Our second example deals with a more challenging problem: the recognition of hand-printed letters of the alphabet. The characters that people print in the ordinary course of filling out forms and questionnaires are surprisingly varied. Gaps abound wherecontinuous lines might be expected; curves and sharp angles appear interchangeably; there is almost every imaginable distortion of slant, shape and size. Even human readers cannot always identify such characters; their error rate is about 3 per cent on randomly selected letters and numbers, seen out of context.
– from Oliver G. Selfridge & Ulric Neisser. PATTERN RECOGNITION BY MACHINE . In Computers & thought, Edward A. Feigenbaum and Julian Feldman (Eds.). MIT Press, Cambridge, MA, USA, 1963. pp. 8-30.
Bangalore: HSBC, the world's leading trade finance bank, is working with IBM to develop a cognitive intelligence solution combining optical character recognition with advanced robotics to make global trade safer and more efficient for thousands of businesses. HSBC's Global Trade and Receivables Finance (GTRF) team facilitates over $500 billion of documentary trade for customers every year, and in doing so must manually review and process up to 100 million pages of documents, ranging from invoices to packing lists and insurance certificates. The new solution uses IBM's advanced analytics technology, including intelligent segmentation and text analytics, to identify, digitise and extract key data within these documents before feeding it into the bank's transaction processing systems; boosting accuracy whilst freeing up staff for more value-adding activities. "The average trade transaction requires 65 data fields to be extracted from 15 different documents, with 40 pages to be reviewed," said Natalie Blyth, HSBC's Global Head of GTRF.
HSBC is using IBM artificial intelligence (AI) technology to process documents related to international trade. Currently around 100 million pages of documents, such as invoices and insurance documents, are manually reviewed and processed by HSBC staff. Using optical character recognition and robotics technology from IBM, HSBC's Global Trade and Receivables Finance (GTRF) is automating the review of documents and sending them automatically to the bank's transaction processing systems. For example, a report from financial services management consultancy Opimas predicted that in 2017, discounting acquisitions of startups, finance firms in the investment sector would spend $1.5bn on robotic process automation, machine learning, deep learning and cognitive analytics, increasing by 75% to $2.8bn in 2021.
Postal Service (USPS) crates sit on the floor at the Brookland Post Office in Washington, D.C., U.S. No customer data was stolen in a recent data breach, USPS officials say. Postal Service is warning that it will likely default on up to $6.9 billion in payments for future retiree health benefits for the fifth straight year. It is citing a coming cash crunch that could disrupt day-to-day mail delivery. Postmaster General Megan Brennan stressed an urgent need for federal regulators to grant the Postal Service wide freedom to increase stamp prices to cover costs.
Deep learning is applicable to a widening range of artificial intelligence problems, such as image classification, speech recognition, text classification, question answering, text-to-speech, and optical character recognition. It is the technology behind photo tagging systems at Facebook and Google, self-driving cars, speech recognition systems on your smartphone, and much more. Deep learning can allow you to create a system that understands how to map such tags to images, learning only from examples. This system can then be applied to new images, automating the task of photo tagging.
Another interesting example of small, high precision data being used to make big gains with AI can be found in the airline industry. One such project aims to dramatically reduce maintenance costs with AI by standardizing maintenance logs. A useful framework for taming data chaos and extracting small high precision data is focusing on the lifecycles of customers, partners, and suppliers. In the world of digital business, companies are always looking for big bang solutions -- some breakthrough that can give them an edge.
And now for some very Canadian news: Mail delivery has been halted in certain areas of Vancouver because a "well-known crow" attacked a mailman. SEE ALSO: Buy this house and you'll live in 2 countries at once Canuck the crow, who is identifiable to locals because of a red tag on its ankle, has been causing trouble in the area for a long time apparently. Canada Post spokeswoman Darcia Kmet told the BBC: "Regular mail delivery was suspended to three homes due to it being unsafe for our employees. Canuck the badass crow has two times more Facebook fans than the state of Arkansas, and his fanbase seems to absolutely love him.
I am using an app called Be My Eyes, an app that connects blind and visually impaired people to sighted volunteers via a remote video connection. In the mid-1970s Ray Kurzweil, a pioneer in optical character recognition (OCR) – software that can recognise printed text – founded Kurzweil Computer Products and programmed omni-font, the first OCR program with the ability to recognise any kind of print style. All the time, companies are finding new ways to improve accessibility and Be My Eyes isn't the only assistive technology company taking advantage of the real time human element, building technology that is based on the creation of dialogue with its users. Earlier this year, Aira helped Erich Manser, who has retinitis pigmentosa, run the Boston marathon.
To see what kind of talent we are currently looking for and submit your resume, please visit: https://a9.com/careers/ We are always looking for talented people with backgrounds in: · Computer Vision · Machine Learning · Natural Language Processing · Backend Infrastructure / Systems Software Development · Analytics Data Mining · Pattern Recognition · Artificial Intelligence · Optical Character Recognition · Server Infrastructure · Augmented Reality · DevOps / Operations Engineer · Software Developer in Test A9 solves some of the biggest challenges in search and advertising. We design, develop, and deploy high performance, fault-tolerant distributed search systems used by millions of Amazon customers every day. A9 advertising drives the publisher products for Amazon's ad programs. To see all of our current openings, please visit: https://a9.com/careers/ To see all of our current openings, please visit: https://a9.com/careers/
This content is designed for audience without any prior Machine learning knowledge. It starts from very basics and goes to advanced topics. We will try to keep this content live and include more and more advanced lab sessions with real life scenarious. Thanks for your support and feedback to make this content better.
Machine learning is the ability for computers to learn without explicit programming. For example, iconoclastic author Tom Peters highlights 159 cognitive biases that impact management decision-making (Peters, Tom. Given a computer is devoid of emotion and the hubris of human ego, it would seem logical that machine learning is not impacted by cognitive bias. Machine learning technology is deployed today for many business uses, including self-driving cars, online recommendation, search engines, handwriting recognition, computer vision, online ad serving, pricing, prediction of equipment failure, credit scoring, fraud detection, OCR (optical character recognition), spam filtering and many other uses.