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.

Ben Kehoe, Cloud Robotics Research Scientist, Discusses Serverless @iRobot

On this week’s podcast, Wes Reisz talks with Ben Kehoe of iRobot. Ben is a Cloud Robotics Research Scientist where he works on using the Internet to allow robots to do more and better things. AWS and, in particular, Lambda is a core part of cloud enabled robots.

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.

Justin Cormack on Decomposing the Modern Operating System

Justin Cormack discusses how the modern operating system is being decomposed with toolkits and libraries such as LinuxKit, eBPF, XDP, and what the kernel space service mesh Cilium is doing. Wes Reisz and Justin Cormack also discuss how Cilium differs from service meshes like an Istio, Linkerd2 (previously Conduit), or Envoy.

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.