Karoline Leavitt's family member was swarmed by ICE agents while picking up son from school as child's father tell her to'self deport' Deaths from highly infectious virus are growing... as states brace for widespread outbreaks My book on the Kennedys was used as a'mistress manual' by Olivia Nuzzi... then this wannabe Carolyn Bessette had the nerve to hound me with these outrageous texts: MAUREEN CALLAHAN Katy Perry's legal victory as judge orders disabled veteran to pay singer nearly $2m over Montecito mansion Trump reveals next DC renovation project to remove'Biden filth' after White House ballroom Cracker Barrel CEO whines that she got'fired by America' for woke redesign Kroger employee reveals shocking amount laundry products have increased by... 'biggest price jump I've seen in a single week' Hollywood heir, 23, whose mom Anne Heche died in horror car fireball has secret LOVE CHILD with 43-year-old... now she's telling all Missing Melodee Buzzard's mom'left her daughter with strangers she met at the zoo' Rachel Zoe reveals why she dumped husband of 26 years... and if she has started dating again Horrific moment cops found body of Cowboys star Marshawn Kneeland after he shot himself at end of 145 mph chase'This is pretty lurid' Jenny McCarthy, 53, reveals health emergency that involved NINE surgeries, her'teeth falling out' and'growth' on her eyeballs Maryland grandma, 58, dragged across floor after being deported to country she'has never even visited' READ MORE: New'stone head' statue mysteriously appears on Easter Island One of the biggest mysteries surrounding Easter Island may finally be solved - as scientists pinpoint who built the iconic stone heads over 900 years ago. In the past, researchers assumed that the 12 to 80-ton statues would have required the combined efforts of hundreds of labourers to build and move. However, new archaeological evidence shows that the statues, known as moai, were not carved by a single powerful chiefdom. Instead, each moai was carved by a small clan or by an individual family, with as few as four to six people working on a single statue. Using a new 3D model of the island's main moai quarry, which you can explore below, archaeologists identified 30 unique'workshops' where the statues were produced.

Large language models (LLMs) have delivered significant breakthroughs across diverse domains but can still produce unreliable or misleading outputs, posing critical challenges for real-world applications. While many recent studies focus on quantifying model uncertainty, relatively little work has been devoted to \textit{diagnosing the source of uncertainty}. In this study, we show that, when an LLM is uncertain, the patterns of disagreement among its multiple generated responses contain rich clues about the underlying cause of uncertainty. To illustrate this point, we collect multiple responses from a target LLM and employ an auxiliary LLM to analyze their patterns of disagreement. The auxiliary model is tasked to reason about the likely source of uncertainty, such as whether it stems from ambiguity in the input question, a lack of relevant knowledge, or both. In cases involving knowledge gaps, the auxiliary model also identifies the specific missing facts or concepts contributing to the uncertainty. In our experiment, we validate our framework on AmbigQA, OpenBookQA, and MMLU-Pro, confirming its generality in diagnosing distinct uncertainty sources. Such diagnosis shows the potential for relevant manual interventions that improve LLM performance and reliability.

Giselle and Stephen Jiroch of California have been traveling full-time for the last four years. The couple said these U.S. destinations are must-see spots. Costco is rolling out new ways to deliver perks to its customers while tapping into the travel industry's knowledge and insight. In collaboration with Travelport, a global technology company that connects travel suppliers, Costco Travel has introduced new features for members. The partnership will expand the flight options available to members.

Large Language Models (LLMs) tend to prioritize adherence to user prompts over providing veracious responses, leading to the sycophancy issue. When challenged by users, LLMs tend to admit mistakes and provide inaccurate responses even if they initially provided the correct answer. Recent works propose to employ supervised fine-tuning (SFT) to mitigate the sycophancy issue, while it typically leads to the degeneration of LLMs' general capability. To address the challenge, we propose a novel supervised pinpoint tuning (SPT), where the region-of-interest modules are tuned for a given objective. Specifically, SPT first reveals and verifies a small percentage (<5%) of the basic modules, which significantly affect a particular behavior of LLMs. i.e., sycophancy. Subsequently, SPT merely fine-tunes these identified modules while freezing the rest. To verify the effectiveness of the proposed SPT, we conduct comprehensive experiments, demonstrating that SPT significantly mitigates the sycophancy issue of LLMs (even better than SFT). Moreover, SPT introduces limited or even no side effects on the general capability of LLMs. Our results shed light on how to precisely, effectively, and efficiently explain and improve the targeted ability of LLMs.

