Snap is proud to be an equal opportunity employer, and committed to providing employment opportunities regardless of race, religious creed, color, national origin, ancestry, physical disability, mental disability, medical condition, genetic information, marital status, sex, gender, gender identity, gender expression, pregnancy, childbirth and breastfeeding, age, sexual orientation, military or veteran status, or any other protected classification, in accordance with applicable federal, state, and local laws. If you have a disability or special need that requires accommodation, please don't be shy and contact us at_ _accommodations- • *About Us** Snap Inc. is a camera company. We believe that reinventing the camera represents our greatest opportunity to improve the way people live and communicate. Our products empower people to express themselves, live in the moment, learn about the world, and have fun together. At Snap, we believe that having a team of diverse backgrounds and voices working together will enable us to create innovative products that improve the way people live and communicate. Snap is proud to be an equal opportunity employer, and committed to providing employment opportunities regardless of race, religious creed, color, national origin, ancestry, physical disability, mental disability, medical condition, genetic information, marital status, sex, gender, gender identity, gender expression, pregnancy, childbirth and breastfeeding, age, sexual orientation, military or veteran status, or any other protected classification, in accordance with applicable federal, state, and local laws.

Fox News Flash top headlines are here. Check out what's clicking on Foxnews.com. Facing a growing threat from China, the Navy envisions drone ships keeping an electronic eye on enemy forces across the vast Pacific Ocean, extending the reach of firepower, and keeping sailors out of harm's way. The Navy is speeding development of those robotic ships as an affordable way to keep pace with China's growing fleet while vowing not to repeat costly shipbuilding blunders from recent years. The four largest drone ships are being used together this summer during a multination naval exercise in the Pacific Ocean.

Think you know what lurks beneath you when you take a dip in the ocean? Scientists have discovered 39 species that are'potentially new to science', while exploring up to 16,700 feet (5,100 metres) underwater. A robot was sent down to the abyssal plains of the Clarion-Clipperton Zone (CCZ) in the central Pacific Ocean - one of the least explored regions of the world - to collect specimens of deep sea creatures. The researchers, from the Natural History Museum in London, recovered 39 brand new species of megafauna as well as nine known species. Amongst those found were spindly starfish, tulip-shaped sea sponges, prickly urchins and'gummy squirrel' sea cucumbers.

One of the more evocative platforms for AI art, Midjourney, has now opened to everyone in beta mode. This is the second time that the platform has opened to all as a beta. On July 18, the platform opened up for 24 hours. In an email sent out to Midjourney beta testers on Tuesday, however, founder David Holz wrote that the "Midjourney beta is now open to everyone." Midjourney is one of the more interesting entrants in the small but growing field of AI art, which takes user-generated queries, runs them through an AI algorithm, and lets the algorithm pull from its source images and apply various artistic techniques to the resulting image.

Amid Taiwan's annual Han Kuang war games, a Chinese Unmanned Aerial Vehicle (UAV) was spotted off the island's east coast Monday. The UAV, a reconnaissance and strike vehicle, is dubbed the "Twin-Tailed Scorpion." The "Twin-Tailed Scorpion" reportedly flew from the East China Sea area through the Miyako Strait between the Japanese islands of Okinawa and Miyakojima, a statement issued by the Japanese Defense Ministry said. After entering the Pacific Ocean, the UAV turned southwest and flew past the Sakishima Islands. The UAV was then seen heading northwest toward the Bashi Channel and northeastern Taiwan, its last reported position was off the coast of Taiwan's Hualien County, deep inside the eastern sector of Taiwan's ADIZ, reported Taiwan News.

China has for the first time sent a TB001 combat and reconnaissance drone on a solo mission through Okinawa Prefecture's Miyako Strait, traveling from the East China Sea into the Pacific near Taiwan, according to the Japanese Defense Ministry. The flight of the drone, which has a maximum range of 6,000 kilometers and can carry missiles and precision guided bombs, occurred Monday from the morning through the afternoon. The Defense Ministry said it scrambled fighter jets to monitor the drone, which did not violate the country's territorial airspace. This could be due to a conflict with your ad-blocking or security software. Please add japantimes.co.jp and piano.io to your list of allowed sites.

Prior work has demonstrated that data augmentation is useful for improving dialogue state tracking. However, there are many types of user utterances, while the prior method only considered the simplest one for augmentation, raising the concern about poor generalization capability. In order to better cover diverse dialogue acts and control the generation quality, this paper proposes controllable user dialogue act augmentation (CUDA-DST) to augment user utterances with diverse behaviors. With the augmented data, different state trackers gain improvement and show better robustness, achieving the state-of-the-art performance on MultiWOZ 2.1

If you have a habit of perusing satellite imagery of the world's oceans--and who doesn't, really?--you might get lucky and spot long, thin clouds, like white slashes across the sea. That's a peculiar phenomenon known as a ship track. As cargo ships chug along, flinging sulfur into the atmosphere, they actually trace their routes for satellites to see. That's because those pollutants rise into low-level clouds and plump them up by acting as nuclei that attract water vapor, which also brightens the clouds. Counterintuitively, these pollution-derived tracks actually have a cooling effect on the climate, since brighter clouds bounce more of the sun's energy back into space.

As machine learning has made its way into more and more areas of our lives, concerns about algorithmic bias have escalated. Machine learning models, which today facilitate decisions about everything from hiring and lending to medical diagnosis and criminal sentencing, may appear to be data-driven and impartial, at least to naïve users--but the typically opaque models are only as good the data they are trained on, and only as ethical as the value judgments embedded in the algorithms. The burgeoning field of algorithmic fairness, part of the much broader field of responsible computing, is aiming to remedy the situation. For several years now, along with philosophers, legal scholars, and experts in other fields, computer scientists have been tackling the issue. As Stanford University computer science professor Omer Reingold likes to put it, "We are part of the problem, and we should be part of the solution."

Automated detection of anomalous trajectories is an important problem with considerable applications in intelligent transportation systems. Many existing studies have focused on distinguishing anomalous trajectories from normal trajectories, ignoring the large differences between anomalous trajectories. A recent study has made great progress in identifying abnormal trajectory patterns and proposed a two-stage algorithm for anomalous trajectory detection and classification (ATDC). This algorithm has excellent performance but suffers from a few limitations, such as high time complexity and poor interpretation. Here, we present a careful theoretical and empirical analysis of the ATDC algorithm, showing that the calculation of anomaly scores in both stages can be simplified, and that the second stage of the algorithm is much more important than the first stage. Hence, we develop a FastATDC algorithm that introduces a random sampling strategy in both stages. Experimental results show that FastATDC is 10 to 20 times faster than ATDC on real datasets. Moreover, FastATDC outperforms the baseline algorithms and is comparable to the ATDC algorithm.