Intel's new desktop CPUs are radically different than the Intel CPUs you're used to. Today marks the launch of Arrow Lake, the company's latest architecture for desktop processors, formally sold as the Core Ultra 200S Series. According to Intel's claims, this batch of Core chips is faster and far more power efficient than last-gen Raptor Lake CPUs, while still beating out the competition. However, Arrow Lake isn't notable just for what it does, but also for what it is. As the first set of desktop x86 processors shipped but not fabricated by Intel, TSMC's involvement in their production is but one new standout aspect. Intel has reworked its chip design, too--and the overhaul comes with some quirks, as we discovered during our testing.

BBS leverages machine learning/statistical techniques to estimate the probability density of the search space and modifies the bisection step to split based on probability density rather than the traditional midpoint, allowing for the learned distribution of the search space to guide the search algorithm. Search space density estimation can flexibly be performed using supervised probabilistic machine learning techniques (e.g., Gaussian process regression, Bayesian neural networks, quantile regression) or unsupervised learning algorithms (e.g., Gaussian mixture models, kernel density estimation (KDE), maximum likelihood estimation (MLE)). We demonstrate significant efficiency gains of using BBS on both simulated data across a variety of distributions and in a real-world binary search use case of probing channel balances in the Bitcoin Lightning Network, for which we have deployed the BBS algorithm in a production setting. The concept of organizing data for efficient searching has ancient roots. One of the earliest known examples is the Inakibit-Anu tablet from Babylon (c. Similar sorting techniques were evident in name lists discovered on the Aegean Islands.

Large language models (LLMs) are becoming increasingly relevant as a potential tool for healthcare, aiding communication between clinicians, researchers, and patients. However, traditional evaluations of LLMs on medical exam questions do not reflect the complexity of real patient-doctor interactions. An example of this complexity is the introduction of patient self-diagnosis, where a patient attempts to diagnose their own medical conditions from various sources. While the patient sometimes arrives at an accurate conclusion, they more often are led toward misdiagnosis due to the patient's over-emphasis on bias validating information. In this work we present a variety of LLMs with multiple-choice questions from United States medical board exams which are modified to include self-diagnostic reports from patients. Our findings highlight that when a patient proposes incorrect bias-validating information, the diagnostic accuracy of LLMs drop dramatically, revealing a high susceptibility to errors in self-diagnosis.

The newly unveiled updated Apple Watch Series 9 will be Apple's first-ever carbon neutral gadget that requires a simple tap of two fingers to work. The device, which will become available on September 22, was also made using renewable materials and clean energy, leading to a 75 percent decrease in the amount of carbon waste emitted. And for the first time, users will be able to control the watch simply by tapping together the index finger and thumb on their watch hand. The Series 9 will start at $399 while the Apple Watch SE will run you $249. The Ultra 2 model will set you back $799.

IBM and the Massachusetts Institute of Technology conducted research into artificial intelligence's impact on employment and found that the emerging technology would result in fewer tasks and more focus on work that requires "soft skills." MIT and IBM's Watson AI Lab analyzed the potential applicability of machine learning in 170M online job postings from 2010 to 2017 as part of the study titled "The Future of Work: How New Technologies Are Transforming Tasks," IBM said Wednesday. According to the study, there was a 3.7 decrease in required work across 18.5K tasks and 46 percent less demand for tasks that are more suited for AI and machine learning. The IBM-MIT team noted that workers were asked to perform 4.3 fewer tasks encompassing activities like scheduling and credential validation. Tasks requiring soft skills like common sense, intuition, judgment and creativity saw 2.9 fewer tasks throughout a seven-year period.

Consumer enthusiasm for both emerging technology and resilient mature categories is exceeding expectations – driving the U.S. consumer technology industry to an estimated 3.2 percent revenue growth in 2017, earning $321 billion in retail revenues ($251 billion wholesale), according to new research from the Consumer Technology Association (CTA). The latest edition of CTA's semi-annual industry report, U.S. Consumer Technology Sales and Forecasts, also projects drones, OLED TV and virtual reality (VR) technology will each cross the $1 billion revenue milestone for the first time this year. "Driven by consumer demand for the products we already know and love, as well as new, innovative technologies, revenue growth in the consumer technology industry is exceeding expectations," said Gary Shapiro, president and CEO, CTA. "Not only are breakthrough technologies changing our lives for the better – such as drones delivering medical supplies to remote areas or the use of VR in patient care – tech is also a key driver of the U.S. economy, outpacing GDP growth, and reinforcing America's role as a global leader in innovation." CTA's semi-annual report serves as a benchmark for the consumer technology industry, charting the size and growth of underlying product categories.

One-to-one customer engagement enabled by machine learning yields a 13 percent reduction in bounce rate and a 33 percent average order value improvement at Marmot. A recent study from Gallup shed light on just how valuable it is to invest in customer engagement. Fully engaged customers, defined as those who have had a measurable reaction, connection, or experience with your brand, represent a 23 percent share of wallet, profitability, revenue, and relationship growth premium compared to average shoppers. By contrast, the study found that disengaged customers -- those who have no emotional connection to your brand -- represent a 13 percent discount in those same measures. It's no surprise that customer engagement and loyalty applications have been hot in retail, particularly e-commerce, where customer data is easier to gather and easier to analyze than in any other channel.