Now the company says it has fine-tuned that protein model to predict which misspellings found in human DNA are safe to ignore and which are likely to cause disease. The new software, called AlphaMissense, was described today in a report published by the journal Science. As part of its project, DeepMind says, it is publicly releasing tens of millions of these predictions, but the company isn't letting others directly download the model because of what it characterizes as potential biosecurity risks should the technique be applied to other species. Although not intended to directly make diagnoses, computer predictions are already used by doctors to help locate the genetic causes of mysterious syndromes. In a blog post, DeepMind said its results are part of an effort to uncover "the root cause of disease" and could lead to "faster diagnosis and developing life-saving treatments."

There's a reason consumer drones have evolved from an expensive toy into a tool of war: They can perform high-altitude surveillance, carry out reconnaissance, or even deploy weapons, with their operator safely hidden as far as miles away. But hackers are revealing that for quadcopters sold by the world's biggest drone manufacturer, operators aren't nearly as hidden as they might think. In fact, these small flying machines are continually broadcasting their pilots' exact locations from the sky, and anyone with some cheap radio hardware and a newly released software tool can eavesdrop on those broadcasts and decode them to extract their coordinates. At the Network and Distributed System Security Symposium (NDSS) in San Diego this week, researchers from Ruhr University Bochum and the CISPA Helmholtz Center for Information Security demonstrated that they were able to reverse engineer the radio signals of drones sold by DJI, the leading manufacturer of consumer quadcopter drones, to decode a radio protocol they use called DroneID. By deconstructing this signal, the researchers could see that every DJI drone's DroneID communications transmit not only its own GPS location and a unique identifier for that drone, but also the GPS coordinates of its operator.

Today's customer expects the ability to engage with businesses through various communication channels like email, SMS, Push notifications, and in-app notifications when they have a question or need a problem resolved. SMS is one of the fastest growing communication channels, and we've seen that customers enjoy the ease and speed of texting for help versus traditional call channels. However, building an SMS system at scale to address millions of inquiries can be challenging for even the most advanced IT departments. Research also shows that customers prefer a personalized experience over a generic one, but using agents or employees to personalize millions of messages on a case-by-case basis is not practical. To solve this problem, we can use Amazon Pinpoint, AWS' multichannel communication service, to interact in personalized 2-way SMS messages with customers.

Industry experts estimate that acquiring a new policyholder is 5-25x more expensive than retaining an existing one, but until now, there was no way to predictively anticipate if an account would churn. ReFocus AI's Converge platform offers a unique, turnkey solution that allows brokers to leverage the predictive power of their policyholder data to pinpoint the ideal retention action to reduce churn by as much as 25%. "The ReFocus AI platform allows us to better serve our clients by understanding their concerns and how best we can serve them," says Christopher Cook, CEO of Alliance. "These insights will help us realize growth and prioritize our efforts around renewals. We believe that AI-powered churn analytics will result in higher customer retention and significantly better customer experiences."

The potential number of applications for machine learning has grown tremendously in the last several years, as AI models become increasingly more powerful. Machine learning is already being used in many areas of daily life, whether that's in recommendation algorithms, self-driving cars, or being used in novel ways in fields like research or finance. Even more promising is how machine learning models might someday revolutionize healthcare, and may even help us grapple with impossibly complex issues like mitigating climate change. But despite the great potential of machine learning models, they are not foolproof and can make mistakes -- sometimes with disastrous consequences. These unintended impacts are all the more concerning when image recognition algorithms are being increasingly used in evaluating people's biometric data.

At a workshop hosted through the Air Force's military university on Aug. 26 in Montgomery, Alabama, students were shown a video of President Joe Biden addressing the UN while effortlessly switching between five languages including Mandarin and Russian. While Thomas Jefferson and John Quincy Adams were fluent in several languages, Biden, like most U.S. presidents, is only known to speak English. The video was a piece of synthetic media, more commonly known as a "deepfake." Created using a combination of machine learning and artificial intelligence, deepfakes are hyperrealistic videos that replace one person's likeness with that of another, or appear to show them doing something they never did. And as the technology improves, they get harder to detect.