Reinforcement learning (RL) has achieved remarkable success in real-world decision-making across diverse domains, including gaming, robotics, online advertising, public health, and natural language processing. Despite these advances, a substantial gap remains between RL research and its deployment in many practical settings. Two recurring challenges often underlie this gap. First, many settings offer limited opportunity for the agent to interact extensively with the target environment due to practical constraints. Second, many target environments often undergo substantial changes, requiring redesign and redeployment of RL systems (e.g., advancements in science and technology that change the landscape of healthcare delivery). Addressing these challenges and bridging the gap between basic research and application requires theory and methodology that directly inform the design, implementation, and continual improvement of RL systems in real-world settings. In this paper, we frame the application of RL in practice as a three-component process: (i) online learning and optimization during deployment, (ii) post- or between-deployment offline analyses, and (iii) repeated cycles of deployment and redeployment to continually improve the RL system. We provide a narrative review of recent advances in statistical RL that address these components, including methods for maximizing data utility for between-deployment inference, enhancing sample efficiency for online learning within-deployment, and designing sequences of deployments for continual improvement. We also outline future research directions in statistical RL that are use-inspired -- aiming for impactful application of RL in practice.

Chinese firms are building battery plants from Europe to North America, promising jobs while prompting local concerns about the environment, politics, and who really benefits. When the rest of WIRED subscribers get their hands on our next print magazine, you, dear readers of Made in China, can proudly say you heard about it here first. The issue is all about China and includes stories about robots, AI boyfriends, a Chinese town that became the crystal capital of the world, and a Chinese DNA database built for family reunions. Like this newsletter, the issue is our attempt to document how deeply Chinese technology now shapes everyday life--no matter where you live in the world. As part of the issue, I reported a story on how Chinese lithium battery companies like CATL, BYD, and Gotion are now building factories on nearly every continent.

Plus: Trump has climbed down from his plan for the US to take Greenland. Yann LeCun's new venture is a contrarian bet against large language models Yann LeCun is a Turing Award recipient and a top AI researcher, but he has long been a contrarian figure in the tech world. He believes that the industry's current obsession with large language models is wrong-headed and will ultimately fail to solve many pressing problems. Instead, he thinks we should be betting on world models--a different type of AI that accurately reflects the dynamics of the real world. Perhaps it's no surprise, then, that he recently left Meta, where he had served as chief scientist for FAIR (Fundamental AI Research), the company's influential research lab that he founded. LeCun sat down with MIT Technology Review in an exclusive online interview from his Paris apartment to discuss his new venture, life after Meta, the future of artificial intelligence, and why he thinks the industry is chasing the wrong ideas.

We consider the problem of modifying a description logic concept in light of models represented as pointed interpretations. We call this setting model change, and distinguish three main kinds of changes: eviction, which consists of only removing models; reception, which incorporates models; and revision, which combines removal with incorporation of models in a single operation. We introduce a formal notion of revision and argue that it does not reduce to a simple combination of eviction and reception, contrary to intuition. We provide positive and negative results on the compatibility of eviction and reception for EL-bottom and ALC description logic concepts and on the compatibility of revision for ALC concepts.

The president wants big tech to pay more for electricity, but he's curbing renewable projects that could boost supply Donald Trump is worried about datacenters. Specifically, he is concerned about their effects on an already expensive electricity market in the United States. Will Americans' resentment of sharply rising energy costs scuttle his party's November election ambitions? The US president's anxiety is evident in two actions in recent weeks. On 13 January, Trump and Microsoft's president jointly announced that the tech giant would pay more for its datacenters, paying full property taxes and accepting neither tax reductions nor electricity rate discounts in towns where it operates datacenters.

What We Know About the Winter Storm About to Hit the US--and What We Don't A huge portion of the United States is going to be hit with snow or freezing rain this weekend. Exactly where, what, and how much remains uncertain. Over the past weekend, when weather models first started forecasting a winter storm that would sweep over large parts of the country, Sean Sublette, a meteorologist living in Virginia, started telling people in his area to prepare for snow . At the time, Sublette says, "a lot of the data started to point to a substantial snow storm for the mid-Atlantic and the Northeast, with significant ice farther southward into Carolina's Tennessee Valley." Then, Sublette woke up Wednesday morning.

Using a magnet to connect the transmitting and receiving coils, electrons behave more consistently and the phone is less likely to overheat. Breakthroughs, discoveries, and DIY tips sent six days a week. In-car wireless chargers are notoriously finicky. Your phone can slide off the slippery charging pad at a sudden stop, or overheat and stop charging; the case can also prevent your phone from connecting. Often, it's a pain in the neck, not to mention an added distraction while you're behind the wheel.

You'd never guess this lock is smart by looking at it, and that's my favorite part. No bulk or screen; looks like a regular lock from both sides of the door. Impressive design with the battery hidden inside the lock bolt. App is beautiful and easy to use. Best with accessories that need to be purchased separately.

Find out more about our session on Wednesday 21 January.

Could Ukraine hold a presidential election right now? Will Europe use frozen Russian assets to fund war? How can Ukraine rebuild China ties? 'Ukraine is running out of men, money and time' At least three people have been reported killed after Russian forces struck the southeastern Ukrainian city of Zaporizhzhia, Governor Ivan Fedorov announced on the Telegram messaging app. Russian strikes also destroyed several private houses and cars, and left nearly 1,500 households without electricity, the governor said.