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LLMOps, Large Language Models in Production - HS#13

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Manage episode 426633082 series 3558558
Content provided by Miko Pawlikowski. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Miko Pawlikowski 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://player.fm/legal.

Understanding LLMOps: Differentiating from MLOps with Abi Aryan

Join Miko Pawlikowski on this episode of HockeyStick as he interviews Abi Aryan, a leading expert and author on Large Language Model Operations (LLMOps), to distinguish it from Machine Learning Operations (MLOps) and Machine Learning Engineering (MLE). Abi delves into the challenges and unique requirements of managing generative models in production, discusses the evolution and future of LLMOps, and shares insights into her upcoming book, 'LLMOps: Managing Large Language Models in Production.' Gain understanding on safety, scalability, robustness, and the lifecycle of LLMs, and learn practical steps to effectively deploy and monitor these advanced models.

00:00 Introduction

1:11 Generative vs. Discriminative Models

1:58 Challenges in LLMOps

2:12 The Shift to Task-Agnostic Software

2:50 Fine-Tuning and Prompt Engineering

4:37 The Origin of LLMOps

13:20 Safety, Scalability, and Robustness in LLMOps

29:40 Dynamic Model Adaptation

30:37 Challenges of Static Models

31:42 Improving Model Performance

32:20 Introducing a New Framework

34:06 Lifecycle of an LLM in Production

35:29 Data Engineering and Evaluation

37:06 Orchestration and Security

47:51 Future Predictions and Concerns

48:46 Impact on Jobs and Society

55:06 Risks and Ethical Considerations

59:11 Industry Trends and Monopolies

01:00:52 Conclusion and Contact Information


This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit www.hockeystick.show
  continue reading

30 episodes

Artwork
iconShare
 
Manage episode 426633082 series 3558558
Content provided by Miko Pawlikowski. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Miko Pawlikowski 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://player.fm/legal.

Understanding LLMOps: Differentiating from MLOps with Abi Aryan

Join Miko Pawlikowski on this episode of HockeyStick as he interviews Abi Aryan, a leading expert and author on Large Language Model Operations (LLMOps), to distinguish it from Machine Learning Operations (MLOps) and Machine Learning Engineering (MLE). Abi delves into the challenges and unique requirements of managing generative models in production, discusses the evolution and future of LLMOps, and shares insights into her upcoming book, 'LLMOps: Managing Large Language Models in Production.' Gain understanding on safety, scalability, robustness, and the lifecycle of LLMs, and learn practical steps to effectively deploy and monitor these advanced models.

00:00 Introduction

1:11 Generative vs. Discriminative Models

1:58 Challenges in LLMOps

2:12 The Shift to Task-Agnostic Software

2:50 Fine-Tuning and Prompt Engineering

4:37 The Origin of LLMOps

13:20 Safety, Scalability, and Robustness in LLMOps

29:40 Dynamic Model Adaptation

30:37 Challenges of Static Models

31:42 Improving Model Performance

32:20 Introducing a New Framework

34:06 Lifecycle of an LLM in Production

35:29 Data Engineering and Evaluation

37:06 Orchestration and Security

47:51 Future Predictions and Concerns

48:46 Impact on Jobs and Society

55:06 Risks and Ethical Considerations

59:11 Industry Trends and Monopolies

01:00:52 Conclusion and Contact Information


This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit www.hockeystick.show
  continue reading

30 episodes

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