Podcasts

Emmanuel Ameisen, Head of AI at Insight, on Building a Semantic Search System for Images

On this week’s podcast, Wes Reisz talks to Emmanuel Ameisen, head of AI for Insight Data Science, about building a semantic search system for images using convolution neural networks and word embeddings, how you can build on the work done by companies like Google, and then explores where the gaps are and where you need to train your own models.

Vaughn Vernon on Developing a Domain Driven Design First Actor-Based Microservices Framework

Vaughn Vernon has recently released a new open source project called vlingo. The platform is designed to support DDD at the framework and toolkit level. On today’s podcast, Vernon discusses what the framework is all about, why he felt it was needed, and some of the design decisions made in developing the platform.

Mike Lee Williams on Probabilistic Programming, Bayesian Inference, and Languages Like PyMC3

Reisz talks with Mike Lee Williams of Cloudera’s Fast Forward Labs about Probabilistic Programming. The two discuss how Bayesian Inference works, how it’s used in Probabilistic Programming, production-level languages in the space, and some of the implementations/libraries that we’re seeing.

Colin Eberhardt on What WebAssembly Is, and Plans for Version 2.0

In this podcast Wes talks to Colin Eberhardt, the technology director at Scott Logic, about what WebAssembly (WASM) is, a bit of the history of JavaScript, and plans for WebAssembly 2.0 including the threading model and GC.

Sander Mak on the Java Module System

Sander Mak discusses the module system with Java. We’ll hit on some of the practical advice he’s seen preparing and then implementing migrations to 9 (with and without the classpath). We’ll discuss some of the benefits and pitfalls to look for as you plan and execute your migrations.