July 17, 2024 at 08:58AM
MLCommons plans to run stress tests on large language models to gauge the safety of their responses. The AI Safety suite will assess the models’ output in categories like hate speech and exploitation. By providing safety ratings, the benchmark aims to guide companies and organizations in selecting AI systems, with plans to expand beyond text to other media.
From the meeting notes, here are the key takeaways:
1. MLCommons, an AI consortium with members like Google, Microsoft, and Meta, has announced an AI Safety benchmark that will run stress tests on large language models (LLMs) to assess whether they produce unsafe responses. The benchmarked LLMs will be given safety ratings to inform customers about the risks.
2. The AI Safety suite will use text questions to elicit responses related to hate speech, exploitation, child abuse, sex crimes, intellectual property violations, and defamation. The responses will be rated as safe or unsafe.
3. These benchmarks can be used by companies, governments, and nonprofits to identify weaknesses in AI systems and provide feedback to make changes in LLMs.
4. MLCommons aims to release a stable version 1.0 of the AI Safety benchmark by October 31.
5. There is growing concern about the safety of AI systems, with MLCommons spokeswoman Kelly Berschauer emphasizing the need for industry-standard safety testing.
6. The initial benchmark focuses on grading the safety of chatbot-style LLMs but may expand to include image and video generation in the future.
7. Researchers have highlighted the challenge of keeping up with safety in AI due to the rapid pace of change, with concerns about potential poisoning of AI models with bad data or malicious models.
Please let me know if you need more information or further details on any specific points.