Building With AI cover image

Building With AI

Enabling startups to innovate with AI | Jason Liu (Independent Consultant)

Jan 29, 2024
Jason Liu, a seasoned AI operator and consultant, discusses general applications vs. AI applications, how developers should work with LLMs, what LLMOps companies need to focus on, why saying 'no' can improve AI's success rate, building agile AI systems, best practices for RAG systems, and more!
37:04

Episode guests

Podcast summary created with Snipd AI

Quick takeaways

  • Prioritizing tasks and dropping ineffective ones improves success rates and expands capabilities.
  • Dev tools like instructor simplify working with non-deterministic code, ensuring code quality in AI systems.

Deep dives

Improving Success Rate through Prioritization

By dropping tasks that cannot be effectively executed and prioritizing those that can, success rates can be significantly improved. This approach allows for a higher accuracy rate in completing tasks and opens up the opportunity to expand capabilities and explore new tasks. The focus is not on doing everything, but on fine-tuning existing capabilities and gradually incorporating new ones.

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