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.

Pipeline Conversations on social media

Episodes

  • The Evaluation Playbook: Making LLMs Production-Ready ๐Ÿงช๐Ÿ“ˆ

    December 15th, 2024  |  Season 3  |  32 mins 43 secs
    ai, evaluation, genai, llmops, llms, mlops

    A comprehensive exploration of real-world lessons in LLM evaluation and quality assurance, examining how industry leaders tackle the challenges of assessing language models in production.

  • Prompt Engineering & Management in Production: Practical Lessons from the LLMOps Database

    December 11th, 2024  |  Season 3  |  29 mins 34 secs
    ai, genai, llmops, llms, mlops, prompt-engineering, prompts

    Prompt engineering is the art and science of crafting instructions that unlock the potential of large language models (LLMs). It's a critical skill for anyone working with LLMs, whether you're building cutting-edge applications or conducting fundamental research. But what does effective prompt engineering look like in practice, and how can we systematically improve our prompts over time?

  • LLM Agents in Production: Architectures, Challenges, and Best Practices

    December 9th, 2024  |  Season 3  |  32 mins 37 secs
    agents, ai, genai, llmops, llms, mlops

    An in-depth exploration of LLM agents in production environments, covering key architectures, practical challenges, and best practices.

  • Building Advanced Search, Retrieval, and Recommendation Systems with LLMs

    December 6th, 2024  |  Season 3  |  13 mins 8 secs
    ai, embeddings, genai, llmops, llms, mlops, rag, recommendation, search

    Discover how embeddings power modern search and recommendation systems with LLMs.

  • Building LLM Applications that Know What They're Talking About ๐Ÿ”“๐Ÿง 

    December 3rd, 2024  |  Season 3  |  21 mins 23 secs
    ai, genai, llmops, llms, mlops, rag

    A conversation about the RAG entries in the ZenML LLMOps database

  • Demystifying LLMOps: A Practical Database of Real-World Generative AI Implementations

    December 2nd, 2024  |  Season 3  |  15 mins 2 secs
    genai, llmops

    NotebookLM summary podcast episode of a ZenML blog around the LLMOps Database.

  • ML at the British Library with Daniel van Strien

    November 10th, 2022  |  Season 2  |  57 mins 28 secs
    ai, archives, computer-vision, data-science, libraries, machine-learning

    This week I spoke with Daniel van Strien, a digital curator working at the British Library. Daniel has worked on a number of projects at the intersection of archives, libraries and machine learning and I was really happy to have the chance to get to unpack some of the ways he's finding to apply these techniques and tools.

  • Questioning MLOps with Lak Lakshmanan

    October 27th, 2022  |  Season 2  |  53 mins 2 secs
    ai, artificial-intelligence, data-science, infrastructure, machine-learning, mlops, scale

    This week I spoke with Lak Lakhshmanan, who worked for years at Google on ML and AI projects and products at a senior level and he also brings years of experience working on meteorology and other scientific projects previously.

  • The Full Stack with Charles Frye

    October 12th, 2022  |  Season 2  |  57 mins 5 secs
    ai, artificial-intelligence, data-science, deep-learning, education, machine-learning, mlops

    This week I spoke with Charles Frye. Not only has Charles volunteered to be a judge on our Month of MLOps competition happening right now, he's part of the core team working on the Full Stack Deep Learning course.

  • Educating the next generation with Goku Mohandas

    September 29th, 2022  |  Season 2  |  1 hr 8 mins
    ai, artificial-intelligence, data-science, education, infrastructure, machine-learning, medicine, mlops

    In today's conversation, I'm speaking with Goku Mohandas, founder and creator of the amazing online resource MadeWithML. Goku has a bunch of practical experience, from working with Apple to a startup in the oncology space and much more.

  • ZenML MLOps Competition

    September 26th, 2022  |  Season 2  |  8 mins 13 secs
    competition, mlops, open-source, zenml

    So excited to be able to announce our :fire: AMAZING :fire: external judges for the ZenML Month of MLOps competition! We have a stellar panel of :sparkles: ML and MLOps heroes :sparkles: to help select the best pipelines from all of your submissions!

  • 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.