Misinformation from LLMs poses a core vulnerability for applications relying on these models. Misinformation occurs when LLMs produce false or misleading information that appears credible. This vulnerability can lead to security breaches, reputational damage, and legal liability. One of the major causes of misinformation is hallucination—when the LLM generates content that seems accurate but is […]| OWASP Gen AI Security Project
Issue # 16 | Autonomous Agents are the next step in the evolution of LLM Apps. What is the state of the art, applications and current limitations?| newsletter.victordibia.com
Issue #12 | How to build tools for automatic data exploration, grammar-agnostic visualizations and infographics using Large Language Models like ChatGPT and GPT4.| newsletter.victordibia.com
Issue #11 | How can we make systems that integrate LLM's like ChatGPT more reliable? Here are practical techniques (and research) to mitigate hallucination and improve overall performance.| newsletter.victordibia.com