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As a teenager, I remember being moved almost to tears by the sound of a family member chewing muesli. A friend eating dumplings once forced me to flee the room. The noises one former housemate makes when chomping popcorn mean I have declined their invitations to the cinema for nearly 20 years. I am not proud of myself for reacting like this – in fact, I am pretty embarrassed – but my responses feel unavoidable. It is probable that I have misophonia. According to a forthcoming scientific paper from King’s College London, so do 18% of people in the UK.

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When we ask investors about their realistic expectations for returns on their retirement portfolios, the answers are often anything but: “Anything from 10% at the bottom to 15% at the top” is a common response. Keeping in mind that the average stock market return is around 8% per year, as measured by the S&P 500 index, it’s easy to see why these scenarios, particularly at the higher end, are somewhat overly optimistic.

Rising theft is a serious problem for retailers across the U.S., with smaller and big businesses alike losing about $112 billion annually to shoplifters. But a recent survey by the Software Advice IT advisory firm says the heavy-handed defensive responses to “shrink” by larger outlets and chains may benefit smaller stores, as clients seek out buying experiences that don’t feel so much like prison lockdowns.

Capturing weak signals across endpoints and predicting potential intrusion attempt patterns is a perfect challenge for Large Language Models (LLMs) to take on. The goal is to mine attack data to find new threat patterns and correlations while fine-tuning LLMs and models. Leading endpoint detection and response (EDR) and extended detection and response (XDR) vendors are taking on the challenge.

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