In this episode, Andres and Matti talk to Mike Sperber, CEO of Active Group in Germany. They discuss how to successfully develop an application based on deep learning in Haskell, contrast learning by example with the German bureaucratic approach, and highlight the virtues of having fewer changes in the language.
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As the original author would start a Haskell file, would turn on all the GHC extensions existing at the time and then proceed to use them. And now I think one or two years have passed, and GHC would no longer compile the sources. They knew what changes they were going to make. They probably even had people who could do the changes, but they did not have – they literally did not have a single person there who could make it compile.
Emphasis mine. Never do this kids.
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Can someone please point me to SPJ’s paper referenced in this episode?
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(I just searched for “Simon Peyton Jones and Jean-Marc Eber on how to do financial derivatives using functional programming”)
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Thank you. I found the same paper, but I wasn’t sure that’s the one referenced since this paper does not explicitly discuss combinators.
They do discuss combinators. For example, Figure 2 lists a bunch of combinators.
They do, but not explicitly. I was expecting a recommendation to use combinators to build large-scale apps. I always try to point developers on my team to build combinators instead of creating premature abstractions and I was looking to point them to a paper where they also recommend something like that explicitly.