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> people are scared to be an early adopter. ML was first developed in 1973. Ocaml in 1996 and SML in 1997. Great tools which haven't been popular in 20-40 year
by mavelikara 6y ago
> people are scared to be an early adopter.
ML was first developed in 1973. Ocaml in 1996 and SML in 1997. Great tools which haven't been popular in 20-40 years probably have something beyond fear of early adoption inhibiting them.
- AlchemistCamp 6y agoI'd say herd behavior and network effects are the main issues. Do a quick search on YouTube on "what programming language to learn". You'll find video after video using popularity as a primary or even the primary factor to base the decision on. Non-technical management tends to do the same, based out of the belief that languages are all pretty much equivalent and a desire to hire easily swappable "resources".
- mavelikara 6y agoYaron Minsky joined Jane Street in 2003. The success of Jane Street and the use of OCaml there is well known in finance circles. Finance is full of people who don’t exhibit herd behavior - many firms have a culture of studying fundamental causes and taking contrarian positions. That begs the question - why did OCaml not get widely adopted in finance? Jet was purchased by Walmart in 2016. Mark Lore from Jet was appointed as CEO of Walmart to turn the company around, particular its technology operations (to compete effectively with Amazon). Jet’s tech was mostly developed in F#. Yet, Lore did not push for its adoption widely within Walmart. IMO explaining away the failure of ML languages to gain market share over multiple decades as “herd behavior and network effects” is lazy.
- de_keyboard 6y ago> why did OCaml not get widely adopted in finance? I think it has been pretty successful. The bigger success story in finance is F# though, which takes a bunch of ideas from OCaml.
- de_keyboard 6y agoI think it's tooling. But tooling follows from adoption in most cases.
- mavelikara 6y agoAgreed. The stuff "sitting on the shelf", as your parent comment said, have problems too (eg tooling). They might solve some problems, but are far from the silver bullets we are looking for.