In Part 1, we established why LLMs are vulnerable: the attention mechanism treats all input tokens equally, with no architectural separation between trusted instructions and untrusted user data. Now ...

If you were trying to learn how to get other people to do what you want, you might use some of the techniques found in a book like Influence: The Power of Persuasion. Now, a pre-print study out of the ...

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 the prompt engineering advantages ...

LLM security testing for pentesters: map attacks to the OWASP LLM Top 10, break a vulnerable MCP server locally, and turn ...

Prompt injection attacks continue to present the most dangerous threat from large language models (LLMs), despite the relatively low number of recorded incidents relating to this vector, according to ...

I've been seeing people talk about local LLMs everywhere and praise the benefits, such as privacy wins, offline access, no API costs, and no data leaving your device. It sounded appealing on paper, ...

Nolen began their writing career in 2019, with three years dedicated to editing the Creative section at MakeUseOf. Their expertise lies at the crossroads of technology and creativity, covering areas ...

Using an LLM does not prevent copyright protection, but receiving an AI-generated answer does not create copyright ownership. Copyright follows human authorship. Once sufficient human authorship ...