The next phase in the fight against invasive spotted lanternflies (Lycorma delicatula) in the United States might just involve man's best friend. New research from Cornell University found that trained dogs were better than humans at detecting the lanternfly eggs that spend the winter in some landscapes, particularly forested areas. The findings are detailed in a study published December 26, 2024 in the journal Ecosphere. The spotted lanternfly is native to China, and was first detected in Pennsylvania in 2014. Since then, it has spread to at least 17 other states primarily in the eastern United States.

In a desperate attempt to shun western technology, President Vladimir Putin has ordered the creation of a new Russian video game console. Now, as a Russian chief admits it won't be as good as the Xbox or the PS5, commentators have flocked to social media to mock the upcoming machine, dubbing it the'Putindo 64'. On Reddit, someone posted: 'The Putindo is gonna be a wild collectors item in a few decades.' Another user posted'I only hyev tetris' in a reference to the famous puzzle video game created in 1985 by Russia's Alexey Pajitnov. Another said: 'what is going on with russian government, why are they trying to develop a console when they are fighting at the front.'

The Sixth Circuit US Court of Appeals ruled yesterday that the FCC does not have the "statutory authority" to implement net neutrality rules. Since the rules were established in 2015, the FCC argued that classifying ISPs as "telecommunication services" gives it broad authority to regulate them. The decision to redefine ISPs as "information services" during the first Trump Administration led to the repeal of net neutrality in 2017. The current FCC voted to restore net neutrality on April 25 last year. The difference between 2015 and now is the Supreme Court's recent, radical reinterpretation of an important legal doctrine.

The Trump administration's recent announcement of a sweeping deregulatory agenda for generative artificial intelligence (Gen AI) has created ripples across industries. This policy shift has implications for professionals and businesses alike, signaling a future where Gen AI development will accelerate quickly. If you want your work and business to survive this new acceleration, you need to adapt quickly to our increasingly disrupted environment. Gen AI, a transformative technology capable of generating human-like text, images and even code, has already proven its value in diverse sectors. A study by McKinsey indicates that businesses integrating Gen AI achieve productivity gains of up to 45% in certain areas, like customer support.

Russia's gradual, grinding advance in parts of Ukraine's eastern region of Donetsk succeeded in wresting away 4,168 sq km (1,609 square miles) of fields and abandoned villages in 2024 – equivalent to 0.69 percent of the country. That was the assessment of the Institute for the Study of War, a Washington-based think-tank, based on satellite imagery and geolocated video footage. "Russian forces have seized four mid-sized settlements – Avdiivka, Selydove, Vuhledar, and Kurakhove – in all of 2024, the largest of which had a pre-war population of just over 31,000 people," said the ISW. Russian forces spent four months taking Avdiivka, and two months each for Selydove and Kurakhove. "Seizing these settlements has not allowed Russian forces to threaten any notable Ukrainian defensive nodes," said the ISW, adding that Moscow's troops failed to conduct the kind of rapid, mechanised manoeuvre necessary to convert these "tactical gains into deep penetrations of Ukraine's rear".

One person has been killed and four others were injured when Russian drones targeted the Ukrainian capital of Kyiv, military and civilian officials said, as Russia launched barrages across the country. The Ukrainian Air Force said its air defences shot down 60 out of 93 Russian drones launched at Ukraine since the early hours of Friday. Moscow's forces have escalated aerial attacks across Ukraine in recent days, including a New Year's Day drone attack targeting central Kyiv that killed two people. In the latest barrage, a truck driver was killed by drone debris, according to Mykola Kalashnyk, acting governor for the Kyiv region. He said the debris also damaged several houses, injuring four people, including a 16-year-old boy.

While official reports of eerie drone-like UFOs dropped over the holidays, New Jersey residents are still coming forward with bizarre encounters. Two witnesses in Manalapan Township, for example, videotaped a bus-sized, 25- to 50-foot-long black triangle UFO that they saw'pull off a high g [force] maneuver over a residential area' just days before Christmas. The sighting, which lasted at least one minute, ended with the object zooming'in the general direction of McGuire [Joint Base McGuire-Dix-Lakehurst]' -- matching a persistent pattern of'drone' UFO incursions over US bases in recent years. Another New Jersey skywatcher recorded what they described as a classic'flying saucer' with an'aura or haze around object' just three miles off the coast of Atlantic City. And still more Garden State witnesses now say they saw as many as 20 to 30 drones just this Wednesday night, which'kind of hovered and all looked like miniature aircraft,' in an account posted to Facebook.

AI is often considered a threat to democracies and a boon to dictators. In 2025 it is likely that algorithms will continue to undermine the democratic conversation by spreading outrage, fake news, and conspiracy theories. In 2025 algorithms will also continue to expedite the creation of total surveillance regimes, in which the entire population is watched 24 hours a day. In the 20th century, distributed information networks like the USA functioned better than centralized information networks like the USSR, because the human apparatchiks at the center just couldn't analyze all the information efficiently. Replacing apparatchiks with AIs might make Soviet-style centralized networks superior.

The advancement of machine learning and the availability of large-scale reaction datasets have accelerated the development of data-driven models for computer-aided synthesis planning (CASP) in the past decade. Here, we detail the newest version of ASKCOS, an open source software suite for synthesis planning that makes available several research advances in a freely available, practical tool. Four one-step retrosynthesis models form the basis of both interactive planning and automatic planning modes. Retrosynthetic planning is complemented by other modules for feasibility assessment and pathway evaluation, including reaction condition recommendation, reaction outcome prediction, and auxiliary capabilities such as solubility prediction and quantum mechanical descriptor prediction. ASKCOS has assisted hundreds of medicinal, synthetic, and process chemists in their day-to-day tasks, complementing expert decision making. It is our belief that CASP tools like ASKCOS are an important part of modern chemistry research, and that they offer ever-increasing utility and accessibility.

Recently, Large language models (LLMs) with in-context learning have demonstrated remarkable potential in handling neural machine translation. However, existing evidence shows that LLMs are prompt-sensitive and it is sub-optimal to apply the fixed prompt to any input for downstream machine translation tasks. To address this issue, we propose an adaptive few-shot prompting (AFSP) framework to automatically select suitable translation demonstrations for various source input sentences to further elicit the translation capability of an LLM for better machine translation. First, we build a translation demonstration retrieval module based on LLM's embedding to retrieve top-k semantic-similar translation demonstrations from aligned parallel translation corpus. Rather than using other embedding models for semantic demonstration retrieval, we build a hybrid demonstration retrieval module based on the embedding layer of the deployed LLM to build better input representation for retrieving more semantic-related translation demonstrations. Then, to ensure better semantic consistency between source inputs and target outputs, we force the deployed LLM itself to generate multiple output candidates in the target language with the help of translation demonstrations and rerank these candidates. Besides, to better evaluate the effectiveness of our AFSP framework on the latest language and extend the research boundary of neural machine translation, we construct a high-quality diplomatic Chinese-English parallel dataset that consists of 5,528 parallel Chinese-English sentences. Finally, extensive experiments on the proposed diplomatic Chinese-English parallel dataset and the United Nations Parallel Corpus (Chinese-English part) show the effectiveness and superiority of our proposed AFSP.