Safely Executing LLM Code
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Safely Executing LLM Code
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In this episode, AI experts Bradley Arsenault and Justin Macon dive deep into the challenges and best practices for safely executing code generated by large language models in a production environment. They discuss key security considerations, containerization techniques, static/dynamic code analysis, and error handling - providing valuable insights for anyone looking to leverage the power of LLMs while mitigating the risks of abuse by AI hackers.
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Continue listening to The Prompt Desk Podcast for everything LLM & GPT, Prompt Engineering, Generative AI, and LLM Security.
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