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    <title>Pipeline Conversations - Episodes Tagged with “Platforms”</title>
    <link>https://podcast.zenml.io/tags/platforms</link>
    <pubDate>Mon, 05 Sep 2022 09:00:00 +0200</pubDate>
    <description>Pipeline Conversations brings you interviews with platform engineers, ML practitioners, and technical leaders building production AI systems. We dig into the real challenges of MLOps and LLMOps: orchestrating complex workflows on Kubernetes, fine-tuning and evaluating models at scale, and shipping AI that actually works. From ZenML.
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    <itunes:subtitle>MLOps and LLMOps, from the trenches</itunes:subtitle>
    <itunes:author>ZenML GmbH</itunes:author>
    <itunes:summary>Pipeline Conversations brings you interviews with platform engineers, ML practitioners, and technical leaders building production AI systems. We dig into the real challenges of MLOps and LLMOps: orchestrating complex workflows on Kubernetes, fine-tuning and evaluating models at scale, and shipping AI that actually works. From ZenML.
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  <title>ML Abstractions with Phil Howes</title>
  <link>https://podcast.zenml.io/ml-abstractions-phil-howes</link>
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  <pubDate>Mon, 05 Sep 2022 09:00:00 +0200</pubDate>
  <author>ZenML GmbH</author>
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  <itunes:author>ZenML GmbH</itunes:author>
  <itunes:subtitle>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.</itunes:subtitle>
  <itunes:duration>54:13</itunes:duration>
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  <description>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.
We got into some of the big challenges he had working to build out the platform, as well as the core issue of iteration speed that motivates why they're building BaseTen.
Phil has experienced quite a few of the industry's end-to-end patterns in the years that he's been working on machine learning and it was great to have that context inform the conversation, too. Special Guest: Phil Howes.
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  <itunes:keywords>mlops, machine-learning, data-science, ai,  infrastructure, pipelines, tools, platforms</itunes:keywords>
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    <![CDATA[<p>This week we dive into the abstractions that we&#39;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.</p>

<p>We got into some of the big challenges he had working to build out the platform, as well as the core issue of iteration speed that motivates why they&#39;re building BaseTen.</p>

<p>Phil has experienced quite a few of the industry&#39;s end-to-end patterns in the years that he&#39;s been working on machine learning and it was great to have that context inform the conversation, too.</p><p>Special Guest: Phil Howes.</p><p>Links:</p><ul><li><a title="Baseten | Turn ML models into full-stack apps" rel="nofollow" href="https://www.baseten.co/">Baseten | Turn ML models into full-stack apps</a></li><li><a title="Welcome to Baseten! - Baseten" rel="nofollow" href="https://docs.baseten.co/">Welcome to Baseten! - Baseten</a></li><li><a title="Blog | Baseten" rel="nofollow" href="https://www.baseten.co/blog">Blog | Baseten</a></li><li><a title="Gallery | Baseten" rel="nofollow" href="https://www.baseten.co/gallery">Gallery | Baseten</a></li><li><a title="basetenlabs/truss: Serve any model without boilerplate code" rel="nofollow" href="https://github.com/basetenlabs/truss">basetenlabs/truss: Serve any model without boilerplate code</a></li><li><a title="Baseten" rel="nofollow" href="https://github.com/basetenlabs">Baseten</a></li><li><a title="Phil Howes (LinkedIn)" rel="nofollow" href="https://www.linkedin.com/in/philhowes/">Phil Howes (LinkedIn)</a></li></ul>]]>
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    <![CDATA[<p>This week we dive into the abstractions that we&#39;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.</p>

<p>We got into some of the big challenges he had working to build out the platform, as well as the core issue of iteration speed that motivates why they&#39;re building BaseTen.</p>

<p>Phil has experienced quite a few of the industry&#39;s end-to-end patterns in the years that he&#39;s been working on machine learning and it was great to have that context inform the conversation, too.</p><p>Special Guest: Phil Howes.</p><p>Links:</p><ul><li><a title="Baseten | Turn ML models into full-stack apps" rel="nofollow" href="https://www.baseten.co/">Baseten | Turn ML models into full-stack apps</a></li><li><a title="Welcome to Baseten! - Baseten" rel="nofollow" href="https://docs.baseten.co/">Welcome to Baseten! - Baseten</a></li><li><a title="Blog | Baseten" rel="nofollow" href="https://www.baseten.co/blog">Blog | Baseten</a></li><li><a title="Gallery | Baseten" rel="nofollow" href="https://www.baseten.co/gallery">Gallery | Baseten</a></li><li><a title="basetenlabs/truss: Serve any model without boilerplate code" rel="nofollow" href="https://github.com/basetenlabs/truss">basetenlabs/truss: Serve any model without boilerplate code</a></li><li><a title="Baseten" rel="nofollow" href="https://github.com/basetenlabs">Baseten</a></li><li><a title="Phil Howes (LinkedIn)" rel="nofollow" href="https://www.linkedin.com/in/philhowes/">Phil Howes (LinkedIn)</a></li></ul>]]>
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