Open-source tools for AI safety now available from Meta

Open-source tools for AI safety now available from Meta

Meta has introduced Purple⁢ Llama, a project ⁤dedicated to creating open-source tools for ⁤developers⁣ to‌ evaluate and boost the trustworthiness and safety of generative‍ AI models before ‍they are​ used ⁤publicly.

Meta emphasized ⁣the need for collaborative efforts in ensuring ​AI safety, stating that AI‌ challenges​ cannot be tackled in‍ isolation. The company ⁤said the goal ​of Purple Llama is ⁤to establish a shared foundation for developing safer​ genAI ⁣as concerns mount about large language models and other AI technologies.

“The people building ⁢AI systems can’t address the challenges of AI ‍in a vacuum, which is ‌why we want to level the playing field and create ⁣a center of mass ⁣for open trust and safety,” Meta wrote in⁤ a blog post.

Gareth Lindahl-Wise, Chief Information ⁢Security ‌Officer at the cybersecurity firm Ontinue, called Purple Llama “a positive and proactive”‌ step towards safer AI.

“There will undoubtedly ​be some claims of virtue signaling ​or ulterior motives in gathering development onto a platform ‌– but in reality, better ‘out of the box’ consumer-level protection is going to be beneficial,” he ⁢added. “Entities with stringent internal, customer, or⁤ regulatory obligations will, of course, still need to follow robust evaluations, undoubtedly​ over and above the offering from Meta, but anything that can help reign in the potential Wild West is good for the⁤ ecosystem.”

The‍ project involves partnerships with AI ⁢developers; cloud‌ services like AWS and Google Cloud; semiconductor ​companies such as Intel, ⁤AMD, and Nvidia; and software firms ‍including ‌Microsoft.⁣ The collaboration aims to⁣ produce⁤ tools for both research⁣ and commercial use‍ to test AI models’ capabilities and ⁤identify safety risks.

The ‍first set of tools released through Purple Llama includes CyberSecEval, which assesses cybersecurity risks in AI-generated software. It‌ features a language model that identifies inappropriate or harmful text, including discussions of violence or illegal activities. Developers can use CyberSecEval to test ‌if their ​AI models are⁢ prone to creating insecure ⁢code or aiding cyberattacks. Meta’s research has found that large‌ language models often suggest vulnerable code, ​highlighting the importance of continuous testing and improvement for AI security.

Llama Guard is another tool in this suite, a⁢ large language model trained to identify potentially harmful⁤ or offensive language. Developers can ⁣use Llama Guard to ‌test if their models produce or⁣ accept‍ unsafe⁤ content, helping to filter out prompts that​ might lead to⁣ inappropriate outputs.

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2023-12-08 16:41:04
Link from www.infoworld.com rnrn

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