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
LLMOps, Large Language Models in Production - HS#13