The Application Security Podcast
Steve Wilson -- The Developer's Playbook for Large Language Model Security: Building Secure AI Applications
Oct 1, 2024
Steve Wilson, author of 'The Developer's Playbook for Large Language Model Security,' dives into the complexities of AI and security. He discusses AI hallucinations and the crucial need for trust in AI applications. Steve shares insights on supply chain vulnerabilities and the importance of strict oversight and testing tools. He also explores the interplay between personal hobbies and security strategies, emphasizing innovative approaches in AppSec leveraging AI to enhance vulnerability management. Expect practical tips for building secure AI applications!
36:32
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Quick takeaways
- AI hallucinations present a significant challenge for developers, emphasizing the need for improved accuracy through solutions like retrieval augmented generation and prompt engineering.
- Trust in large language models is essential for organizations, necessitating strict data usage policies and security protocols to safeguard against potential vulnerabilities.
Deep dives
Understanding AI Hallucinations
AI hallucinations occur when large language models (LLMs) produce incorrect or misleading information despite sounding plausible. This phenomenon arises due to the statistical nature of these models, which generate responses based on patterns learned during training rather than strict algorithms. Users may find it challenging to assess the reliability of these answers, as the models can provide responses without indicating their uncertainty. Solutions like retrieval augmented generation (RAG) and prompt engineering can improve accuracy, but hallucinations inherently remain a part of LLM interactions.
