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    <title>Pipeline Conversations - Episodes Tagged with “Annotation”</title>
    <link>https://podcast.zenml.io/tags/annotation</link>
    <pubDate>Thu, 15 Sep 2022 10:00:00 +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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    <language>en-us</language>
    <itunes:type>episodic</itunes:type>
    <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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    <itunes:keywords>machine-learning, machinelearning, mlops, deeplearning, ai, artificialintelligence, artificial-intelligence, technology, tech, mlops, llmops</itunes:keywords>
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      <itunes:name>ZenML GmbH</itunes:name>
      <itunes:email>podcast@zenml.io</itunes:email>
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  <title>Data-centric Computer Vision with Eric Landau</title>
  <link>https://podcast.zenml.io/data-centric-computer-vision-eric-landau-encord</link>
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  <pubDate>Thu, 15 Sep 2022 10:00:00 +0200</pubDate>
  <author>ZenML GmbH</author>
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  <itunes:episodeType>full</itunes:episodeType>
  <itunes:season>2</itunes:season>
  <itunes:author>ZenML GmbH</itunes:author>
  <itunes:subtitle>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.</itunes:subtitle>
  <itunes:duration>51:51</itunes:duration>
  <itunes:explicit>no</itunes:explicit>
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  <description>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.
We also discuss the much-used term 'data-centric AI' and consider where it's useful and where perhaps there's a little bit of hype. We also get into some of the technical tradeoffs and decisions that come when building a platform. I'm really excited to get to present this episode to you today as I really enjoyed the discussion. Special Guest: Eric Landau.
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  <itunes:keywords>computer-vision, data-centric-ai, machine-learning, annotation, engineering</itunes:keywords>
  <content:encoded>
    <![CDATA[<p>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&#39;t an annotation tool per se, Eric and his team have tackled a bunch of quite complicated problems relating to that domain.</p>

<p>We also discuss the much-used term &#39;data-centric AI&#39; and consider where it&#39;s useful and where perhaps there&#39;s a little bit of hype. We also get into some of the technical tradeoffs and decisions that come when building a platform. I&#39;m really excited to get to present this episode to you today as I really enjoyed the discussion.</p><p>Special Guest: Eric Landau.</p><p>Links:</p><ul><li><a title="Eric Landau (LinkedIn)" rel="nofollow" href="https://www.linkedin.com/in/eric-landau-40992ab0/">Eric Landau (LinkedIn)</a></li><li><a title="Encord | The platform for data-centric computer vision" rel="nofollow" href="https://encord.com/">Encord | The platform for data-centric computer vision</a></li><li><a title="Encord blog" rel="nofollow" href="https://blog.encord.com/">Encord blog</a></li><li><a title="Encord (Github)" rel="nofollow" href="https://github.com/encord-team">Encord (Github)</a></li><li><a title="Encord (@encord_team) / Twitter" rel="nofollow" href="https://twitter.com/encord_team">Encord (@encord_team) / Twitter</a></li></ul>]]>
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  <itunes:summary>
    <![CDATA[<p>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&#39;t an annotation tool per se, Eric and his team have tackled a bunch of quite complicated problems relating to that domain.</p>

