PIX connects computers and devices with the physical world around them through the enablement of computer vision. The platform connects developers with a scalable, decentralized image database for use in disparate systems and platforms. PIX customers gain knowledge, service, and information to enable the developement of decentralized augmented reality apps. Recognize and react to playing cards, chips, game pieces, etc.
New York's bid to identify road-going terrorists with facial recognition isn't going very smoothly so far. The Wall Street Journal has obtained a Metropolitan Transportation Authority email showing that a 2018 technology test on New York City's Robert F. Kennedy Bridge not only failed, but failed spectacularly -- it couldn't detect a single face "within acceptable parameters." An MTA spokesperson said the pilot program would continue at RFK as well as other bridges and tunnels, but it's not an auspicious start. The problem may be inherent to the early state of facial recognition at these speeds. Oak Ridge National Laboratory achieved more than 80 percent accuracy in a study that spotted faces through windshields, but that was at low speed.
Today's speech recognition technologies are largely tied up in a few products: think Amazon's Alexa and Google's own assistant. These major voice assistants are driven by commercial interests and only serve the majority languages, mainly English. "Most speech databases are trained with an overrepresentation of certain demographics which results in a bias towards male and white and middle class," Davis added. "Accents and dialects that tend to be under-represented in training datasets.
The announcement of the Nobel Prizes always promises a big week for science. Whom the Norwegian Nobel Committee chooses to honor says a lot about where science is going. The 2018 Nobel Prize will forever stand as a historic marker in the evolution of scientific recognition. For only the third time in history, a woman, Donna Strickland, received the Nobel Prize for Physics. She shares the prize with Arthur Ashkin and Gérard Mourou for their work in the manipulation of lasers and the development of optical tweezers.
For scientists and engineers involved with face-recognition technology,the recently released results of the Face Recognition Grand Challenge–more fully, the Face Recognition Vendor Test (FRVT) 2006 and the Iris Challenge Evaluation (ICE) 2006–have been a quiet triumph. Sponsored by the National Institute of Standards and Technology (NIST), the match up of face-recognition algorithms showed that machine recognition of human individuals has improved tenfold since 2002 and a hundredfold since 1995. Indeed, the best face-recognition algorithms now perform more accurately than most humans can manage. Overall, facial-recognition technology is advancing rapidly. Jonathon Phillips, program manager for the NIST tests and lead author of the agency's report, says that the intended goal of the Face Recognition Grand Challenge was always an order-of-magnitude improvement in recognition performance over the results from 2002.