These high-tech appliances can make your life easier. Samsung, Frigidaire, GE and other big-name brands have great deals on ovens, refrigerators, small appliances, washers and dryers.

The frequency of the preferred order for a noun phrase formed by demonstrative, numeral, adjective and noun has received significant attention over the last two decades. We investigate the actual distribution of the preferred 24 possible orders. There is no consensus on whether it can be well-fitted by an exponential or a power law distribution. We find that an exponential distribution is a much better model. This finding and other circumstances where an exponential-like distribution is found challenge the view that power-law distributions, e.g., Zipf's law for word frequencies, are inevitable. We also investigate which of two exponential distributions gives a better fit: an exponential model where the 24 orders have non-zero probability or an exponential model where the number of orders that can have non-zero probability is variable. When parsimony and generalizability are prioritized, we find strong support for the exponential model where all 24 orders have non-zero probability. This finding suggests that there is no hard constraint on word order variation and then unattested orders merely result from undersampling, consistently with Cysouw's view.

This paper explores the challenges posed by nominal adjectives (NAs) in natural language processing (NLP) tasks, particularly in part-of-speech (POS) tagging. We propose treating NAs as a distinct POS tag, "JN," and investigate its impact on POS tagging, BIO chunking, and coreference resolution. Our study shows that reclassifying NAs can improve the accuracy of syntactic analysis and structural understanding in NLP. We present experimental results using Hidden Markov Models (HMMs), Maximum Entropy (MaxEnt) models, and Spacy, demonstrating the feasibility and potential benefits of this approach. Additionally we finetuned a bert model to identify the NA in untagged text.

LG Electronics (LG) announces that production of its Inverter Direct Drive (DD) motor has exceeded 100 million units. The company's differentiated motor technology is a major factor in the strong, reliable performance and continuing global popularity of LG's industry-leading laundry solutions. LG's Inverter DD motor connects directly to the washing drum, an innovation that helps make LG washing machines more durable and dramatically reduces noise and energy consumption during operation. LG has refined the Inverter DD motor over four generations, continuously improving the technology and its performance capabilities to deliver greater customer value. The company holds over 240 Inverter DD motor related technology patents in Korea and internationally.

Social media platforms give rise to an abundance of posts and comments on every topic imaginable. Many of these posts express opinions on various aspects of society, but their unfalsifiable nature makes them ill-suited to fact-checking pipelines. In this work, we aim to distill such posts into a small set of narratives that capture the essential claims related to a given topic. Understanding and visualizing these narratives can facilitate more informed debates on social media. As a first step towards systematically identifying the underlying narratives on social media, we introduce PAPYER, a fine-grained dataset of online comments related to hygiene in public restrooms, which contains a multitude of unfalsifiable claims. We present a human-in-the-loop pipeline that uses a combination of machine and human kernels to discover the prevailing narratives and show that this pipeline outperforms recent large transformer models and state-of-the-art unsupervised topic models.

Builders Show) and KBIS (Kitchen and Bath Industry Show) was a bevy of announcements--everything from 3D printing to software to appliances. Parks Associates found steady purchase intentions for smart appliances and continued growth for smart energy and lighting products at the show. But here is what stood out to me: Roughly 25% of U.S. broadband households plan to buy a smart appliance in the next six months. I was able to see firsthand how new appliances are becoming greener and more ecofriendly. They are better for the world and save energy, while also lengthening the life of our food.

We hope you're able to celebrate the long weekend with your family and friends. Maybe stay indoors this year to take your mind off the heat wave currently working its way through the US. If you're outside, we have lots of advice on how to stay cool. The good news is there's money to be saved on some of our favorite home and outdoor products this weekend thanks to a bevy of July 4th sales. Special offer for Gear readers: Get a 1-Year Subscription to WIRED for $5 ($25 off).

In the context of the Covid-19 pandemic, many were quick to spread deceptive information. I investigate here how reasoning in Description Logics (DLs) can detect inconsistencies between trusted medical sources and not trusted ones. The not-trusted information comes in natural language (e.g. "Covid-19 affects only the elderly"). To automatically convert into DLs, I used the FRED converter. Reasoning in Description Logics is then performed with the Racer tool.

Smart appliances are nothing new. As with most consumer products, the ubiquity of built-in WiFi and Bluetooth progresses steadily, promising a bold, yet decidedly unspecific, future of "connectedness." LG's new ProActive Care is attempting to finally make good on some of that promise by leveraging artificial intelligence (AI) to zero in on one of the biggest pain-points in appliance ownership: services and repair. Broken or malfunctioning appliances are a fact of life for consumers. No matter how well built, those big metal boxes that get exceptionally hot, wet, or cold on a daily basis are going to break down eventually.

At CES, LG Electronics (LG) unveiled its most advanced innovation in laundry, deploying artificial intelligence to deliver precision washing for optimal results without the guesswork. The AI DD washer builds on 20 years of advancements in LG's groundbreaking Direct Drive motor, which delivers both effectiveness and efficiency. LG's new washing machine not only detects the volume and weight of each unique laundry load but also uses AI and advanced sensors to identify fabric types in each load. Using deep learning technology, the washer then compares this information against more than 20 thousand data points related to washer usage to program the optimal wash cycle setting for the best results, improving cleaning and extending the life of garments by 15 percent.* LG's most intelligent washer is able to detect a mixed load of t-shirts and pants (different from bedding, delicates and other fabric combinations) and program the wash cycle to use customized motions, temperatures and times for the optimal wash.