<p>We also discuss the much-used term &#39;data-centric AI&#39; and consider where it&#39;s useful and where perhaps there&#39;s a little bit of hype. We also get into some of the technical tradeoffs and decisions that come when building a platform. I&#39;m really excited to get to present this episode to you today as I really enjoyed the discussion.</p><p>Special Guest: Eric Landau.</p><p>Links:</p><ul><li><a title="Eric Landau (LinkedIn)" rel="nofollow" href="https://www.linkedin.com/in/eric-landau-40992ab0/">Eric Landau (LinkedIn)</a></li><li><a title="Encord | The platform for data-centric computer vision" rel="nofollow" href="https://encord.com/">Encord | The platform for data-centric computer vision</a></li><li><a title="Encord blog" rel="nofollow" href="https://blog.encord.com/">Encord blog</a></li><li><a title="Encord (Github)" rel="nofollow" href="https://github.com/encord-team">Encord (Github)</a></li><li><a title="Encord (@encord_team) / Twitter" rel="nofollow" href="https://twitter.com/encord_team">Encord (@encord_team) / Twitter</a></li></ul>]]>
  </itunes:summary>
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<item>
  <title>Humans in the Loop with Iva Gumnishka</title>
  <link>https://podcast.zenml.io/humans-in-loop-iva-gumnishka</link>
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  <pubDate>Thu, 23 Jun 2022 10:00:00 +0200</pubDate>
  <author>ZenML GmbH</author>
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  <itunes:episodeType>full</itunes:episodeType>
  <itunes:season>2</itunes:season>
  <itunes:author>ZenML GmbH</itunes:author>
  <itunes:subtitle>We were lucky to get to talk to [Iva Gumnishka](https://www.linkedin.com/in/ivagumnishka/), the founder of [Humans in the Loop](https://humansintheloop.org/). 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.</itunes:subtitle>
  <itunes:duration>50:55</itunes:duration>
  <itunes:explicit>no</itunes:explicit>
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  <description>In this episode, I'm really happy to be able to continue the dialogue we've been having with our users and community around the role of data annotation and labeling in MLOps.
We were lucky to get to talk to Iva Gumnishka (https://www.linkedin.com/in/ivagumnishka/), the founder of Humans in the Loop (https://humansintheloop.org/). 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.
Iva has a ton of experience working with annotation and has seen how different companies build this into their production machine learning lifecycles. We're continuing to work on a feature that will allow you to do this as part of your MLOps workflow when using ZenML, and I welcome any feedback you might have on the back of this podcast or the articles we've been publishing on the ZenML blog. Special Guest: Iva Gumnishka.
</description>
  <itunes:keywords>data-annotation, labeling, annotation, data, data-centric-ai, machine-learning</itunes:keywords>
  <content:encoded>
    <![CDATA[<p>In this episode, I&#39;m really happy to be able to continue the dialogue we&#39;ve been having with our users and community around the role of data annotation and labeling in MLOps.</p>

<p>We were lucky to get to talk to <a href="https://www.linkedin.com/in/ivagumnishka/" rel="nofollow">Iva Gumnishka</a>, the founder of <a href="https://humansintheloop.org/" rel="nofollow">Humans in the Loop</a>. 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.</p>

<p>Iva has a ton of experience working with annotation and has seen how different companies build this into their production machine learning lifecycles. We&#39;re continuing to work on a feature that will allow you to do this as part of your MLOps workflow when using ZenML, and I welcome any feedback you might have on the back of this podcast or the articles we&#39;ve been publishing on the ZenML blog.</p><p>Special Guest: Iva Gumnishka.</p><p>Links:</p><ul><li><a title="Humans in the Loop | Image annotation for ethical AI" rel="nofollow" href="https://humansintheloop.org/">Humans in the Loop | Image annotation for ethical AI</a></li><li><a title="Blog | Humans in the Loop" rel="nofollow" href="https://humansintheloop.org/resources/blog/">Blog | Humans in the Loop</a></li><li><a title="10 of the best open-source annotation tools for computer vision 2022 | Humans in the Loop" rel="nofollow" href="https://humansintheloop.org/10-of-the-best-open-source-annotation-tools-for-computer-vision-2022/">10 of the best open-source annotation tools for computer vision 2022 | Humans in the Loop</a></li><li><a title="zenml-io/awesome-open-data-annotation: Open Source Data Annotation &amp; Labeling Tools" rel="nofollow" href="https://github.com/zenml-io/awesome-open-data-annotation">zenml-io/awesome-open-data-annotation: Open Source Data Annotation &amp; Labeling Tools</a></li><li><a title="Need an open-source data annotation tool? We’ve got you covered! | ZenML Blog" rel="nofollow" href="https://blog.zenml.io/open-source-data-annotation-tools/">Need an open-source data annotation tool? We’ve got you covered! | ZenML Blog</a></li><li><a title="How to get the most out of data annotation | ZenML Blog" rel="nofollow" href="https://blog.zenml.io/data-labelling-annotation/">How to get the most out of data annotation | ZenML Blog</a></li><li><a title="Foundation | Humans in the Loop" rel="nofollow" href="https://humansintheloop.org/why-us/foundation/">Foundation | Humans in the Loop</a></li><li><a title="Your Data Needs a Human Touch. The story of Iva Gumnishka, a Bulgarian… | by Antoaneta Manko | womenintechglobal | Medium" rel="nofollow" href="https://medium.com/bulgarianwomenintech/your-data-needs-a-human-touch-5bc2ee70d548">Your Data Needs a Human Touch. The story of Iva Gumnishka, a Bulgarian… | by Antoaneta Manko | womenintechglobal | Medium</a></li></ul>]]>
  </content:encoded>
  <itunes:summary>
    <![CDATA[<p>In this episode, I&#39;m really happy to be able to continue the dialogue we&#39;ve been having with our users and community around the role of data annotation and labeling in MLOps.</p>

