April 14, 2024, 5:26 a.m. | Dr. Tony Hoang

The Artificial Intelligence Podcast linktr.ee

MIT researchers have developed a new machine learning technique to enhance the red-teaming process, which involves testing AI models for safety. The approach involves using curiosity-driven exploration to encourage the generation of diverse and novel prompts that expose potential weaknesses in AI systems. This method has proven to be more effective than traditional techniques, producing a wider range of toxic responses and improving the robustness of AI safety measures. The researchers aim to enable the red-team model to generate prompts …

ai models ai systems curiosity diverse exploration machine machine learning mit mit researchers novel process prompts researchers safety systems testing

AI Research Scientist

@ Vara | Berlin, Germany and Remote

Data Architect

@ University of Texas at Austin | Austin, TX

Data ETL Engineer

@ University of Texas at Austin | Austin, TX

Lead GNSS Data Scientist

@ Lurra Systems | Melbourne

Data Science Analyst

@ Mayo Clinic | AZ, United States

Sr. Data Scientist (Network Engineering)

@ SpaceX | Redmond, WA