As new large language models, or LLMs, are rapidly developed and deployed, existing methods for evaluating their safety and discovering potential vulnerabilities quickly become outdated. To identify ...
New tools for filtering malicious prompts, detecting ungrounded outputs, and evaluating the safety of models will make generative AI safer to use. Both extremely promising and extremely risky, ...
Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. Dany Lepage discusses the architectural ...
One of the important things in today’s day and age is digital safety and security. However, some tools come under scrutiny when it comes to maintaining the sanctity of the digital world, and MSTY LLM ...
Hosted on MSN
Microsoft boffins figured out how to break LLM safety guardrails with one simple prompt
A single, unlabeled training prompt can break LLMs' safety behavior, according to Microsoft Azure CTO Mark Russinovich and colleagues. They published a research paper that detailed how this prompt, ...
Sure, when chatbots aren’t outright hallucinating, they can be helpful tools for gathering information, generating ideas, and completing tasks. But some of the biggest players in the AI chatbot ...
Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More To scale up large language models (LLMs) in support of long-term AI ...
A subtle but revealing failure in large language model (LLM) behavior is drawing attention to a lesser-discussed risk: how safety mechanisms can unintentionally train models to produce outputs that ...
Results that may be inaccessible to you are currently showing.
Hide inaccessible results