web01.fireside.fm Thu, 23 Apr 2026 07:09:42 -0500 Fireside (https://fireside.fm) Pipeline Conversations - Episodes Tagged with “Data” https://podcast.zenml.io/tags/data Thu, 04 Aug 2022 10:00:00 +0200 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. en-us episodic MLOps and LLMOps, from the trenches ZenML GmbH 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. no machine-learning, machinelearning, mlops, deeplearning, ai, artificialintelligence, artificial-intelligence, technology, tech, mlops, llmops ZenML GmbH podcast@zenml.io Safe and Testable Computer Vision with Lakera https://podcast.zenml.io/safe-testable-computer-vision-lakera 6300d5ea-04f5-45a5-8c81-ca184b3d5bd4 Thu, 04 Aug 2022 10:00:00 +0200 ZenML GmbH full 2 ZenML GmbH 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. 57:32 no This week I spoke with Mateo Rojas-Carulla, the CTO and a co-founder of Lakera (https://www.lakera.ai/) and Matthias Kraft, also a co-founder and the CPO there. Lakera (https://www.lakera.ai/) 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. We discuss how they think about the testing of machine learning models, and about how having this safety element upfront has implications for how you go about the testing and ensuring robustness. We specifically dive into how to go about testing computer vision models and the various pitfalls that are to be found in that domain. Special Guests: Mateo Rojas-Carulla and Matthias Kraft. mlops, monitoring, data, machine-learning, computer-vision, testing, safety 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.

We discuss how they think about the testing of machine learning models, and about how having this safety element upfront has implications for how you go about the testing and ensuring robustness. We specifically dive into how to go about testing computer vision models and the various pitfalls that are to be found in that domain.

Special Guests: Mateo Rojas-Carulla and Matthias Kraft.

]]> 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.

We discuss how they think about the testing of machine learning models, and about how having this safety element upfront has implications for how you go about the testing and ensuring robustness. We specifically dive into how to go about testing computer vision models and the various pitfalls that are to be found in that domain.

Special Guests: Mateo Rojas-Carulla and Matthias Kraft.

]]> ML Monitoring with Emeli Dral https://podcast.zenml.io/monitoring-evidently-emeli-dral 57e441f1-021f-42f6-b676-fd8077e4eca1 Thu, 07 Jul 2022 11:00:00 +0200 ZenML GmbH full 2 ZenML GmbH 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. 46:57 no 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. We discussed the challenges around building a tool that is both straightforward to use while also customisable and powerful. We also got into the thinking behind how they grew their community and blog along the way. Special Guest: Emeli Dral. mlops, monitoring, data, machine-learning 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.

We discussed the challenges around building a tool that is both straightforward to use while also customisable and powerful. We also got into the thinking behind how they grew their community and blog along the way.

Special Guest: Emeli Dral.

Links:

]]> 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.

We discussed the challenges around building a tool that is both straightforward to use while also customisable and powerful. We also got into the thinking behind how they grew their community and blog along the way.

Special Guest: Emeli Dral.

Links:

]]> Humans in the Loop with Iva Gumnishka https://podcast.zenml.io/humans-in-loop-iva-gumnishka 2b5720f5-ce03-4cd5-a077-87780513ee1d Thu, 23 Jun 2022 10:00:00 +0200 ZenML GmbH full 2 ZenML GmbH 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. 50:55 no 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. data-annotation, labeling, annotation, data, data-centric-ai, machine-learning 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, 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.

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.

Links:

]]> 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, 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.

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.

Links:

]]>