Oshen's robotic sailboats are powered by the wind and the sun The UK's Royal Navy may return to the age of sail, with a new demonstration involving a flotilla of small, wind-propelled robot boats. Made by Oshen in Plymouth, UK, the vessels, known as C-Stars, are just 1.2 metres long and weigh around 40 kilos. Solar panels power navigation, communications and sensors, while a sail provides propulsion. Deployed as a constellation, the small vessels act as a wide-area sensor network. How the US military wants to use the world's largest aircraft "The simplest way of describing C-Stars is as self-deploying, station-keeping ocean buoys," says Oshen CEO Anahita Laverack .

That time Oregon blew up a whale with dynamite. And why we should never do it again. Breakthroughs, discoveries, and DIY tips sent every weekday. When a whale dies in the ocean, an ecosystem grows around its sunken carcass. It's an epic burial at sea, something researchers call a whale fall .

Diffusion models may be formulated as a time-indexed sequence of energy-based models, where the score corresponds to the negative gradient of an energy function. As opposed to learning the score directly, an energy parameterization is attractive as the energy itself can be used to control generation via Monte Carlo samplers. Architectural constraints and training instability in energy parameterized models have so far yielded inferior performance compared to directly approximating the score or denoiser. We address these deficiencies by introducing a novel training regime for the energy function through distillation of pre-trained diffusion models, resembling a Helmholtz decomposition of the score vector field. We further showcase the synergies between energy and score by casting the diffusion sampling procedure as a Feynman Kac model where sampling is controlled using potentials from the learnt energy functions. The Feynman Kac model formalism enables composition and low temperature sampling through sequential Monte Carlo.

Taylor Sheridan, the most overextended man in television, has done it again. Landman, according to the internal metrics at Paramount, is the most watched original show the streamer has ever had. Remember, Yellowstone proper is on Peacock.) The West Texas–set story, which stars Billy Bob Thornton as Tommy Norris, an all-purpose problem solver for a fictional oil company owned by Monty Miller (Jon Hamm), has also developed a bit more of a critical halo than Sheridan's other TV ventures, popping up on best-of-2024 lists, edging into mainstream discourse via podcasts that typically cover more-prestige fare, and retaining a score of 80 percent on Rotten Tomatoes. And the week before Landman wrapped up, this past Sunday night, its lead actor, Billy Bob Thornton, attended the Golden Globes as a nominee for his role in the series.

While the hope of the US returning to the moon has been temporarily dashed, Astrobotic CEO John Thornton expressed high hopes for its future Griffin lunar lander missions. 'What a wild adventure we were just on,' Thornton said. 'Certainly not the outcome we were hoping for and certainly challenging right up front.' Like the Peregrine, these robotic lunar landers are expected to serve as a scout for the NASA's Artemis astronauts before they make their own moon landing in 2026. The CEO and trained mechanical engineer described'victory' after'victory' as his team scrambled to make the most of the scrapped Peregrine mission.

The possibility of automatically classifying high frequency sub-bottom acoustic reflections collected from an Autonomous Underwater Robot is investigated in this paper. In field surveys of Cobalt-rich Manganese Crusts (Mn-crusts), existing methods relies on visual confirmation of seafloor from images and thickness measurements using the sub-bottom probe. Using these visual classification results as ground truth, an autoencoder is trained to extract latent features from bundled acoustic reflections. A Support Vector Machine classifier is then trained to classify the latent space to idetify seafloor classes. Results from data collected from seafloor at 1500m deep regions of Mn-crust showed an accuracy of about 70%.

Because I am a writer, and because I am a hoarder, my apartment is littered with notebooks that contain a mixture of journal entries and school assignments. Many pages don't have dates, but I can tell which era of my life they correspond to just by looking at the handwriting. In the earliest examples, from elementary school, my print is angular, jagged; even the s's and j's turn sharp corners. In middle school, when I wanted to be more feminine (and was otherwise failing), I made my letters rounder, every curve a bubble ready to pop. In my junior year of high school, when it was time to get serious about applying to college, I switched to cursive, slender and tightly controlled.

On December 10, the US Treasury Department imposed sanctions, including a bar on American investments, on SenseTime, a Chinese artificial intelligence company accused of developing facial-recognition software used to target China's predominantly Muslim Uyghur community. The move, part of a raft of sanctions introduced on Human Rights Day, prompted SenseTime to postpone a planned IPO in Hong Kong. Officially, Treasury added SenseTime to its Chinese Military-Industrial Complex (CMIC) list, created under a different name in November 2020 by then president Trump. In June, President Biden removed some companies from the list, added others, and expanded its scope to include Chinese companies selling surveillance technology. On December 16, eight companies were added to the blacklist, including dronemaker DJI and facial-recognition firm Megvii. The moves show how, despite toned-down rhetoric, Biden has largely maintained Trump's policies toward China.

"Alexa, read us a story." That's one way teachers are using digital assistants, such as the popular Amazon Echo device -- technology that many parents of home-bound students used last year to aid in their children's educational routines -- in the classroom. One school district in California has integrated this technology even further with the Symphony Classroom device from Merlyn Mind, described as the world's first digital assistant for education. The device is powered by Edge AI, combining artificial intelligence with edge computing technology. READ MORE: A digital assistant for educators helps with K–12 classroom management.

LONDON - In decades to come, African farmers may pool their money to buy small robot vehicles to weed their fields or drones that can hover to squirt a few drops of pesticide only where needed. Smartphones already allow farmers in remote areas to snap photos of sick plants, upload them and get a quick diagnosis, plus advice on treatment. Researchers also are trying to train crops like maize and wheat to produce their own nitrogen fertilizer from the air -- a trick soybeans and other legumes use -- and exploring how to make wheat and rice better at photosynthesis in very hot conditions. As warmer, wilder weather linked to climate change brings growing challenges for farmers across the globe -- and as they try to curb their own heat-trapping emissions -- a rush of innovation aimed at helping both rich and poor farmers is now converging in ways that could benefit them all, scientists say. In a hotter world, farmers share "the same problems, the same issues," said Svend Christensen, head of plant and environmental sciences at the University of Copenhagen.