Fixtures giant Kohler has a holiday promo code for 10 percent off big orders for Black Friday 2025. There are Black Friday deals, and then there are Black Friday deals. Most deals are the kind that show up later on your porch from Amazon (see WIRED's guide to the best early Black Friday deals). But fixture and plumbing mainstay Kohler is doing something a little different, and a lot bigger, for the holidays. After all, Kohler is big--one of the biggest family-owned manufacturing empires in the country.

We present a theoretically well-founded deep learning algorithm for nonparametric regression. It uses over-parametrized deep neural networks with logistic activation function, which are fitted to the given data via gradient descent. We propose a special topology of these networks, a special random initialization of the weights, and a data-dependent choice of the learning rate and the number of gradient descent steps. We prove a theoretical bound on the expected $L_2$ error of this estimate, and illustrate its finite sample size performance by applying it to simulated data. Our results show that a theoretical analysis of deep learning which takes into account simultaneously optimization, generalization and approximation can result in a new deep learning estimate which has an improved finite sample performance.

In deep learning, the task is to estimate the functional relationship between input and output using deep neural networks. For the particular application area of image classification, the input data consists of observed images and the output data represents classes of the corresponding images that describe what kind of objects are present in the images. The most successful methods, especially in the area of image classification can be attributed to deep learning approaches (see, e.g., Krizhevsky, Sutskever and Hinton (2012), LeCun, Bengio and Hinton (2015), and Rawat and Wang (2017)) and, in particular, to convolutional neural networks (CNNs).

A new smart Smart toilets showcased at CES give'porcelain throne' a new meaning. Attendees of the Las Vegas event feasted their eyes on innovative loos designed by appliance maker Kholer, which feature voice activation, touch screens and high prices. For 4,500, the Veil includes a range of services like pulsating spray options and automatic deodorizer, while Amazon's Alexa powers the top-of-the-line Numi, which costs around 10,000. The company did display a more affordable option - the 1,200 PureWash E930 bidet that connects to your home internet and features voice control. The Kohler Veil, released this year at CES, is Kohler's mid-range smart toilet.

Some companies take monitors, TVs or AI-fueled laptops to CES. Others bring a toilet seat you can talk to. The 151-year-old bathroom appliance company Kohler will introduce the PureWash E930 Bidet Seat in Las Vegas next week. Kohler says the PureWash E930 Bidet Seat "brings you the freshness of personal cleansing in a slim, low-profile design." At $2,149, it isn't cheap, but it could save you money -- and installation hassles -- compared to full-on smart toilets.

Recent results show that estimates defined by over-parametrized deep neural networks learned by applying gradient descent to a regularized empirical $L_2$ risk are universally consistent and achieve good rates of convergence. In this paper, we show that the regularization term is not necessary to obtain similar results. In the case of a suitably chosen initialization of the network, a suitable number of gradient descent steps, and a suitable step size we show that an estimate without a regularization term is universally consistent for bounded predictor variables. Additionally, we show that if the regression function is H\"older smooth with H\"older exponent $1/2 \leq p \leq 1$, the $L_2$ error converges to zero with a convergence rate of approximately $n^{-1/(1+d)}$. Furthermore, in case of an interaction model, where the regression function consists of a sum of H\"older smooth functions with $d^*$ components, a rate of convergence is derived which does not depend on the input dimension $d$.

Convolutional neural network image classifiers are defined and the rate of convergence of the misclassification risk of the estimates towards the optimal misclassification risk is analyzed. Here we consider images as random variables with values in some functional space, where we only observe discrete samples as function values on some finite grid. Under suitable structural and smoothness assumptions on the functional a posteriori probability, which includes some kind of symmetry against rotation of subparts of the input image, it is shown that least squares plug-in classifiers based on convolutional neural networks are able to circumvent the curse of dimensionality in binary image classification if we neglect a resolution-dependent error term. The finite sample size behavior of the classifier is analyzed by applying it to simulated and real data.

Geolocation, the process of identifying the precise location in the world where a photo or video was taken, is central to many types of investigative work, from debunking fake news posted on social media to locating terrorist training camps. Professional geolocation is often a manual, time-consuming process that involves searching large areas of satellite imagery for potential matches. In this paper, we explore how crowdsourcing can be used to support expert image geolocation. We adapt an expert diagramming technique to overcome spatial reasoning limitations of novice crowds, allowing them to support an expert's search. In two experiments (n 1080), we found that diagrams work significantly better than ground-level photos and allow crowds to reduce a search area by half before any expert intervention. We also discuss hybrid approaches to complex image analysis combining crowds, experts, and computer vision.

Kohler has revealed when you'll be able to snag the Stillness Bath it unveiled at CES 2021, as well as a number of other smart home products. The bath, which takes inspiration from Japanese forest bathing, aims to replicate a spa experience with the help of light, fog and aromas. All aspects of the experience can be controlled through Kohler's Konnect app. The Soak Freestanding Bath model will cost around $8,000 and you'll be able to order it by the end of March. Another model offers voice control and another, called the Infinity Experience, fills from the bottom and water overflows into the wood base.

Architecture and construction have always been, rather quietly, at the bleeding edge of tech and materials trends. It's no surprise, then, especially at a renowned technical university like ETH Zurich, to find a project utilizing AI and robotics in a new approach to these arts. The automated design and construction they are experimenting with show how homes and offices might be built a decade from now. The project is a sort of huge sculptural planter, "hanging gardens" inspired by the legendary structures in the ancient city of Babylon. Begun in 2019, Semiramis (named after the queen of Babylon back then) is a collaboration between human and AI designers.