Fine-Tuning for Success
Sunil emphasizes the importance of well-defined API interfaces in building scalable systems, highlighting that clear roles and boundaries can significantly reduce failure rates. He advocates for fine-tuning models to enhance controllability and reliability, ensuring that developers can expect consistent outputs. This approach addresses the common pitfalls of using generic LLMs, leading to a more dependable workflow.In this clip
From this podcast
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
An Agentic Mixture of Experts for DevOps with Sunil Mallya - 708
Related Questions
How will large language models (LLMs) and AI change software engineering and the software development lifecycle (SDLC) as discussed in the episode Shreya Rajpal: Guardrails AI, AI Production Challenges, & AI Reliability | Around the Prompt #9 and the clip AI Validation Insights?
How will large language models (LLMs) and AI change software engineering and the software development lifecycle (SDLC) as discussed in the episode Making Your Company LLM-native // Francisco Ingham // #266 and the clip Enhancing, Not Replacing?
How will large language models (LLMs) and AI change software engineering and the software development lifecycle (SDLC) as discussed in the episode Shreya Rajpal: Guardrails AI, AI Production Challenges, & AI Reliability | Around the Prompt #9 and the clip AI Validation Insights?