This paper examines the efficacy of utilizing large language models (LLMs) to detect public threats posted online. Amid rising concerns over the spread of threatening rhetoric and advance notices of violence, automated content analysis techniques may aid in early identification and moderation. Custom data collection tools were developed to amass post titles from a popular Korean online community, comprising 500 non-threat examples and 20 threats. Various LLMs (GPT-3.5, GPT-4, PaLM) were prompted to classify individual posts as either "threat" or "safe." Statistical analysis found all models demonstrated strong accuracy, passing chi-square goodness of fit tests for both threat and non-threat identification. GPT-4 performed best overall with 97.9% non-threat and 100% threat accuracy. Affordability analysis also showed PaLM API pricing as highly cost-efficient. The findings indicate LLMs can effectively augment human content moderation at scale to help mitigate emerging online risks. However, biases, transparency, and ethical oversight remain vital considerations before real-world implementation.

AI is more accessible to young people in the workforce who grew up as'digital natives' with Alexa and self-driving cars as part of the landscape, giving them expectations grounded in their experience of what is possible. That idea set the foundation for a panel discussion at AI World Government on Mindset Needs and Skill Set Myths for AI engineering teams, held this week virtually and in-person in Alexandria, Va. "People feel that AI is within their grasp because the technology is available, but the technology is ahead of our cultural maturity," said panel member Dorothy Aronson, CIO and Chief Data Officer for the National Science Foundation. We might have access to big data, but it might not be the right thing to do," to work with it in all cases. Things are accelerating, which is raising expectations. When panel member Vivek Rao, lecturer and researcher at the University of California at Berkeley, was working on his PhD, a paper on natural language processing might be a master's thesis. "Now we assign it as a homework assignment with a two-day turnaround.

Bill Holmes, facilities manager at the Corona, Calif., plant that produces the iconic Fender Stratocaster and Telecaster guitars, remembers all too well walking the factory floor with a crude handheld vibration analyzer and then plugging the device into a computer to get readings on the condition of his equipment. While all of the woodworking was done by hand when Leo Fender founded Fender Musical Instruments Corp. 75 years ago, today the guitar necks and bodies are produced with computer-controller woodworking routers, then handed off to the craftsmen who build the final product. Holmes says he is always looking for the latest technological advances to solve problems (he uses robotics to help paint the guitars), and there's no problem more vexing than equipment breakdowns. Preventive maintenance, where machines get attention on a predetermined schedule, is insufficient, he says. "Ninety percent of breakdowns are instant failures that shut down processes. If you can spot a failure before it happens, you're not shutting down production and the maintenance team isn't running around putting out fires."

Experts have warned for years that robots will replace humans in restaurants. Instead, a twist on that prediction is unfolding. Amid the lowest unemployment in years, fast-food restaurants are turning to machines--not to get rid of workers, but because they can't find enough. The hospitality industry had 844,000 unfilled positions in April, a record high, according to the Labor Department. Employment in food service and drinking places has increased by 1.6 million since May 2013 to 11.9 million in May 2018.

Experts have warned for years that robots will replace humans in restaurants. Instead, a twist on that prediction is unfolding. Amid the lowest unemployment in years, fast-food restaurants are turning to machines--not to get rid of workers, but because they can't find enough. The hospitality industry had 844,000 unfilled positions in April, a record high, according to the Labor Department. Employment in food service and drinking places has increased by 1.6 million since May 2013 to 11.9 million in May 2018.