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Content provided by Justin Macorin and Bradley Arsenault. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Justin Macorin and Bradley Arsenault or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.
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Safely Exeuting LLM Code

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Manage episode 435300933 series 3519364
Content provided by Justin Macorin and Bradley Arsenault. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Justin Macorin and Bradley Arsenault or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.

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.
Check out PromptDesk.ai for an open-source prompt management tool.
Check out Brad’s AI Consultancy at bradleyarsenault.me
Add Justin Macorin and Bradley Arsenault on LinkedIn.
Please fill out our listener survey here to help us create a better podcast: https://docs.google.com/forms/d/e/1FAIpQLSfNjWlWyg8zROYmGX745a56AtagX_7cS16jyhjV2u_ebgc-tw/viewform?usp=sf_link


Hosted by Ausha. See ausha.co/privacy-policy for more information.

  continue reading

47 episodes

Artwork
iconShare
 
Manage episode 435300933 series 3519364
Content provided by Justin Macorin and Bradley Arsenault. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Justin Macorin and Bradley Arsenault or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.

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.

---
Continue listening to The Prompt Desk Podcast for everything LLM & GPT, Prompt Engineering, Generative AI, and LLM Security.
Check out PromptDesk.ai for an open-source prompt management tool.
Check out Brad’s AI Consultancy at bradleyarsenault.me
Add Justin Macorin and Bradley Arsenault on LinkedIn.
Please fill out our listener survey here to help us create a better podcast: https://docs.google.com/forms/d/e/1FAIpQLSfNjWlWyg8zROYmGX745a56AtagX_7cS16jyhjV2u_ebgc-tw/viewform?usp=sf_link


Hosted by Ausha. See ausha.co/privacy-policy for more information.

  continue reading

47 episodes

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