If a major disaster like Fukushima or Chornobyl ever happens again, the world would know almost straight away, thanks to an array of government and DIY radiation-monitoring programs running globally. Why Don't Norwegians Hate Tesla Like the Rest of Europe Does? November's Tesla registrations were down in France, Sweden, Denmark, and Germany. Norway, however, is bucking the trend--thanks to a tax incentive system that will soon be rolled back.

West Somerset Lagoon would harness renewable energy for UK's AI boom - and create'iconic' arc around Bristol Channel The architect of the London Eye wants to build a vast tidal power station in a 14-mile arc off the coast of Somerset that could help Britain meet surging electricity demand to power artificial intelligence - and create a new race track to let cyclists skim over the Bristol Channel. Julia Barfield, who designed the Eye and the i360 observation tower in Brighton, is part of a team that has drawn up the £11bn proposal. The proposal comes amid growing concern that rapidly rising use of AI in Britain will drive up carbon emissions unless more renewable energy sources are found. The AI boom is expected to add to sharp increases in demand for electricity across the UK, which the government estimated this month could more than double by 2050. "If the decision is to go ahead with adopting more and more AI - which I am surprised is not being questioned more at a time of climate emergency - then it is going to be better with a renewable energy source," said Barfield.

This was supposed to be the year when autonomous agents took over everyday tasks. One year ago, Sam Altman, the C.E.O. of OpenAI, made a bold prediction: "We believe that, in 2025, we may see the first AI agents'join the workforce' and materially change the output of companies." A couple of weeks later, the company's chief product officer, Kevin Weil, said at the World Economic Forum conference at Davos in January, "I think 2025 is the year that we go from ChatGPT being this super smart thing . . . to ChatGPT doing things in the real world for you." He gave examples of artificial intelligence filling out online forms and booking restaurant reservations. He later promised, "We're going to be able to do that, no question."

In the AI boom, chatbots and GPTs come and go quickly. On a drizzly and windswept afternoon this summer, I visited the headquarters of Rokid, a startup developing smart glasses in Hangzhou, China. As I chatted with engineers, their words were swiftly translated from Mandarin to English, and then transcribed onto a tiny translucent screen just above my right eye using one of the company's new prototype devices. Rokid's high-tech spectacles use Qwen, an open-weight large language model developed by the Chinese ecommerce giant Alibaba. OpenAI's GPT-5, Google's Gemini 3, and Anthropic's Claude often score higher on benchmarks designed to gauge different dimensions of machine cleverness.

Things to Do in L.A. Tap to enable a layout that focuses on the article. 'Memory manipulation is inevitable': How rewriting memory in the lab might one day heal humans Professor and neuroscientist Steve Ramirez, shown working with brain samples, is exploring the science of memory manipulation. This is read by an automated voice. Please report any issues or inconsistencies here . Scientists have found that memories are not static records but dynamic processes that change the brain's wiring each time they are recalled.

A Florida man is facing multiple charges after he allegedly stole hundreds of pounds of avocados from a Miami-area grove with the intent to sell the avocados for money to buy his kids Christmas gifts.

If a major disaster like Fukushima or Chornobyl ever happens again, the world would know almost straight away, thanks to an array of government and DIY radiation-monitoring programs running globally.

Federated Learning (FL) is a form of distributed learning that allows multiple institutions or clients to collaboratively learn a global model to solve a task. This allows the model to utilize the information from every institute while preserving data privacy. However, recent studies show that the promise of protecting the privacy of data is not upheld by existing methods and that it is possible to recreate the training data from the different institutions. This is done by utilizing gradients transferred between the clients and the global server during training or by knowing the model architecture at the client end. In this paper, we propose a federated learning framework for semantic segmentation without knowing the model architecture nor transferring gradients between the client and the server, thus enabling better privacy preservation. We propose \textit{BlackFed} - a black-box adaptation of neural networks that utilizes zero order optimization (ZOO) to update the client model weights and first order optimization (FOO) to update the server weights. We evaluate our approach on several computer vision and medical imaging datasets to demonstrate its effectiveness. To the best of our knowledge, this work is one of the first works in employing federated learning for segmentation, devoid of gradients or model information exchange.

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Existing full text datasets of U.S. public domain newspapers do not recognize the often complex layouts of newspaper scans, and as a result the digitized content scrambles texts from articles, headlines, captions, advertisements, and other layout regions. OCR quality can also be low. This study develops a novel, deep learning pipeline for extracting full article texts from newspaper images and applies it to the nearly 20 million scans in Library of Congress's public domain Chronicling America collection. The pipeline includes layout detection, legibility classification, custom OCR, and association of article texts spanning multiple bounding boxes. To achieve high scalability, it is built with efficient architectures designed for mobile phones. The resulting American Stories dataset provides high quality data that could be used for pre-training a large language model to achieve better understanding of historical English and historical world knowledge. The dataset could also be added to the external database of a retrieval-augmented language model to make historical information - ranging from interpretations of political events to minutiae about the lives of people's ancestors - more widely accessible. Furthermore, structured article texts facilitate using transformer-based methods for popular social science applications like topic classification, detection of reproduced content, and news story clustering. Finally, American Stories provides a massive silver quality dataset for innovating multimodal layout analysis models and other multimodal applications.