How the US left Ukraine exposed to Russia's winter war Will Europe use frozen Russian assets to fund war? How can Ukraine rebuild China ties? Russian forces launched multiple attacks on Ukraine's Zaporizhia region, killing one person and injuring seven others over the past day, the region's military administration said on the Telegram messaging platform. The attacks involved 448 drones as well as 163 artillery strikes, causing damage to 136 homes, cars and other structures, the military administration said. Russian forces also continued shelling Ukraine's Donetsk region, forcing 173 people, including 135 children, to evacuate front-line areas over the past day, regional governor Vadym Filashkin said on Telegram.

Reinforcement learning with the help of neural-guided search consumes huge computational resources to achieve remarkable performance.

This intervention significantly improves the performance of LLaMA models on the TruthfulQA benchmark.

Researchers at the company are trying to understand their A.I. system's mind--examining its neurons, running it through psychology experiments, and putting it on the therapy couch. It has become increasingly clear that Claude's selfhood, much like our own, is a matter of both neurons and narratives. A large language model is nothing more than a monumental pile of small numbers. It converts words into numbers, runs those numbers through a numerical pinball game, and turns the resulting numbers back into words. Similar piles are part of the furniture of everyday life. Meteorologists use them to predict the weather. Epidemiologists use them to predict the paths of diseases. Among regular people, they do not usually inspire intense feelings. But when these A.I. systems began to predict the path of a sentence--that is, to talk--the reaction was widespread delirium. As a cognitive scientist wrote recently, "For hurricanes or pandemics, this is as rigorous as science gets; for sequences of words, everyone seems to lose their mind." It's hard to blame them. Language is, or rather was, our special thing. We weren't prepared for the arrival of talking machines. Ellie Pavlick, a computer scientist at Brown, has drawn up a taxonomy of our most common responses. There are the "fanboys," who man the hype wires. They believe that large language models are intelligent, maybe even conscious, and prophesy that, before long, they will become superintelligent. The venture capitalist Marc Andreessen has described A.I. as "our alchemy, our Philosopher's Stone--we are literally making sand think." The fanboys' deflationary counterparts are the "curmudgeons," who claim that there's no there, and that only a blockhead would mistake a parlor trick for the soul of the new machine. In the recent book " The AI Con," the linguist Emily Bender and the sociologist Alex Hanna belittle L.L.M.s as "mathy maths," "stochastic parrots," and "a racist pile of linear algebra." But, Pavlick writes, "there is another way to react." It is O.K., she offers, "to not know." What Pavlick means, on the most basic level, is that large language models are black boxes. We don't really understand how they work. We don't know if it makes sense to call them intelligent, or if it will ever make sense to call them conscious. The existence of talking machines--entities that can do many of the things that only we have ever been able to do--throws a lot of other things into question. We refer to our own minds as if they weren't also black boxes.

In this paper, we propose a distributed framework for reducing the dimensionality of high-dimensional, large-scale, heterogeneous matrix-variate time series data using a factor model. The data are first partitioned column-wise (or row-wise) and allocated to node servers, where each node estimates the row (or column) loading matrix via two-dimensional tensor PCA. These local estimates are then transmitted to a central server and aggregated, followed by a final PCA step to obtain the global row (or column) loading matrix estimator. Given the estimated loading matrices, the corresponding factor matrices are subsequently computed. Unlike existing distributed approaches, our framework preserves the latent matrix structure, thereby improving computational efficiency and enhancing information utilization. We also discuss row- and column-wise clustering procedures for settings in which the group memberships are unknown. Furthermore, we extend the analysis to unit-root nonstationary matrix-variate time series. Asymptotic properties of the proposed method are derived for the diverging dimension of the data in each computing unit and the sample size $T$. Simulation results assess the computational efficiency and estimation accuracy of the proposed framework, and real data applications further validate its predictive performance.

Apple's Siri AI will be powered by Gemini The Duo and Family plans are getting a $2 price hike. Spotify is raising the prices for its premium subscriptions by $1 to $2 across the board, starting this February. Those are similar figures to the company's last price hike in 2024. Subscribers across the US, Estonia and Latvia will soon receive an email, notifying them that they'll be paying a larger amount for their February bill. The streaming service said it's raising its prices occasionally to "reflect the value that Spotify delivers," "to continue offering the best possible experience" and to "benefit artists."

Topological methods have the potential of exploring data clouds without making assumptions on their the structure. Here we propose a hierarchical topological clustering algorithm that can be implemented with any distance choice. The persistence of outliers and clusters of arbitrary shape is inferred from the resulting hierarchy. We demonstrate the potential of the algorithm on selected datasets in which outliers play relevant roles, consisting of images, medical and economic data. These methods can provide meaningful clusters in situations in which other techniques fail to do so.

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' Russian forces launched an air attack on Ukraine's capital, Kyiv, on Monday, killing one civilian in the first reported death in the city this year, according to the Ukrainian military. Russia's military also carried out drone attacks on northeastern Ukraine on Sunday, killing at least two people in the Sumy region and wounding three in the Kharkiv region, according to local officials.

Photographer Victor Lima used a 12 millimeter fisheye lens to take this panoramic image of the aurora borealis over the Skógafoss waterfall in Iceland. Breakthroughs, discoveries, and DIY tips sent every weekday. Watching the aurora borealis (in the Northern Hemisphere) or aurora australis (in the Southern Hemisphere) is unforgettable. Photographing them is on a whole other level. Capturing these ribbons of light as they move and twist across the night sky transforms even the darkest winter night into a surreal wonderland.