On a recent Tuesday evening, the experimental musician Julianna Barwick checked into Sister City, a new two-hundred-room boutique hotel on the Lower East Side of Manhattan. If you're having the sort of day that makes you want to minimize human interaction, Sister City is a merciful oasis: there are self-service registration kiosks in the lobby, and each floor features a supply closet containing the sorts of sundries that you'd usually have to request from the concierge. The lobby has sparse but careful décor--clean white walls, cherry-wood furniture, floor tiles in muted shades of green and gray--suggesting a Scandinavian sauna, or perhaps the careful serenity of a Japanese stationery store; the vibe is "Serenity Now!" filtered through Instagram. Barwick, who has long, dark hair and inquisitive eyes, is using the sky immediately above the hotel as a source for a new composition. A camera mounted to the roof of the building sends information about the goings-on in the airspace above the hotel (rain, clouds, pigeons, airplanes, wind, sun, moonlight, drones, helicopters, constellations, what have you) to Pereira's program, which uses Microsoft's artificial intelligence to cue sounds written and recorded by Barwick.
AI and machine learning disruption for Enterprises started happening in the areas such as IT operations management (ITOPs) and Cloud management and SaaS apps. In 2019 CIOs will see disruptive solutions for Cloud & Devops, AI/ML driven IT Ops and Cloud Ops. Customers want AI-driven multi-cloud operations for monitoring, detection, prevention of disruptions. Disruptions cause revenue loss, unhappy users, impacts brand reputation etc. AI and Machine learning had a tremendous impact and success in cyber security solutions. This similar trend will happen for IT Ops, DevOps, Cloud Ops.
Lack of diversity in the artificial intelligence field has reached "a moment of reckoning", according to new findings published by a New York University research center. A "diversity disaster" has contributed to flawed systems that perpetuate gender and racial biases found the survey, published by the AI Now Institute, of more than 150 studies and reports. The AI field, which is overwhelmingly white and male, is at risk of replicating or perpetuating historical biases and power imbalances, the report said. Examples cited include image recognition services making offensive classifications of minorities, chatbots adopting hate speech, and Amazon technology failing to recognize users with darker skin colors. The biases of systems built by the AI industry can be largely attributed to the lack of diversity within the field itself, the report said.
To demonstrate how easy it is to track people without their knowledge, we collected public images of people who worked near Bryant Park (available on their employers' websites, for the most part) and ran one day of footage through Amazon's commercial facial recognition service. Our system detected 2,750 faces from a nine-hour period (not necessarily unique people, since a person could be captured in multiple frames). It returned several possible identifications, including one frame matched to a head shot of Richard Madonna, a professor at the SUNY College of Optometry, with an 89 percent similarity score.
Jobs in banking are some of the most sought after for job seekers -- but plenty of roles may not be around much longer. Despite a year of scandals that entangled many of the country's largest banks, the desire to work at these companies remains high, according to a new report by LinkedIn. Some of the more high-profile scandals include Deutsche Bank's alleged involvement in a global money-laundering scheme and accusations against Well Fargo's auto-loan and mortgage practices. Nonetheless, Bank of America, Goldman Sachs, Citigroup, Wells Fargo, and JPMorgan Chase remain five of the most popular places to work in 2019. LinkedIn attributes the popularity to banks offering increasingly tech-focused jobs that attract talented software engineers and developers out of college.
Uber, once the enfant terrible of the tech industry, put on its big kid pants and publicly filed for IPO this week, attempting to prove, once and for all, that it's got its crap together. Its filing reveals a sprawling company that's made strides since ex-CEO Travis Kalanick was dropping Boober jokes back in 2014--but one that also has a few big, hulking problems on the horizon, like fighting drivers on employee classification issues and, you know, achieving profitability. Also in transpo people and companies trying to prove themselves: Tesla goes off-menu for the $35,000 Model 3, ostensibly to shore up cash and streamline production; another industry insider says, yes, self-driving car hype got ahead of reality; and Audi argues its slightly dispiriting E-tron range numbers matter little compared to its luxury features. Let's get you caught up. Why do new premium electric vehicles keep coming up short on range?
Hyundai's Digital Key allows drivers to unlock and start their car with a smartphone using near-field communication technology. It will debut on the 2020 Hyundai Sonata. Self-driving cars are coming – someday. But for now, carmakers and suppliers are focused on technologies that improve vehicle safety, security and convenience. With the 2019 New York Auto Show set to begin next week with media previews, car companies are looking for ways to stand out from the competition in an era when quality and reliability are similar across brands.
Senior, PhD-level engineers with a background in artificial intelligence and machine learning may have more leverage than just about anyone on Wall Street. Investment banks are desperate for people with AI experience and are going to no end to bring them aboard, industry experience bedamned. J.P. Morgan recently poached AI specialists from Google, Facebook and two leading research universities in the U.S. Goldman Sachs hired away a machine learning guru from Amazon, while Morgan Stanley hired an AI and cloud engineering expert with the background in fashion. Needless to say, banks are surely sweetening offers to recruit expert AI minds away from tech giants and comfy university positions. That said, there aren't a massive number of AI jobs currently available on Wall Street as use of the technology is just ramping up.
Traffic crawls through the wind and snow on the RFK Bridge on Friday in the Queens borough of New York. So reports the Wall Street Journal which reviewed an internal email sent by the Metropolitan Transportation Authority, the state agency which manages all the traffic crossing the area's bridges and tunnels. The MTA email was sent to the office of New York Governor Andrew Cuomo. According to the email, the "initial period for the proof of concept testing at the (Robert F. Kennedy Bridge connecting Manhattan, the Bronx and Queens) for facial recognition has been completed and failed with no faces (0%) being detected within acceptable parameters." Besides the RFK Bridge, the MTA is testing the technology at the Throgs Neck and Whitestone bridges, as well as at the Midtown and Hugh L. Carey tunnels.
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.