Computers cannot think, though increasingly, they can do things only humans were able to do. A product of the field of research known as artificial intelligence, cognitive technologies have been evolving over decades. It is now possible to automate tasks that require human perceptual skills, such as recognizing handwriting or identifying faces, and those that require cognitive skills, such as planning, reasoning from partial or uncertain information, and learning. Technologies able to perform tasks such as these, traditionally assumed to require human intelligence, are known as cognitive technologies. Businesses are taking a new look at them because some have improved dramatically in recent years, with impressive gains in computer vision, natural language processing, speech recognition, and robotics, among other areas.

Robots may be used to care for elderly people lacking family aid, according to a team of academics who estimated the highly advanced artificial intelligence could be available within three years, BBC News reported Monday. The international team, sponsored by the European Union and Japanese government, have begun a $2.5 million project in an attempt to develop robots capable of looking after older people. More than 1 million elderly people were lacking the daily living assistance they need, according to charity Age UK. Researchers said robots would not only help out with physical tasks, but also provide companionship with uniquely programmed, culturally sensitive personalities. "Assistive, intelligent robots for older people could relieve pressures in hospitals and care homes as well as improving care delivery at home and promoting independent living for the elderly," Professor Irena Papadopoulos, an expert in transcultural nursing, told BBC. "It is not a question of replacing human support but enhancing and complementing existing care."

Iranian-born bioengineer researcher Nima Enayati works on a robotic surgery machine during an interview with the Associated Press at the Polytechnic University of Milan, Italy, Tuesday, Jan. 31, 2017. An Iranian researcher at Milan's Polytechnic University, Enayati was refused check-in Monday at Milan's Malpensa Airport for his U.S.-bound flight on Turkish Airlines after the Trump administration's executive order came down. Iranian-born bioengineer researcher Nima Enayati works on a robotic surgery machine during an interview with the Associated Press at the Polytechnic University of Milan, Italy, Tuesday, Jan. 31, 2017. An Iranian researcher at Milan's Polytechnic University, Enayati was refused check-in Monday at Milan's Malpensa Airport for his U.S.-bound flight on Turkish Airlines after the Trump administration's executive order came down. Iranian-born bioengineer researcher Nima Enayati stands as he works on a robotic surgery machine during an interview with the Associated Press at the Polytechnic University of Milan, Italy, Tuesday, Jan. 31, 2017.

Today Intel announced record results on a new benchmark in deep learning and convolutional neural networks (CNN). Developed with ZTE, a leading technology telecommunications equipment and systems company, the image recognition technology is what many companies in Internet search and AI are trying to advance. Perception, such as recognizing a face in an image, is one of the essential goals of the ZTE 5G System," said Duan Xiangyang, vice president of the ZTE Wireless Institute. "Deep learning technology is very important as it can enable such perception in mobile edge computing systems, thus making ZTE's 5G System smarter." The test took place in Nanjing City, China, where ZTE's engineers used Intel's midrange Arria 10 FPGA for a cloud inferencing application using a CNN algorithm. ZTE has achieved a new record – beyond a thousand images per second in facial recognition – with what is known as "theoretical high accuracy" achieved for their custom topology. Intel's Arria 10 FPGA accelerated the raw design performance more than 10 times while maintaining the accuracy. The Arria 10 FPGA provides up to 1.5 teraflops (TFLOPs) single precision floating-point processing performance, 1.15 million logic elements, and more than a terabit-per-second high-speed connectivity. Such deep learning designs can be seamlessly migrated from the Arria 10 FPGA family to the high-end Intel Stratix 10 FPGA family, and users can expect up to nine times performance boost. Besides the impressive increase in performance, the team at the ZTE Wireless Institute sped design time with the use of the OpenCL programming language. With the Intel reference design, and using the Intel SDK for OpenCL to program the FPGA, our development time was greatly shortened," said Xiong Tiankui, chief engineer, ZTE Wireless Institute.

Robotic cars are great at monitoring other cars, and they're getting better at noticing pedestrians, squirrels, and birds. The main challenge, though, is posed by the lightest, quietest, swerviest vehicles on the road. "Bicycles are probably the most difficult detection problem that autonomous vehicle systems face," says UC Berkeley research engineer Steven Shladover. Nuno Vasconcelos, a visual computing expert at the University of California, San Diego, says bikes pose a complex detection problem because they are relatively small, fast and heterogenous. "A car is basically a big block of stuff. A bicycle has much less mass and also there can be more variation in appearance -- there are more shapes and colors and people hang stuff on them."

The firm that makes Vespa scooter has unveiled a new two-wheeled vehicle – but this model isn't designed to transport humans. Made by the the Italian firm's Boston Fast Forward R&D lab, Gita is a robot cargo carrier capable of hauling up to 40 pounds (18 kg) of goods while following a human operator or moving autonomously through a mapped environment. The blue ball-like machine stands about 26 inches (66 cm) tall and travels at bicycle speeds - up to 22 mph (35 km/h). The firm that makes Vespa scooter unveiled a new two-wheeled vehicle. Users simply unlock the top lid and place anything from groceries to laundry inside of the machine.

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The 2017 Benzinga Global Fintech Awards is a competition to showcase the companies with the most impressive technology that are paving the future in financial services and capital markets. To get you prepared for this year's awards, Benzinga will profile each fintech company that has applied. For this installment, we spoke with I Know First (answers have been edited for length and clarity). I Know First: I Know First's self-learning forecasting algorithm utilizes artificial intelligence and machine learning techniques to find relationships and patterns in large sets of historical stock market data in order to analyze and predict behavior and identify the best daily market opportunities. I Know First: On the institutional side, our typical clients are family offices, hedge funds and other asset management firms, as well as banks.

Chinese search giant Baidu (NASDAQ: BIDU) is often dismissed as a slow-growth tech stock that has run out of room to grow. Its heavy investments in expanding its ecosystem into adjacent markets have weighed down its bottom line growth, making the stock seem like dead money. Despite those challenges, however, I recently started a new position in Baidu for four main reasons. That dominant position enables it to expand its ecosystem in the same way as Alphabet's (NASDAQ: GOOG) (NASDAQ: GOOGL) Google. Its sprawling ecosystem now includes Baidu Maps, video streaming site iQiyi, its Duer voice assistant, the Baidu Wallet payment platform, numerous portal sites, and various O2O (online-to-offline) services in its "monolithic" mobile app.

When I was a kid dreaming of being a game developer, I hoped that in the future I'd be joining a large studio and working on a blockbuster title. Things didn't quite pan out that way. After leaving university with a fellow student, I am now the co-founder of my own company, Vlambeer, renowned for successful game releases such as Nuclear Throne and Ridiculous Fishing. I was born in the Netherlands, the son of an Egyptian immigrant and a Dutch mother, and was raised as a proud Muslim. For the past years, much of my travel to the United States has led to secondary selection, investigation, or interrogation.