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Redefining AI Infrastructure: Open-Source, Chips, and the Future Beyond Kubernetes – Andrey Cheptsov

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Manage episode 464263663 series 2831626
Content provided by DataTalks.Club. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by DataTalks.Club or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://podcastplayer.com/legal.

In this podcast episode, we talked with Andrey Cheptsov about ​The future of AI infrastructure.

About the Speaker:

Andrey Cheptsov is the founder and CEO of dstack, an open-source alternative to Kubernetes and Slurm, built to simplify the orchestration of AI infrastructure. Before dstack, Andrey worked at JetBrains for over a decade helping different teams make the best developer tools.

During the event, the guest, Andrey Cheptsov, founder and CEO of dstack, discussed the complexities of AI infrastructure. We explore topics like the challenges of using Kubernetes for AI workloads, the need to rethink container orchestration, and the future of hybrid and cloud-only infrastructures. Andrey also shares insights into the role of on-premise and bare-metal solutions, edge computing, and federated learning.

00:00 Andrey's Career Journey: From JetBrains to DStack

5:00 The Motivation Behind DStack

7:00 Challenges in Machine Learning Infrastructure

10:00 Transitioning from Cloud to On-Prem Solutions

14:30 Reflections on OpenAI's Evolution

17:30 Open Source vs Proprietary Models: A Balanced Perspective

21:01 Monolithic vs. Decentralized AI businesses

22:05 The role of privacy and control in AI for industries like banking and healthcare

30:00 Challenges in training large AI models: GPUs and distributed systems

37:03 DeepSpeed's efficient training approach vs. brute force methods

39:00 Challenges for small and medium businesses: hosting and fine-tuning models

47:01 Managing Kubernetes challenges for AI teams

52:00 Hybrid vs. cloud-only infrastructure

56:03 On-premise vs. bare-metal solutions

58:05 Exploring edge computing and its challenges

🔗 CONNECT WITH ANDREY CHEPTSOV

Twitter - / andrey_cheptsov

Linkedin - / andrey-cheptsov

GitHub - https://github.com/dstackai/dstack/

Website - https://dstack.ai/

🔗 CONNECT WITH DataTalksClub

Join DataTalks.Club:⁠⁠⁠https://datatalks.club/slack.html⁠⁠⁠

Our events:⁠⁠⁠https://datatalks.club/events.html⁠⁠⁠

Datalike Substack -⁠⁠⁠https://datalike.substack.com/⁠⁠⁠

LinkedIn:⁠⁠⁠ / datatalks-club ⁠

  continue reading

183 episodes

Artwork
iconShare
 
Manage episode 464263663 series 2831626
Content provided by DataTalks.Club. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by DataTalks.Club or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://podcastplayer.com/legal.

In this podcast episode, we talked with Andrey Cheptsov about ​The future of AI infrastructure.

About the Speaker:

Andrey Cheptsov is the founder and CEO of dstack, an open-source alternative to Kubernetes and Slurm, built to simplify the orchestration of AI infrastructure. Before dstack, Andrey worked at JetBrains for over a decade helping different teams make the best developer tools.

During the event, the guest, Andrey Cheptsov, founder and CEO of dstack, discussed the complexities of AI infrastructure. We explore topics like the challenges of using Kubernetes for AI workloads, the need to rethink container orchestration, and the future of hybrid and cloud-only infrastructures. Andrey also shares insights into the role of on-premise and bare-metal solutions, edge computing, and federated learning.

00:00 Andrey's Career Journey: From JetBrains to DStack

5:00 The Motivation Behind DStack

7:00 Challenges in Machine Learning Infrastructure

10:00 Transitioning from Cloud to On-Prem Solutions

14:30 Reflections on OpenAI's Evolution

17:30 Open Source vs Proprietary Models: A Balanced Perspective

21:01 Monolithic vs. Decentralized AI businesses

22:05 The role of privacy and control in AI for industries like banking and healthcare

30:00 Challenges in training large AI models: GPUs and distributed systems

37:03 DeepSpeed's efficient training approach vs. brute force methods

39:00 Challenges for small and medium businesses: hosting and fine-tuning models

47:01 Managing Kubernetes challenges for AI teams

52:00 Hybrid vs. cloud-only infrastructure

56:03 On-premise vs. bare-metal solutions

58:05 Exploring edge computing and its challenges

🔗 CONNECT WITH ANDREY CHEPTSOV

Twitter - / andrey_cheptsov

Linkedin - / andrey-cheptsov

GitHub - https://github.com/dstackai/dstack/

Website - https://dstack.ai/

🔗 CONNECT WITH DataTalksClub

Join DataTalks.Club:⁠⁠⁠https://datatalks.club/slack.html⁠⁠⁠

Our events:⁠⁠⁠https://datatalks.club/events.html⁠⁠⁠

Datalike Substack -⁠⁠⁠https://datalike.substack.com/⁠⁠⁠

LinkedIn:⁠⁠⁠ / datatalks-club ⁠

  continue reading

183 episodes

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