Show HN: Findmelike – Bayesian visual search for art

Re:Show HN: Findmelike – Bayesian visual search for art by boothead on Wednesday September 17, 2014 @04:51AM (#8329132)

I think this is awesome! However for me then most interesting thing is the tech behind it. Having worked in the same office as the team behind this and been to a few talks that Tom's given, here are a few things that HN might find interesting.

* Built by the same guy behind BayesHive: https://bayeshive.com/

* An example of probabilistic functional programming in the wild. (This let's you build programs where the variables are probability distributions.)

* Good example of something built in Haskell that really speaks to the strenghts of the language!

Maybe Tom could give us a brief synopsis of how this was built and how it works?

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Re:Show HN: Findmelike – Bayesian visual search for art by glutamate on Wednesday September 17, 2014 @05:02AM (#8329170)

Thanks Ben.

On the programming side:

* 100% Haskell. Even our post-install script in the packages we build for the server are in Haskell.

* Use Spock and postgresql-simple

* 95% of functionality is in a library which is written in Nice Haskell - e.g. all functions are total, type safety where it makes sense.

* Library consists of data types, pure functions, and functions that live in a DB monad. All code is decoupled from the request-response server implementation.

* Front-end in AngularJS

On the statistics/learning side:

* We apply Bayes' theorem every time you press that green "Next" button. There is a statistical model for your choices based on your ultimate preferences, which we estimate.

* Lots of tricks to bring this inference down to 50ms on a modest CPU and to maximise information yield from user interaction.

More examples of this choice paradigm coming in the next few weeks.

[ Parent | on HN ]