MLCommons, in collaboration with other entities, has unveiled a new AI Safety benchmark to assess LLM risks like aiding crimes and generating hate speech. This benchmark represents a significant step in standardizing AI safety evaluation.
๐ค From this week's issue: The MLCommons AI Safety working group achieved an important first step towards standardization with the release of the AI Safety v0.5 benchmark proof-of-concept. https://t.co/Imns8uy8sK
Benchmarks are how we make progress in AI, for metrics that we care about. But the LLMs we hear about every day aren't yet evaluated for predicting future events. This leaderboard, built with @valoryag and @autonolas, is our first step towards improved prediction machines. Checkโฆ https://t.co/Lwn2cjiTw0
For years @MLCommons has made benchmarks to assess AI models' performance. Now it's unveiling its first benchmark for AI safety. It assesses LLM risks such as helping with crimes and producing hate speech. https://t.co/H4PId9ilgb
We are excited to announce the release of an @MLCommons AI Safety benchmark POC. Built through an inclusive decision-making and engineering process, the POC validates our approach to a v1.0 AI Safety benchmark suite. Learn more: https://t.co/LmEKYS05ME #AI, #benchmarks
Now @jjding99 has come through with a translation of this "authoritative" AI safety benchmark: https://t.co/knl0BP47Jg https://t.co/1USDsftZ18
Advancing AI Safety: Innovations in Toxic Response Mitigation #AI #artificialintelligence #benchmarks #Chatbots #Cybersecurity #llm #machinelearning #redteaming #risks #toxic https://t.co/uszHMHaYkZ https://t.co/9Vyz3JS19J
ai safety is no joke, y'all! https://t.co/yRhmvDSiqw