A fundamental flaw leaves LLMs strikingly vulnerable to attack
MIT Technology Review reports that 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…
For Australian readers, the useful question is what this changes in everyday work: costs, productivity, privacy, hiring, or the tools businesses rely on. We are watching this story because practical AI adoption is moving quickly, and the impact often reaches workplaces before policy or training catches up.
Why it matters
AI changes can quickly flow into the tools Australians use at work and at home. The practical impact is whether this saves time, raises costs, or creates new risks that businesses need to manage.
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