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 448 attacks on 34 settlements in Ukraine's front-line Zaporizhia region in a single day, injuring a six-year-old child and damaging homes, cars and other infrastructure, regional governor Ivan Fedorov wrote on the Telegram app. Russian drone, missile and artillery attacks on Ukraine's Kherson region injured five people and damaged homes, including seven high-rise buildings, the local military administration said on Telegram. Russian attacks also continued in Ukraine's Dnipropetrovsk and Sumy regions, but local officials there noted that "fortunately, no people were injured".

The free Green's Dictionary of Slang celebrates 500 years of'vulgar tongue.' Breakthroughs, discoveries, and DIY tips sent six days a week. While some terms or phrases may linger for centuries, most of today's slang terminology is more current. That often makes it difficult to keep up with the times, let alone understand casual communications of the past. That's where Jonathon Green came to the rescue. In 1993, Green started compiling 500 years of English slang by sifting through mountains of primary sources.

It's not the worst solution to the issue, but the images are definitely AI. Breakthroughs, discoveries, and DIY tips sent six days a week. It's increasingly difficult to keep track of all the generative AI slop currently fooling unsuspecting internetgoers on any given day. Earlier this month, a (fake) image went viral after enough people genuinely believed North Carolina conservationists kept wild horses warm during winter storms by wrapping them in fiberglass insulation . Now, another hoax is tugging on the heartstrings of animal lovers.

We propose a novel neural algorithm for the fundamental problem of computing the entropic optimal transport (EOT) plan between continuous probability distributions which are accessible by samples. Our algorithm is based on the saddle point reformulation of the dynamic version of EOT which is known as the Schrödinger Bridge problem. In contrast to the prior methods for large-scale EOT, our algorithm is end-to-end and consists of a single learning step, has fast inference procedure, and allows handling small values of the entropy regularization coefficient which is of particular importance in some applied problems. Empirically, we show the performance of the method on several large-scale EOT tasks.

One challenge of continual learning is "catastrophic forgetting" [Had+20; VT19; Kem+18]: A model However, if contexts similar to A arise repeatedly, this may be undesirable.. In machine learning, many data sets display cyclic or periodic patterns.