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Sisällön tarjoaa Kubernetes Bytes, Ryan Wallner, and Bhavin Shah. Kubernetes Bytes, Ryan Wallner, and Bhavin Shah tai sen podcast-alustan kumppani lataa ja toimittaa kaiken podcast-sisällön, mukaan lukien jaksot, grafiikat ja podcast-kuvaukset. Jos uskot jonkun käyttävän tekijänoikeudella suojattua teostasi ilman lupaasi, voit seurata tässä https://fi.player.fm/legal kuvattua prosessia.
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Inference in Action: Scaling Al Smarter with Inferless

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Sisällön tarjoaa Kubernetes Bytes, Ryan Wallner, and Bhavin Shah. Kubernetes Bytes, Ryan Wallner, and Bhavin Shah tai sen podcast-alustan kumppani lataa ja toimittaa kaiken podcast-sisällön, mukaan lukien jaksot, grafiikat ja podcast-kuvaukset. Jos uskot jonkun käyttävän tekijänoikeudella suojattua teostasi ilman lupaasi, voit seurata tässä https://fi.player.fm/legal kuvattua prosessia.

In this episode, we sit down with Nilesh Agarwal, co-founder of Inferless, a platform designed to streamline serverless GPU inference. We’ll cover the evolving landscape of model deployment, explore open-source tools like KServe and Knative, and discuss how Inferless solves common bottlenecks, such as cold starts and scaling issues. We also take a closer look at real-world examples like CleanLab, who saved 90% on GPU costs using Inferless.

Whether you’re a developer, DevOps engineer, or tech enthusiast curious about the latest in AI infrastructure, this podcast offers insights into Kubernetes-based model deployment, efficient updates, and the future of serverless ML. Tune in to hear Nilesh's journey from Amazon to founding Inferless and how his platform is transforming the way companies deploy machine learning models.

Subscribe now for more episodes!
Show Links:

Inferless LInks:

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Fetch error

Hmmm there seems to be a problem fetching this series right now. Last successful fetch was on March 03, 2025 17:11 (9M ago)

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Manage episode 446638123 series 3332465
Sisällön tarjoaa Kubernetes Bytes, Ryan Wallner, and Bhavin Shah. Kubernetes Bytes, Ryan Wallner, and Bhavin Shah tai sen podcast-alustan kumppani lataa ja toimittaa kaiken podcast-sisällön, mukaan lukien jaksot, grafiikat ja podcast-kuvaukset. Jos uskot jonkun käyttävän tekijänoikeudella suojattua teostasi ilman lupaasi, voit seurata tässä https://fi.player.fm/legal kuvattua prosessia.

In this episode, we sit down with Nilesh Agarwal, co-founder of Inferless, a platform designed to streamline serverless GPU inference. We’ll cover the evolving landscape of model deployment, explore open-source tools like KServe and Knative, and discuss how Inferless solves common bottlenecks, such as cold starts and scaling issues. We also take a closer look at real-world examples like CleanLab, who saved 90% on GPU costs using Inferless.

Whether you’re a developer, DevOps engineer, or tech enthusiast curious about the latest in AI infrastructure, this podcast offers insights into Kubernetes-based model deployment, efficient updates, and the future of serverless ML. Tune in to hear Nilesh's journey from Amazon to founding Inferless and how his platform is transforming the way companies deploy machine learning models.

Subscribe now for more episodes!
Show Links:

Inferless LInks:

  continue reading

88 jaksoa

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