Pipeline Conversations

A Machine Learning Podcast by ZenML

About the show

Pipeline Conversations is a fortnightly podcast bringing you interviews and discussion with industry leaders, top technology professionals and others. We discuss the latest developments in machine learning, deep learning, artificial intelligence, with a particular focus on MLOps, or how trained models are used in production.

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  • Data-centric Computer Vision with Eric Landau

    September 15th, 2022  |  Season 2  |  51 mins 51 secs
    annotation, computer-vision, data-centric-ai, engineering, machine-learning

    This week I spoke with Eric Landau, co-founder of Encord, a platform for data-centric computer vision. This podcast contains a lot of geekery about annotation, and even though Encord aren't an annotation tool per se, Eric and his team have tackled a bunch of quite complicated problems relating to that domain.

  • ML Abstractions with Phil Howes

    September 5th, 2022  |  Season 2  |  54 mins 13 secs
    ai, data-science, infrastructure, machine-learning, mlops, pipelines, platforms, tools

    This week we dive into the abstractions that we're all trying to layer on top of the core ML processes and workflows. I spoke with Phil Howes, co-founder and chief scientist at BaseTen. BaseTen is a platform that allows data scientists to go from an initial model to an MVP web app quickly.

  • Building MLOps Tools with Outerbounds

    August 22nd, 2022  |  Season 2  |  59 mins 43 secs
    ai, data-science, infrastructure, machine-learning, mlops, pipelines, tools

    This week I spoke with Savin Goyal and Hugo Bowne-Anderson from Outerbounds. They both work on leading, building and helping people put models into production through Metaflow, and I'm sure current users of ZenML will find this conversation interesting to hear how they think through the broader questions and engineering problems involved with MLOps.

  • Safe and Testable Computer Vision with Lakera

    August 4th, 2022  |  Season 2  |  57 mins 32 secs
    computer-vision, data, machine-learning, mlops, monitoring, safety, testing

    This week I spoke with Mateo Rojas-Carulla, the CTO and a co-founder of Lakera and Matthias Kraft, also a co-founder and the CPO there. Lakera is an AI safety company that does a lot of work in the computer vision domain, building a platform and tools for users to gain more confidence in the output and functionality of their models.

  • Satellite Vision with Robin Cole

    July 28th, 2022  |  Season 2  |  47 mins 56 secs
    computer-vision, data-science, deep-learning, mlops, satellite, serverless

    This week I spoke with Robin Cole, a senior data scientist at Satellite Vu, a company that's about to launch a thermal imaging satellite into space in order to provide new ways of seeing the earth from above.

  • Autonomous Shipping with Captain AI

    July 21st, 2022  |  Season 2  |  1 hr 22 secs
    autonomous, computer-vision, data-centric-ai, edge-ml, machine-learning, shipping, vehicles

    This week on the podcast I spoke with Gerard Kruisheer, the CTO and co-founder of Captain AI, a company based in the Netherlands working on autonomous shipping out of the busy Rotterdam port.

  • ML Monitoring with Emeli Dral

    July 7th, 2022  |  Season 2  |  46 mins 57 secs
    data, machine-learning, mlops, monitoring

    I'll be having some conversations with the people behind the tools that ZenML offers as integrations. We spoke with Ben Wilson a few weeks back, and today I'm pleased to publish this conversation with Emeli Dral, co-founder and CTO of Evidently, an open-source tool tackling the problem of monitoring of models and data for machine learning.

  • Edge Computer Vision with Karthik Kannan

    June 30th, 2022  |  Season 2  |  46 mins 53 secs
    computer-vision, data-centric-ai, edge-ml, google-glass, machine-learning

    This week I spoke with Karthik Kannan, cofounder and CTO of Envision, a company that builds on top of the Google Glass and using Augmented Reality features of phones to allow visually impaired people to better sense the environment or objects around them.

  • Humans in the Loop with Iva Gumnishka

    June 23rd, 2022  |  Season 2  |  50 mins 55 secs
    annotation, data, data-annotation, data-centric-ai, labeling, machine-learning

    We were lucky to get to talk to Iva Gumnishka, the founder of Humans in the Loop. They are an organisation that provides data annotation and collection services. Their teams are primarily made up of those who have been affected by conflict and now are asylum seekers or refugees.

  • ML Engineering with Ben Wilson

    June 8th, 2022  |  Season 2  |  1 hr 4 mins
    ai, data-science, infrastructure, machine-learning, mlops, pipelines, tools

    Today, I'm extremely excited to present this conversation I had with Ben Wilson who works over at Databricks and who has also just released a new book called 'Machine Learning Engineering in Action'.

  • ZenML Recap with Adam and Hamza

    April 28th, 2022  |  25 mins 31 secs
    mlops, open-source, zenml

    Adam and Hamza return for a short discussion of what we've been busy working on during the previous few months, where we're going with ZenML and why it's so amazing to be building an open-source tool.

  • Trustworthy ML with Kush Varshney

    April 14th, 2022  |  39 mins 8 secs
    ai, artificial-intelligence, bias, data-science, ethics, fairness, machine-learning

    I enthusiastically read Kush Varshney's book when it was released for free to the world several months back. Trustworthy Machine Learning is a concise and clear overview of many of the ways that machine learning can go wrong, and so I was especially keen to get Kush on to talk more about his work and research.

  • Open-Source MLOps with Matt Squire

    March 31st, 2022  |  47 mins 41 secs
    ai, artificial-intelligence, data-science, infrastructure, machine-learning, mlops, open-source

    This week I spoke with Matt Squire, the CTO and co-founder of Fuzzy Labs, where they help partner organisations think through how best to productionise their machine learning workflows.

  • Practical Production ML with Emmanuel Ameisen

    March 17th, 2022  |  58 mins
    ai, artificial-intelligence, data-science, infrastructure, machine-learning, mlops

    This week I spoke with Emmanuel Ameisen, a data scientist and ML engineer currently based at Stripe. Emmanuel also wrote an excellent O'Reilly book called "Building Machine Learning Powered Applications", a book I find myself often returning to for inspiration and that I was pleased to get the chance to reread in preparation for our discussion.

  • From Academia to Industry with Johnny Greco

    March 3rd, 2022  |  56 mins 34 secs
    academia, applied-ml, astronomy, industry, machine-learning, mlops, nlp

    This week I spoke with Johnny Greco, a data scientist working at Radiology Partners. Johnny transitioned into his current work from a career as an academic — working in astronomy — where also worked in the open-source space to build a really interesting synthetic image data project.

    We get into that project in our conversation but we also discuss his experience of crossing over into industry, the skills that have served him in his new job, and his experience of working in a world where the stakes around models in production are much higher.

  • The Modern Data Stack with Tristan Zajonc

    February 10th, 2022  |  59 mins 4 secs
    ai, artificial-intelligence, data-science, infrastructure, machine-learning, mlops

    This week I spoke with Tristan Zajonc, the CEO and cofounder of Continual, a company that provides an AI layer for enterprise companies or, as we'll get into in the podcast, the so-called 'modern data stack'.