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Beers & Bytes Podcast and Bytes Podcast에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 Beers & Bytes Podcast and Bytes Podcast 또는 해당 팟캐스트 플랫폼 파트너가 직접 업로드하고 제공합니다. 누군가가 귀하의 허락 없이 귀하의 저작물을 사용하고 있다고 생각되는 경우 여기에 설명된 절차를 따르실 수 있습니다 https://ko.player.fm/legal.
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Revolutionizing MLOps: Gorka Erkand on Jozu's Game-Changing Solutions for AI Integration

39:11
 
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Manage episode 445740764 series 2811624
Beers & Bytes Podcast and Bytes Podcast에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 Beers & Bytes Podcast and Bytes Podcast 또는 해당 팟캐스트 플랫폼 파트너가 직접 업로드하고 제공합니다. 누군가가 귀하의 허락 없이 귀하의 저작물을 사용하고 있다고 생각되는 경우 여기에 설명된 절차를 따르실 수 있습니다 https://ko.player.fm/legal.

What if the key to overcoming AI and ML integration challenges in enterprises lies with one visionary company? Join us as we chat with Gorka Erkand, the CTO of Jozu, who is spearheading efforts to revolutionize the MLOps landscape. Gorka shares his insights on how Jozu's open-source project, KitApps, could be the game-changer in seamlessly packaging AI and ML artifacts. As we enjoy our beers, Gorka opens up about Jozu's strategic use of the Open Container Initiative (OCI) and their innovative Jozu Hub, which together aim to redefine the AI and ML experiences for enterprises, making such integrations a reality rather than a distant goal.
Navigating the complexities of managing large language models (LLMs) and their datasets is no small feat. We explore how Jozu tackles these issues head-on, emphasizing the critical aspects of data versioning, integrity, and security. Discover how custom checksums, data snapshots, and software bills of materials (SBOMs) play a vital role in safeguarding the authenticity and transparency of AI systems. Gorka also highlights the significant advancements Jozu is making in vulnerability scanning and deployment processes, with exciting features like packaging Jupyter Notebooks into microservice containers for easy deployment. Unpack the intricacies of model drift monitoring and the implementation of guardrails, ensuring robust and reliable AI and ML systems that can stand the test of time.

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챕터

1. AI and ML DevOps Challenges (00:00:00)

2. Managing Large Model and Data Sets (00:12:12)

3. AI ML Vulnerability Scanning and Deployment (00:21:40)

31 에피소드

Artwork
icon공유
 
Manage episode 445740764 series 2811624
Beers & Bytes Podcast and Bytes Podcast에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 Beers & Bytes Podcast and Bytes Podcast 또는 해당 팟캐스트 플랫폼 파트너가 직접 업로드하고 제공합니다. 누군가가 귀하의 허락 없이 귀하의 저작물을 사용하고 있다고 생각되는 경우 여기에 설명된 절차를 따르실 수 있습니다 https://ko.player.fm/legal.

What if the key to overcoming AI and ML integration challenges in enterprises lies with one visionary company? Join us as we chat with Gorka Erkand, the CTO of Jozu, who is spearheading efforts to revolutionize the MLOps landscape. Gorka shares his insights on how Jozu's open-source project, KitApps, could be the game-changer in seamlessly packaging AI and ML artifacts. As we enjoy our beers, Gorka opens up about Jozu's strategic use of the Open Container Initiative (OCI) and their innovative Jozu Hub, which together aim to redefine the AI and ML experiences for enterprises, making such integrations a reality rather than a distant goal.
Navigating the complexities of managing large language models (LLMs) and their datasets is no small feat. We explore how Jozu tackles these issues head-on, emphasizing the critical aspects of data versioning, integrity, and security. Discover how custom checksums, data snapshots, and software bills of materials (SBOMs) play a vital role in safeguarding the authenticity and transparency of AI systems. Gorka also highlights the significant advancements Jozu is making in vulnerability scanning and deployment processes, with exciting features like packaging Jupyter Notebooks into microservice containers for easy deployment. Unpack the intricacies of model drift monitoring and the implementation of guardrails, ensuring robust and reliable AI and ML systems that can stand the test of time.

Send us a text

Support the show

  continue reading

챕터

1. AI and ML DevOps Challenges (00:00:00)

2. Managing Large Model and Data Sets (00:12:12)

3. AI ML Vulnerability Scanning and Deployment (00:21:40)

31 에피소드

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