<p>We were lucky to get to talk to <a href="https://www.linkedin.com/in/ivagumnishka/" rel="nofollow">Iva Gumnishka</a>, the founder of <a href="https://humansintheloop.org/" rel="nofollow">Humans in the Loop</a>. 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.</p>

<p>Iva has a ton of experience working with annotation and has seen how different companies build this into their production machine learning lifecycles. We&#39;re continuing to work on a feature that will allow you to do this as part of your MLOps workflow when using ZenML, and I welcome any feedback you might have on the back of this podcast or the articles we&#39;ve been publishing on the ZenML blog.</p><p>Special Guest: Iva Gumnishka.</p><p>Links:</p><ul><li><a title="Humans in the Loop | Image annotation for ethical AI" rel="nofollow" href="https://humansintheloop.org/">Humans in the Loop | Image annotation for ethical AI</a></li><li><a title="Blog | Humans in the Loop" rel="nofollow" href="https://humansintheloop.org/resources/blog/">Blog | Humans in the Loop</a></li><li><a title="10 of the best open-source annotation tools for computer vision 2022 | Humans in the Loop" rel="nofollow" href="https://humansintheloop.org/10-of-the-best-open-source-annotation-tools-for-computer-vision-2022/">10 of the best open-source annotation tools for computer vision 2022 | Humans in the Loop</a></li><li><a title="zenml-io/awesome-open-data-annotation: Open Source Data Annotation &amp; Labeling Tools" rel="nofollow" href="https://github.com/zenml-io/awesome-open-data-annotation">zenml-io/awesome-open-data-annotation: Open Source Data Annotation &amp; Labeling Tools</a></li><li><a title="Need an open-source data annotation tool? We’ve got you covered! | ZenML Blog" rel="nofollow" href="https://blog.zenml.io/open-source-data-annotation-tools/">Need an open-source data annotation tool? We’ve got you covered! | ZenML Blog</a></li><li><a title="How to get the most out of data annotation | ZenML Blog" rel="nofollow" href="https://blog.zenml.io/data-labelling-annotation/">How to get the most out of data annotation | ZenML Blog</a></li><li><a title="Foundation | Humans in the Loop" rel="nofollow" href="https://humansintheloop.org/why-us/foundation/">Foundation | Humans in the Loop</a></li><li><a title="Your Data Needs a Human Touch. The story of Iva Gumnishka, a Bulgarian… | by Antoaneta Manko | womenintechglobal | Medium" rel="nofollow" href="https://medium.com/bulgarianwomenintech/your-data-needs-a-human-touch-5bc2ee70d548">Your Data Needs a Human Touch. The story of Iva Gumnishka, a Bulgarian… | by Antoaneta Manko | womenintechglobal | Medium</a></li></ul>]]>
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