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A conversation with Laurent Mazare about how your choice of programming language interacts with the kind of work you do, and in particular about the tradeoffs between Python and OCaml when doing machine learning and data analysis. Ron and Laurent discuss the tradeoffs between working in a text editor and a Jupyter Notebook, the importance of visualization and interactivity, how tools and practices vary between language ecosystems, and how language features like borrow-checking in Rust and ref-counting in Swift and Python can make machine learning easier. You can find the transcript for this podcast episode along with links to things we discussed at signalsandthreads.com.

A conversation with Laurent Mazare about how your choice of programming language interacts with the kind of work you do, and in particular about the tradeoffs between Python and OCaml when doing machine learning and data analysis. Ron and Laurent discuss the tradeoffs between working in a text editor and a Jupyter Notebook, the importance of visualization and interactivity, how tools and practices vary between language ecosystems, and how language features like borrow-checking in Rust and ref-counting in Swift and Python can make machine learning easier. You can find the transcript for this podcast episode along with links to things we discussed at signalsandthreads.com.

Memory issues can be hard to track down. A function that onlyallocates a few small objects can cause a space leak if it’s calledoften enough and those object...

It’s a software engineer’s dream: A compiler that can take idiomatic high-level code and output maximally efficient instructions. Ron’s guest this week is Greta Yorsh, who has worked on just that problem in a career spanning both industry and academia. Ron and Greta talk about some of the tricks that compilers use to make our software faster, ranging from feedback-directed optimization and super-optimization to formal analysis. You can find the transcript for this episode along with links to things we discussed at signalsandthreads.com.

This blog post and the previous one about functor packs covers two RFCs currently developed by OCamlPro and Jane Street. We previously introduced functor packs, a new feature adding the possiblity to compile packs as functors, allowing the user to implement functors as multiple source files or even ...

OCamlPro has a long history of dedicated efforts to support the development of the OCaml compiler, through sponsorship or direct contributions from Flambda Team. An important one is the Flambda intermediate representation designed for optimizations, and in the future its next iteration Flambda 2. Th...

At Tarides, we build many tools and writing UI is usually a tedious task. In this post we will see how to write functional UIs in OCaml…

Electronic exchanges like Nasdaq need to handle a staggering number of transactions every second. To keep up, they rely on two deceptively simple-sounding concepts: single-threaded programs and multicast networking. In this episode, Ron speaks with Brian Nigito, a 20-year industry veteran who helped build some of the earliest electronic exchanges, about the tradeoffs that led to the architecture we have today, and how modern exchanges use these straightforward building blocks to achieve blindingly fast performance at scale. You can find the transcript for this episode along with links to things we discussed at signalsandthreads.com.