingofcomputing
See omnystudio.com/listener for privacy information.

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