Unless you're an English speaker, and one with as neutral an American accent as possible, you've probably butted heads with a digital assistant that couldn't understand you. With any luck, a couple of open-source datasets from MLCommons could help future systems grok your voice. The two datasets, which were made generally available in December, are the People's Speech Dataset (PSD), a 30,000-hour database of spontaneous English speech; and the Multilingual Spoken Words Corpus (MSWC), a dataset of some 340,000 keywords in 50 languages. By making both datasets publicly available under CC-BY and CC-BY-SA licenses, MLCommons hopes to democratize machine learning – that is to say, make it available to everyone – and help push the industry toward data-centric AI. David Kanter, executive director and founder of MLCommons, told Nvidia in a podcast this week that he sees data-centric AI as a conceptual pivot from "which model is the most accurate," to "what can we do with data to improve model accuracy."
The saying "data is the new oil," was reportedly coined by British mathematician and marketing whiz Clive Humby in 2006. Data is the fuel powering modern AI models; without enough of it the performance of these systems will sputter and fail. And like oil, the resource is scarce and controlled by big businesses. What do you do if you're a small computer vision company? You can turn to fake data to train your models, and if you're lucky it might just work.
When it comes to clearing the ocean of explosives, the British Royal Navy is turning to robots. Announced April 12, the Ministry of Defense is awarding £32 million (about $42 million) to Dorset-based company Atlas Elektronik to give the fleet an "autonomous mine-hunting capability." Employing robots to hunt and clear the sea of naval mines should make waterways useful for military missions and safe for commercial and civilian use afterwards. "The threat posed by sea mines is constantly evolving," said Simon Bollom, CEO of the UK's Defence Equipment and Support Board, in a statement. To meet this changing threat, the Royal Navy is acquiring a total of nine robotic vehicles, equipped with synthetic aperture sonar and advanced software.
Since graduating in 2014 with a master of fine arts from UCLA's design media arts program, artist Refik Anadol has become a worldwide sensation known for exhibitions that harness state-of-the-art artificial intelligence and machine learning algorithms to create mind-blowing multisensory experiences. His body of work though, is much more than simply mesmerizing feasts for the eyes and ears; it addresses the challenges and possibilities that our ubiquitous computing has imposed on humanity. On April 19, Anadol's latest piece, "Moment of Reflection" will debut on campus, where he also serves as a lecturer in the UCLA Department of Design Media Arts. It was in that department, he learned from innovative professors like Christian Moeller, Casey Reas, Jennifer Steinkamp and Victoria Vesna, all of whom use digital technology to help reshape conceptions of art. "Using data is a scientific approach to something very soulful and spiritual," Anadol said.
When college instructor Angela Dancey wants to decipher whether her first-year English students comprehend what she's trying to get across in class, their facial expressions and body language don't reveal much. "Even in an in-person class, students can be difficult to read. Typically, undergraduates don't communicate much through their faces, especially a lack of understanding," said Dancey, a senior lecturer at the University of Illinois Chicago. Dancey uses tried-and-true methods such as asking students to identify their "muddiest point" -- a concept or idea she said students still struggle with -- following a lecture or discussion. "I ask them to write it down, share it and we address it as a class for everyone's benefit," she said.
Medical imaging is an important part of modern healthcare, enhancing both the precision, reliability and development of treatment for various diseases. Artificial intelligence has also been widely used to further enhance the process. However, conventional medical image diagnosis employing AI algorithms require large amounts of annotations as supervision signals for model training. To acquire accurate labels for the AI algorithms--radiologists, as part of the clinical routine, prepare radiology reports for each of their patients, followed by annotation staff extracting and confirming structured labels from those reports using human-defined rules and existing natural language processing (NLP) tools. The ultimate accuracy of extracted labels hinges on the quality of human work and various NLP tools.
Virtual sales meetings have made it tougher than ever for salespeople to read the room. So, some well funded tech providers are stepping in with a bold sales pitch of their own: that AI can not only help sellers communicate better, but detect the "emotional state" of a deal -- and the people they're selling to. In fact, while AI researchers have attempted to instill human emotion into otherwise cold and calculating robotic machines for decades, sales and customer service software companies including Uniphore and Sybill are building products that use AI in an attempt to help humans understand and respond to human emotion. Virtual meeting powerhouse Zoom also plans to provide similar features in the future. "It's very hard to build rapport in a relationship in that type of environment," said Tim Harris, director of Product Marketing at Uniphore, regarding virtual meetings.
Driverless cars could be tricked into interpreting a red traffic light as green, leaving them vulnerable to attacker-instigated crashes. The legislation around autonomous vehicles varies worldwide. Although fully driverless cars aren't yet on the roads, with such vehicles in development, concerns have been raised that they may be more vulnerable to vandalism and hence robust regulation is needed to protect against this.
The missile test was a crucial step for the Navy's autonomous vessel program, an extensive initiative to develop 21 robot ships over the next few years. The program is a direct response to countries such as China, which have been building sophisticated missile technology to target ships that approach their shores. Robot vessels could be a cheaper and more effective way to protect the seas while putting fewer sailors' lives at risk, former naval officers said.
When applied to the data sets taken from the Long Beach area, the algorithms detected substantially more earthquakes and made it easier to work out how and where they started. And when applied to data from a 2014 earthquake in La Habra, also in California, the team observed four times more seismic detections in the "denoised" data compared with the officially recorded number. Researchers from Penn State have been training deep-learning algorithms to accurately predict how changes in measurements could indicate forthcoming earthquakes--a task that has confounded experts for centuries. And members of the Stanford team previously trained models for phase picking, or measuring the arrival times of seismic waves within an earthquake signal, which can be used to estimate the quake's location. Deep-learning algorithms are particularly useful for earthquake monitoring because they can take the burden off human seismologists, says Paula Koelemeijer, a seismologist at Royal Holloway University of London, who was not involved in this study.