Find open roles in Artificial Intelligence (AI), Machine Learning (ML), Natural Language Processing (NLP), Computer Vision (CV), Data Engineering, Data Analytics, Big Data, and Data Science in general, filtered by job title or popular skill, toolset and products used.

Find open roles in Artificial Intelligence (AI), Machine Learning (ML), Natural Language Processing (NLP), Computer Vision (CV), Data Engineering, Data Analytics, Big Data, and Data Science in general, filtered by job title or popular skill, toolset and products used.

Find open roles in Artificial Intelligence (AI), Machine Learning (ML), Natural Language Processing (NLP), Computer Vision (CV), Data Engineering, Data Analytics, Big Data, and Data Science in general, filtered by job title or popular skill, toolset and products used.

Since the start of the pandemic, many restaurants have seen great success taking their menus online, offering off-premise ordering via digital platforms. In a challenging labor market, these ordering channels provide a more efficient option for restaurants, enabling consumers to act as their own order taker. Yet, for all brands' efforts to incentivize adoption by making these channels as convenient and intuitive as possible, many consumers still prefer to call their order in via phone, the old-fashioned way. The ongoing popularity of phone ordering poses challenges for restaurants at a time when there is not always time to answer all the calls coming in. Victor Matchie, owner of Aloha, Oregon-based sandwich chain Monkey's Subs, spoke with PYMNTS about how the company's conversational artificial intelligence (AI) voice assistant, from speech recognition company SoundHound, enables the restaurant to meet this demand without the bottlenecks that can otherwise result from call-in orders at peak times.

These are just some of the questions being raised by lawmakers, civil libertarians, and privacy advocates in the wake of an ACLU report released last summer that claimed Amazon's facial recognition software, Rekognition, misidentified 28 members of congress as criminals. Rekognition is a general-purpose, application programming interface (API) developers can use to build applications that can detect and analyze scenes, objects, faces, and other items within images. The source of the controversy was a pilot program in which Amazon teamed up with the police departments of two cities, Orlando, Florida and Washington County, Oregon, to explore the use of facial recognition in law enforcement. In January 2019, the Daily Mail reported that the FBI has been testing Rekognition since early 2018. The Project on Government Oversight also revealed via a Freedom of Information Act request that Amazon had also pitched Rekognition to ICE in June 2018.

In Washington County, Oregon, sheriff's deputies use a mobile app to send photos of suspects to Amazon's cloud computing service. The e-commerce giant's algorithms check those faces against a database of tens of thousands of mugshots, using Amazon's Rekognition image analysis service. Such use of facial recognition by law enforcement is essentially unregulated. But some developers of the technology want to change that. In a blog post Thursday, Amazon asked Congress to put some rules around the use of the technology, echoing a call by Microsoft in December.

McAfee isn't known for its work on adversarial machine learning on autonomous vehicles. Yet at the new McAfee Advanced Threat Research Lab in Hillsboro, Oregon, automotive research is on full display. The lab is equipped with sensors used for vehicle autonomy, as well as an operational dashboard for an electronic vehicle. The lab even has two full-sized garage doors to roll in cars for live demos. Automotive attacks are "certainly an area we may be interested in looking into, and it's certainly an area that's emerging as a significant attack vector," Steve Povolny, head of Advanced Threat Research at McAfee, told ZDNet.

SAN FRANCISCO -- Amazon's controversial facial recognition program, Rekognition, falsely identified 28 members of Congress during a test of the program by the American Civil Liberties Union, the civil rights group said Thursday. In its test, the ACLU scanned photos of all members of Congress and had the system compare them with a public database of 25,000 mugshots. The group used the default "confidence threshold" setting of 80 percent for Rekognition, meaning the test counted a face match at 80 percent certainty or more. At that setting, the system misidentified 28 members of Congress, a disproportionate number of whom were people of color, tagging them instead as entirely different people who have been arrested for a crime. The faces of members of Congress used in the test include Republicans and Democrats, men and women and legislators of all ages.

Amazon's online facial recognition system incorrectly matched pictures of US Congress members to mugshots of suspected criminals in a study by the American Civil Liberties Union. The ACLU, a nonprofit headquartered in New York, has called for Congress to ban cops and Feds from using any sort of computer-powered facial recognition technology due to the fact that, well, it sucks. Amazon's AI-powered Rekognition service was previously criticized by the ACLU when it revealed the web giant was aggressively marketing its face-matching tech to police in Washington County, Oregon, and Orlando, Florida. Rekognition is touted by the Bezos Bunch as, among other applications, a way to identify people in real time from surveillance camera footage or from officers' body cameras. The results from the ACLU's latest probing showed that Rekognition mistook images of 28 members of Congress for mugshots of cuffed people suspected of crimes.

The Orlando Police Department said it would not immediately renew a pilot program with Amazon.com for controversial facial-recognition technology, a decision that civil rights advocates claimed as a victory. Orlando had deployed software, known as Rekognition, in five cameras at police headquarters and three cameras downtown during a six-month trial period. "The City of Orlando is always looking for new solutions to further our ability to keep our residents and visitors safe," the city of Orlando and the Orlando Police Department said in a joint statement Monday. "Partnering with innovative companies to test new technology -- while also ensuring we uphold privacy laws and in no way violate the rights of others -- is critical to us as we work to further keep our community safe." The existence of the pilot program was first revealed last month, when the American Civil Liberties Union published documents detailing Amazon's sale of powerful facial-recognition tools to several law enforcement agencies, including in Orlando and Washington County, Ore.