Optical Character Recognition


Machine Learning Predictions: 60% Of Companies Bring AI Into Everyday Business By 2022

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AI and machine learning are breathing new life and business opportunities into that tired old phrase, "automating paper-based processes." I saw an example of how software developers can inject intelligence into business processes in this VIDEO interview at SAP TechEd with Dr. Matthias Sessler, technical enablement lead, SAP Leonardo Machine Learning Foundation. The demo showed image object detection combined with scene text recognition and optical character recognition (OCR), three of the 23 ready-to-use services on offer from the SAP Leonardo Machine Learning Foundation. Image object detection automatically identifies objects from images like a bus, and often tag teams with scene text recognition, which reads the fine print, such as the station name and line number. "With smartphones, it's so much easier for people to take a picture of something. However, developers need a toolbox so they can quickly build machine learning capabilities to make sense of these images and text," said Sessler.


Global Big Data Conference

#artificialintelligence

AI and machine learning are breathing new life and business opportunities into that tired old phrase, "automating paper-based processes." I saw an example of how software developers can inject intelligence into business processes in this VIDEO interview at SAP TechEd with Dr. Matthias Sessler, technical enablement lead, SAP Leonardo Machine Learning Foundation. The demo showed image object detection combined with scene text recognition and optical character recognition (OCR), three of the 23 ready-to-use services on offer from the SAP Leonardo Machine Learning Foundation. Image object detection automatically identifies objects from images like a bus, and often tag teams with scene text recognition, which reads the fine print, such as the station name and line number. "With smartphones, it's so much easier for people to take a picture of something. However, developers need a toolbox so they can quickly build machine learning capabilities to make sense of these images and text," said Sessler.


Zuckerberg Wants Facebook to Build a Mind-Reading Machine

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For those of us who worry that Facebook may have serious boundary issues when it comes to the personal information of its users, Mark Zuckerberg's recent comments at Harvard should get the heart racing. Zuckerberg dropped by the university last month ostensibly as part of a year of conversations with experts about the role of technology in society, "the opportunities, the challenges, the hopes, and the anxieties." His nearly two-hour interview with Harvard law school professor Jonathan Zittrain in front of Facebook cameras and a classroom of students centered on the company's unprecedented position as a town square for perhaps 2 billion people. To hear the young CEO tell it, Facebook was taking shots from all sides--either it was indifferent to the ethnic hatred festering on its platforms or it was a heavy-handed censor deciding whether an idea was allowed to be expressed. Zuckerberg confessed that he hadn't sought out such an awesome responsibility.


Zuckerberg Wants Facebook to Build a Mind-Reading Machine

WIRED

For those of us who worry that Facebook may have serious boundary issues when it comes to the personal information of its users, Mark Zuckerberg's recent comments at Harvard should get the heart racing. Zuckerberg ostensibly dropped by the university last month as part of a year of conversations with experts about the role of technology in society, "the opportunities, the challenges, the hopes, and the anxieties." His nearly two-hour interview with the Harvard law school professor Jonathan Zittrain in front of Facebook cameras and a classroom of students centered on the company's unprecedented position as a town square for perhaps two billion people. To hear the young CEO tell it, Facebook was taking shots from all sides--either it was indifferent to the ethnic hatred festering on its platforms or it was a heavy-handed censor deciding whether an idea was allowed to be expressed. Zuckerberg confessed that he hadn't sought out such an awesome responsibility.


Artificial intelligence firm aims to outdo OCR, speed loan processing

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AI Foundry is aiming to further cut the time it takes to originate a mortgage by adding, among other things, artificial intelligence technology designed to improve on optical character recognition. The fintech firm on Tuesday launched a new "cognitive business automation platform" aimed at improving automated decision-making related to loans, and a new version of its Agile Mortgages technology, which loan officers use to automate the collection and organization of documents. The new technology classifies data and information that at a 90%-plus accuracy rate is "significantly more accurate than optical character recognition," according to a company press release. "Competition in the mortgage lending industry is intense, and while many companies have deployed point-of-sale solutions for the customer, the back-end processes have not undergone a digital transformation, until now," Steve Butler, founder and general manager of AI Foundry, said in a press release. How does your digital mortgage stack up? "We will truly disrupt the'status quo' by automating the mortgage application process and enabling lenders to complement those front-end capabilities with one-day mortgage approvals. This not only opens enormous potential for acquiring and delighting new customers; it also drives down the cost per mortgage, so lenders can be more profitable."


OrCam - Advanced Wearable AI Devices for the Blind Closing The Gap

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The most advanced wearable assistive technology device for the blind and visually impaired, that reads text, recognizes faces, identifies products and more. Intuitively responds to simple hand gestures. Real time identification of faces is seamlessly announced. Small, lightweight, and magnetically mounts onto virtually any eyeglass frame. Tiny, wireless, and does not require an internet connection.


Four people are allowing strangers to control their smart homes

Engadget

For the next seven weeks, anyone who's inclined can go to 205 Hudson Street in New York City and take over someone else's apartment. Smart devices like the kettles, lighting and speakers of four homes connect directly to laptops in the corner of an art gallery. Cameras are trained on bathrooms, kitchens and living areas. Visitors can sit down and become a human Alexa, playing music, eavesdropping on conversations through microphones and communicating with the inhabitants via text-to-speech. Each home -- three in Brooklyn, one in San Francisco -- will be "live" for two hours a day.


Louisiana City Calls for USPS to Fix Mail Delivery Issues

U.S. News

The Advocate reported Saturday that the resolution adopted last month is just another link a long chain of USPS issues the city wants fixed. Plaquemine Mayor Ed Reeves says residents sometimes go days without mail. Residents say packages are sometimes thrown from delivery vans or delivered to the wrong address and expected mail sometimes never appears.


The Quiet Heroism of Mail Delivery

The Atlantic

On Wednesday, a polar vortex brought bitter cold to the Midwest. Overnight, Chicago reached a low of 21 degrees Fahrenheit below zero, making it slightly colder than Antarctica, Alaska, and the North Pole. Wind chills were 64 degrees below zero in Park Rapids, Minnesota, and 45 degrees below zero in Buffalo, North Dakota, according to the National Weather Service. Schools, restaurants, and businesses closed, and more than 1,000 flights have been canceled. Even the United States Postal Service stalled mail delivery, temporarily.


Extract and visualize clinical entities using Amazon Comprehend Medical Amazon Web Services

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Amazon Comprehend Medical is a new HIPAA-eligible service that uses machine learning (ML) to extract medical information with high accuracy. This reduces the cost, time, and effort of processing large amounts of unstructured medical text. You can extract entities and relationships like medication, diagnosis, and dosage, and you can also extract protected health information (PHI). Using Amazon Comprehend Medical allows end users to get value from raw clinical notes that is otherwise largely unused for analytical purposes because it's difficult to parse. There is immense value associated with extracting information from these notes and integrating it with other medical systems like an Electronic Health Record (EHR) and a Clinical Trial Management System (CTMS).