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Thoughtworks Technology Podcast
Themes from Technology Radar Vol.30
May 16, 2024
In this episode, they discuss open-ish source licenses, AI in software development, emerging architecture patterns for LLMs, and integrating pull requests with continuous integration. They explore the challenges and benefits of these themes, implications for software developers, and the impact of AI tools on coding processes and peer reviews.
44:55
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Quick takeaways
- Emerging architecture patterns for LLMs focus on retrieval augmented generation for large language models, enhancing code quality and observability.
- AI-assisted software development teams introduce coding assistants, like GitHub Co-pilot, improving development speed but raising concerns about code quality and deployment complexities.
Deep dives
Emerging Architecture Patterns for Large Language Models (LLMs)
Emerging architecture patterns for LLMs involve utilizing large language models in applications, with a focus on patterns like retrieval augmented generation (RAG). RAG allows infusing prompts with local context, avoiding full model fine-tuning by orchestrating prompts with additional data. Tools like Langfuse and Nemo Guardrails assist in monitoring, testing, and filtering responses, enhancing observability and code quality.
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