Breakthroughs, discoveries, and DIY tips sent every weekday. It wasn't quite the eureka moment a team of scientists in Japan had set out for. Leo Uesaka, a marine biologist at the University of Tokyo, planned to study how seabirds use their legs to take flight from the ocean surface. He secured matchbox-sized cameras to the undersides of 15 streaked shearwaters (Calonectris leucomelas), a Pacific Ocean petrel species, to observe their movements. The tiny, tail-facing cameras successfully recorded information on the birds' legs.

Claire's on brink of collapse putting 2,150 jobs at risk 15 minutes agoShareSaveTom EspinerBusiness reporter, BBC NewsShareSaveEPA Claire's will appoint administrators after struggles with online competition. Fashion accessories chain Claire's is on the brink of collapse after the retailer said it will appoint administrators in the UK and Ireland, putting 2,150 jobs at risk. The company has 278 stores in the UK and 28 in Ireland but has been struggling with falling sales and fierce competition. All the shops will continue trading while administrators at Interpath, once appointed, will "assess options for the company". Interpath chief executive Will Wright, said options include "exploring the possibility of a sale which would secure a future for this well-loved brand". Claire's in the US filed for bankruptcy in the US earlier this month.

Charges against an American influencer and teen pilot who has been stranded on a remote island in the Antarctic since June have been dropped. Ethan Guo, 19, is alleged to have illegally landed his plane in Chilean territory after embarking on a solo trip to all seven continents to raise money for cancer research, according to local authorities. They accused him of providing false flight plan information to officials who detained him and opened an investigation. A judge has ordered him to leave the area, pay a $30,000 (£22,332) donation to a children's cancer foundation and is banned from re-entering Chilean territory for three years. Mr Guo made headlines last year when he began an attempt to become the youngest person to fly solo to all seven continents and collect donations for research into childhood cancer.

Teenager who lost his legs in crash will'never forgive' driver 38 minutes agoShareSaveKen Banks and Louise HosieBBC Scotland NewsShareSaveBBC Adam Golebiewski had a double amputation after the crash last year A teenager who lost his lower legs in a crash says he "will never forgive" the drink-driver at the wheel. Young footballer Adam Golebiewski, 18, had been a passenger in Arran Paterson's car in Macduff, Aberdeenshire, in September last year. Paterson, 19, admitted dangerous driving, being over the drink-drive limit and driving without insurance at Aberdeen Sheriff Court. Adam walked into court unaided on prosthetic legs following intensive rehabilitation. He said: "I want to try to enjoy life again and stay positive."

Google's newest AI model is going to scour the Earth and, ideally, help it out. The mission is to find out once and for all, in fine detail, what we are doing to our planet. Crucially, once the model has supposedly done this it will also, apparently, explain where we might be able to best put things in place to help our world. AlphaEarth Foundations, an offshoot of Google's DeepMind AI model, aims to leverage machine learning and all the gobs and gobs of data that Google has absorbed about our planet over the last two decades, in order to understand how specific areas are changing over time. The model uses a system called "embeddings" that takes terabytes of data collected from satellites every day, analyzes it, and compresses it down to save storage space.

Breakthroughs, discoveries, and DIY tips sent every weekday. It is in these waters that marine mammal ecologist Ari Friedlaender shuts off the inflatable boat's engine and waits. This is the edge of the world--remote, hostile, and stunningly alive. Beneath the hull, the dark sea churns with wonder abound. A humpback whale (Megaptera novaeangliae) emerges, slow, deliberate, and gentle in its curious demeanor, casting a ripple across the surface.

We often attribute human characteristics to large language models (LLMs) and claim that they "know" certain things. LLMs have an internal probabilistic knowledge that represents information retained during training. How can we assess the veracity of this knowledge? We examine two common methods for probing the veracity of LLMs and discover several assumptions that are flawed. To address these flawed assumptions, we introduce sAwMIL (short for Sparse Aware Multiple-Instance Learning), a probing method that utilizes the internal activations of LLMs to separate statements into true, false, and neither. sAwMIL is based on multiple-instance learning and conformal prediction. We evaluate sAwMIL on 5 validity criteria across 16 open-source LLMs, including both default and chat-based variants, as well as on 3 new datasets. Among the insights we provide are: (1) the veracity signal is often concentrated in the third quarter of an LLM's depth; (2) truth and falsehood signals are not always symmetric; (3) linear probes perform better on chat models than on default models; (4) nonlinear probes may be required to capture veracity signals for some LLMs with reinforcement learning from human feedback or knowledge distillation; and (5) LLMs capture a third type of signal that is distinct from true and false and is neither true nor false. These findings provide a reliable method for verifying what LLMs "know" and how certain they are of their probabilistic internal knowledge.

Four killed in Kyiv in new Russian aerial attack 12 minutes agoShareSaveJaroslav LukivBBC NewsShareSaveUkraine's emergencies service DSNSRescuers from Ukraine's emergencies service DSNS tackle fire in a residential building destroyed in the latest Russian attack on Kyiv At least four people have been killed in an overnight Russian missile and drone attack on Ukraine's capital Kyiv, the interior minister says. In a post on social media, Ihor Klymenko says residential areas, hospitals and sports infrastructure were hit. "An entire section of a residential high-rise building was destroyed" in the worst-hit Shevchenkivskyi district, he says, adding that some people are trapped under the rubble. In the Kyiv region, a woman was killed and another two people injured in the Russian aerial attack, regional head Mykola Kalashnyk says. The Russian military has not commented on the issue.

As the issue of global climate change becomes increasingly severe, the demand for research in climate science continues to grow. Natural language processing technologies, represented by Large Language Models (LLMs), have been widely applied to climate change-specific research, providing essential information support for decision-makers and the public. Some studies have improved model performance on relevant tasks by constructing climate change-related instruction data and instruction-tuning LLMs. However, current research remains inadequate in efficiently producing large volumes of high-precision instruction data for climate change, which limits further development of climate change LLMs. This study introduces an automated method for constructing instruction data. The method generates instructions using facts and background knowledge from documents and enhances the diversity of the instruction data through web scraping and the collection of seed instructions. Using this method, we constructed a climate change instruction dataset, named ClimateChat-Corpus, which was used to fine-tune open-source LLMs, resulting in an LLM named ClimateChat. Evaluation results show that ClimateChat significantly improves performance on climate change question-and-answer tasks. Additionally, we evaluated the impact of different base models and instruction data on LLM performance and demonstrated its capability to adapt to a wide range of climate change scientific discovery tasks, emphasizing the importance of selecting an appropriate base model for instruction tuning. This research provides valuable references and empirical support for constructing climate change instruction data and training climate change-specific LLMs.

Breakthroughs, discoveries, and DIY tips sent every weekday. For nearly two decades, balloons carrying highly sensitive atmospheric instruments have drifted more than 25 miles above one of the world's most remote regions. The floating array is the Antarctic Impulsive Transient Antenna (ANITA) experiment, a project overseen by an international group of researchers tasked with measuring some of the universe's oldest and hardest-to-detect cosmic rays. Specifically, the team is hunting for neutrinos--particles with no charge that also possess the smallest known subatomic mass. But according to their recent report, ANITA has repeatedly picked up some truly weird signals that defy explanation.