A fundamental flaw leaves LLMs strikingly vulnerable to attack
Quick summary
It is impossible to make large language models fully secure against hacks because of a fundamental flaw in how they work, a team of researchers argue in a paper presented at the International Conference on Machine Learning, a top AI conference, this month. The claim has huge implications for the safety of this technology, which…
Key takeaways
- It is impossible to make large language models fully secure against hacks because of a fundamental flaw in how they work, a team of researchers argue in a paper presented at the International Conference on Machine Learning, a top AI conference, this month.
- The claim has huge implications for the safety of this technology, which…
Why it matters
“A fundamental flaw leaves LLMs strikingly vulnerable to attack” shows why AI risk cannot be reduced to answer accuracy. Access controls, logging, human approval and incident response need to be designed into the workflow from the start.
