How the Witch of November doomed the'Edmund Fitzgerald' Fifty years after the Great Lakes freighter sank, scientists can explain the weather that still haunts Lake Superior. When the SS Edmund Fitzgerald left port on November 10, 1975, there was no way for the crew to know what they were sailing into. Breakthroughs, discoveries, and DIY tips sent every weekday. On the afternoon of November 9, 1975, when the set out on its 746-mile run from Superior, Wisconsin, to Detroit, Michigan, Lake Superior was mostly calm. Even so, the crew likely saw the red sky from the intensifying storm gathering over the Great Plains.

Machine unlearning is concerned with the task of removing knowledge learned from particular data points from a trained model. In the context of large language models (LLMs), unlearning has recently received increased attention, particularly for removing knowledge about named entities from models for privacy purposes. While various approaches have been proposed to address the unlearning problem, most existing approaches treat all data points to be unlearned equally, i.e., unlearning that Montreal is a city in Canada is treated exactly the same as unlearning the phone number of the first author of this paper. In this work, we show that this all data is equal assumption does not hold for LLM unlearning. We study how the success of unlearning depends on the frequency of the knowledge we want to unlearn in the pre-training data of a model and find that frequency strongly affects unlearning, i.e., more frequent knowledge is harder to unlearn. Additionally, we uncover a misalignment between probability and generation-based evaluations of unlearning and show that this problem worsens as models become larger. Overall, our experiments highlight the need for better evaluation practices and novel methods for LLM unlearning that take the training data of models into account.

Oblique decision trees have attracted attention due to their potential for improved classification performance over traditional axis-aligned decision trees. However, methods that rely on exhaustive search to find oblique splits face computational challenges. As a result, they have not been widely explored. We introduce a novel algorithm, Classification and Regression Tree - Exhaustive Linear Combinations (CART-ELC), for inducing oblique decision trees that performs an exhaustive search on a restricted set of hyperplanes. We then investigate the algorithm's computational complexity and its predictive capabilities. Our results demonstrate that CART-ELC consistently achieves competitive performance on small datasets, often yielding statistically significant improvements in classification accuracy relative to existing decision tree induction algorithms, while frequently producing shallower, simpler, and thus more interpretable trees.

Fox News Flash top headlines are here. Check out what's clicking on Foxnews.com. Wisconsin Gov. Tony Evers on Thursday vetoed Republican proposals that would have allowed election observers to get closer to poll workers and required a new post-election audit, while signing into law a bill requiring that political TV ads using artificial intelligence come with a disclaimer. Evers, a Democrat, also signed a bipartisan bill exempting purchases of precious metal, such as gold and silver, from the state sales tax. The exemption does not apply to jewelry and other personal property, including works of art and scrap metal.

Mist, the pioneer in self-learning networks powered by Artificial Intelligence (AI), announced that it has partnered with Shopper Media Group, Australia's fastest-growing retail out-of-home (OOH) media business. Using Mist, Shopper Media Group will offer superior Wi-Fi, analytics and location-based services across the company's portfolio of Australian shopping centers. Mist currently provides market-leading Wi-Fi and location services using virtual Bluetooth Low Energy (BLE) technology to businesses across all industries worldwide, including over 30 of the Fortune 500 enterprises and the biggest retail players. Shopper Media Group is one of the first companies in Australia to deploy Mist technology, delivering on its mission to provide the best-in-class Wi-Fi solution and AI powered infrastructure to its national network of shopping centers. CEO of Shopper Media Group, Ben Walker said that they are incredibly excited to be working with the leaders in Wi-Fi and location-aware analytics, Mist, as they share the same drive to create, innovate and provide service leadership using ground-breaking AI-driven technology.

TOLEDO, Ohio (AP) - No longer a novelty, drones are becoming an everyday tool for more police and fire departments, new research has found. The number of public safety agencies with drones has more than doubled since the end of 2016, according to data collected by the Center for the Study of the Drone at New York's Bard College. The center estimated that just over 900 police, sheriff, fire and emergency agencies now have drones, with Texas, California, and Wisconsin leading the way, the study showed. While many law enforcement drone units are just getting started and are in place in just a fraction of the public safety agencies around the country, police and fire departments are continuing to find new uses for the remote-controlled aircraft. They're being deployed to take photos of car accidents, guide firefighters through burning buildings and search for missing people and murder suspects.

TOLEDO, OHIO – No longer a novelty, drones are becoming an everyday tool for more police and fire departments, new research has found. The number of public safety agencies with drones has more than doubled since the end of 2016, according to data collected by the Center for the Study of the Drone at New York's Bard College. The center estimated that just over 900 police, sheriff, fire and emergency agencies now have drones, with Texas, California, and Wisconsin leading the way, the study showed. While many law enforcement drone units are just getting started and are in place in just a fraction of the public safety agencies around the country, police and fire departments are continuing to find new uses for the remote-controlled aircraft. They're being deployed to take photos of car accidents, guide firefighters through burning buildings and search for missing people and murder suspects.