Mathias Brandewinder explains why F# is well suited for data science: the REPL, type providers for seamless data access, functional programming concepts and much more.
Yan Cui talks about the advantages of using F# to build DSLs and using the actor model. Also: why and how to use graph databases to model (game) economies.
Natalia Chechina explains the challenges of scaling distributed Erlang beyond a certain number of systems and how SD Erlang helps to overcome those problems.
Dianne Marsh talks to Charles Humble about hiring an engineer at Netflix, organising an engineering team around speed of execution, the languages and frameworks Netflix uses, and diversity in IT.
Andrea Magnorsky talks about her experience with adopting F# for .NET game development, where F# fits, property based testing with FsCheck, and much more.
José Valim explains the ideas behind Elixir, a new programming language for the Erlang VM. Also: concurrency, handling iteration with Iteratees and other approaches, and much more.
David Nolen explains the power of the Transit format (efficiently serializing values to JSON and MessagePack), Transducers, the power of Facebook's React when bundled with immutable data structures.
Marc Prud'hommeaux talks about his experience using Apple's Swift language, both to write new code and port an existing Objective-C code base. Also: immutable data structures, concurrency, and more.
Jessica Kerr discusses the differences between coding in Java, Scala and Clojure, the charm of autogenerated test data, and diversity in the IT industry.
Craig Motlin, technical lead of the GS Collections project, talks about where GS Collections came from, how it compares with other collections libraries, and what influence it had on Java 8. He describes the different philosophy of GS Collections as compared to other collections libraries, and what benefits open-sourcing the internal library has had
Adam Ernst talks about how functional programming and immutable data structures have made Facebook’s iOS app much easier to test and debug. By decoupling the data pipeline from the UI objects, and minimising the wrk on the UI thread, the application has become easier to test and suffers less bugs than when the UI was generated procedurally.