Send the pool guy packing. One of these robotic buddies can maintain your water quality instead. Cleaning swimming pools is not fun. I learned this simple logic as a kid growing up in and around pools--it's the only way to survive summer in Houston, Texas. Four years ago, I became a pool owner myself, and I found that the rule still holds. Jumping into the pool on a hot day remains a rare treat, but if the pool is filled with leaves and dirt, that treat becomes a lot less delightful. And when the thermometer is reading over 100 degrees Fahrenheit, the thought of laboring on the pool deck, scooping out debris with a net, is downright cruel.

These are my favorites, whether you're new to fitness, an athlete, or a parent shopping for your kid. It's been five years since Google officially acquired Fitbit for a reported $2.1 billion, grabbing hardware and software teams that also absorbed assets from Pebble, which Fitbit itself acquired in 2016. So, how have things changed? Well, for starters, Fitbit is now Google Fitbit. It's not the most imaginative of name changes, and it hasn't stuck in consumers' minds, but the good news is that Fitbit devices remain some of the most user-friendly and welcoming fitness trackers available.

A nature-loving 10-year-old girl who found an endangered amphibian under a bridge has left her mum in shock, surprise and disbelief. Melanie Hill said her daughter, Evie, discovered the nine-inch Mexican axolotl as they spent the day near the River Ogmore in Bridgend. She said Evie was always finding things like newts and bugs, but said the axolotl discovery was a surprise. It is the first documented discovery of an axolotl in the wild in the UK with only 50 to 1,000 individuals left globally today, according to experts. Axolotls as pets have seen a surge in popularity in recent years after they were introduced to video games such as Minecraft and Roblox.

I've recently introduced a few friends to the power of a great robot vacuum. One of my friends calls hers a marriage saver, while the other was both thrilled and horrified by how many stains the vacuum's AI found on her floors. Personally, my robot vacuums keep me from wanting to set the litter box on fire, since my cat is on a mission to create his own navigational trail of litter through my home. The best robot vacuums these days aren't just vacuuming your floors, nor are they blindly bumping around your house like they used to. These gadgets are mopping, scrubbing away stains, lifting themselves off of obstacles, and even reminding you to clean the dirtier areas in your home more frequently. A good robot vacuum can cost a pretty penny, but it doesn't have to, depending on what you're looking for. I've been testing every new robot vacuum I can in my three-story home filled with three adults, a preschooler, and a cat who's on a mission to get litter all over the house.

What Will It Take to Get A.I. Out of Schools? The tech world assumes that A.I.-aided education is necessary and inevitable. A growing number of parents, educators, and cognitive scientists say the opposite. I don't like A.I., and I am raising my children not to like it. I've been telling them for years now that chatbots are manipulative and dangerous, that A.I.-image generators are loosening our collective grip on reality, that large language models are built atop industrial-scale intellectual-property theft. At times, I find myself speaking with my kids about A.I. in the same terms that we might discuss a creepy neighbor who lives down the block: avoid eye contact, cross the street when you walk past his house, and, when in doubt, call on a trusted adult. Yes, I, too, have suspected that the creepy neighbor walks on cloven hooves inside his Yeezy Boosts, but he probably isn't going anywhere--in fact, he keeps buying up properties around town--so just try your best not to engage. Somehow, I was not prepared for the creepy neighbor to start hanging around my kids' schools; somehow, I thought we had until high school.

Will fusion power get cheap? New research suggests that cost declines could be slow for the technology. Fusion power could provide a steady, zero-emissions source of electricity in the future--if companies can get plants built and running. But a new study suggests that even if that future arrives, it might not come cheap. Technologies tend to get less expensive over time. Lithium-ion batteries are now about 90% cheaper than they were in 2013.

A visitor looks at the copy of Michelangelo's Last Judgment by Robert le Voyer at the Louvre in Paris, 14 April 2026. A visitor looks at the copy of Michelangelo's Last Judgment by Robert le Voyer at the Louvre in Paris, 14 April 2026. To be human is to live with friction. That's something AI boosters will never understand We're being sold a world where there's no room for reflection or spontaneity. H ow fast do you have to strike a match to get it to light?

In the AI era, Apple's strengths may become its constraints Apple has expressed some willingness to use AI technology developed by rivals when needed. San Francisco - Apple built its empire on control. For decades, the company's tightly managed ecosystem, spanning custom chips, proprietary operating systems and curated apps, delivered devices that were secure and easy to use. That approach helped turn the iPhone into the most successful consumer product in history, generating nearly $210 billion in revenue last year. It also made Apple the world's top-valued company for much of the past decade, a position only overtaken by artificial intelligence chipmaker Nvidia in 2024.

We introduce and study the problem of calibrating conditional risk, which involves estimating the expected loss of a prediction model conditional on input features. We analyze this problem in both classification and regression settings and show that it is fundamentally equivalent to a standard regression task. For classification settings, we further establish a connection between conditional risk calibration and individual/conditional probability calibration, and develop theoretical insights for the performance metric. This reveals that while conditional risk calibration is related to existing uncertainty quantification problems, it remains a distinct and standalone machine learning problem. Empirically, we validate our theoretical findings and demonstrate the practical implications of conditional risk calibration in the learning to defer (L2D) framework. Our systematic experiments provide both qualitative and quantitative assessments, offering guidance for future research in uncertainty-aware decision-making.