Contrary to long-held beliefs that attacking or contaminating large language models (LLMs) requires enormous volumes of malicious data, new research from AI startup Anthropic, conducted in ...
For hackers, the stolen data would be useless, but authorized users would have a secret key that filters out the fake ...
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Anthropic study reveals it's actually even easier to poison LLM training data than first thought
Claude-creator Anthropic has found that it's actually easier to 'poison' Large Language Models than previously thought. In a recent blog post, Anthropic explains that as few as "250 malicious ...
When researchers at software management company, JFrog, routinely scanned AI/ML models uploaded to Hugging Face earlier this year, the discovery of a hundred malicious models put the spotlight on an ...
Large language models (LLMs) have the potential to be security teams’ digital best friends. But today, LLMs are more likely to be the friend that gets you into trouble. Trouble, as in, data poisoning, ...
Forbes contributors publish independent expert analyses and insights. Dr. Lance B. Eliot is a world-renowned AI scientist and consultant. In today’s column, I examine an important discovery that ...
A hot potato: A new study from New York University further highlights a critical issue: the vulnerability of large language models to misinformation. The research reveals that even a minuscule amount ...
It’s pretty easy to see the problem here: The Internet is brimming with misinformation, and most large language models are trained on a massive body of text obtained from the Internet. Ideally, having ...
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