Sphere of application 1: Medicine
A team of researchers from the University of Nottingham has developed four machine learning algorithms to assess the risk of patients' cardiovascular disease. The training used data from 378,000 British patients. Trained artificial intelligence determined the risk of cardiac disease more effectively than real doctors. The accuracy of the algorithm is between 74 and 76.4 percent (a standard system of eight factors developed by the American College of Cardiology only provides 72.8 percent accuracy).
Sphere of application 2: finance
Japanese insurance company Fukoku Mutual Life Insurance has signed a contract with IBM. According to this contract, 34 employees of the Japanese company will replace IBM Watson Explorer AI. The neural network will review tens of thousands of medical certificates and take into account the number of hospital visits, postponed surgeries and other factors to determine the terms and conditions of customer insurance. Fukoku Mutual Life Insurance is confident that using IBM Watson will increase productivity by 30% and will pay off in two years. Machine training helps identify potential fraud cases in various areas of life. Such a tool is used, for example, PayPal - as part of the fight against money laundering, the company compares millions of transactions and finds suspicious among them. As a result, fraudulent transactions in PayPal are at a record low of 0.32%, while the standard in the financial sector is 1.32%.
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Sphere of application 3: commerce
Artificial Intelligence has significantly improved recommendation mechanisms in online stores and services. Algorithms based on machine learning analyze your behavior on the site and compare it with millions of other users. All in order to determine which product you are most likely to buy. The recommendation engine provides Amazon with 35% of sales. Brain's algorithm used by YouTube to recommend content has made it possible for people to find almost 70% of the videos they see on the site through recommendations (not links or subscriptions). WSJ reported that the use of artificial intelligence for recommenders is one of the factors that has contributed to a 10-fold increase in audience over the past five years. The Yandex Data Factory algorithm is able to predict the impact of promotions on product sales. Analyzing the sales history, as well as the type and range of the store, the algorithm gave 87% accurate (accurate to box) and 61% ultra accurate (accurate to package) forecasts. Neural networks that analyze the natural language can be used to create chat bots that allow customers to get the necessary information about the company's products. This will reduce costs for call center teams. Such a robot already works in the Moscow Government reception room and handles about 5% of requests. The bot is able to suggest, among other things, the location of the nearest MFC and the schedule of hot water shutdown. Albert is also based on neural network technology, a full cycle marketing platform that performs almost all operations independently. Its lingerie company Cosabella eventually disbanded its own marketing department and fully trusted the platform.
Sphere of application 4: transportation
Unmanned cars - a concept on which most large concerns, as well as technology companies (Google, Uber, Yandex and others) and start-ups are working - rely on neural networks in their work. Artificial Intelligence is responsible for identifying surrounding objects - whether it is another car, a pedestrian or another obstacle. The potential of artificial intelligence in this area is not limited to autopilot. Recent survey of IBM has shown: 74% of top managers of the automotive industry expect smart cars to be on the road by 2025. These cars, which are integrated into the Internet (see our previous long-read), will collect information on passenger preferences and automatically adjust interior temperature, radio volume, seat position and other parameters. In addition to piloting, the system will also inform about emerging problems (and even try to solve them yourself) and the situation on the road.
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Sphere of application 5: industry
The neural network, developed by Mark Waller of Shanghai University, specializes in the development of synthetic molecules. The algorithm was a six-stage synthesis of benzopiran sulfonamide derivative (required for Alzheimer's treatment) in just 5.4 seconds. Yandex Data Factory tools help in steelmaking: the metal scrap used for steel production is often not homogeneous in composition. In order for steel to meet the standards, it is always necessary to take into account the specificity of scrap and introduce special additives when smelting steel. This is usually done by specially trained technologists. However, since these plants collect a lot of information about the incoming raw materials, additives used and the result, this information is more efficient to process the neural network. According to Yandex, introduction of neural networks allows reducing expenses of expensive ferroalloys by 5%. Similarly, a neural network is able to help in glass processing. Now it is an unprofitable, though useful, business that needs government subsidies. The use of machine learning technologies will significantly reduce costs.
Sphere of application 6: agriculture
Microsoft engineers, together with scientists from ICRISAT, are using artificial intelligence to determine the best sowing time in India. The application, which uses the Microsoft Cortana Intelligence Suite, also monitors soil conditions and selects the necessary fertilizers. Initially, only 175 farmers from 7 villages participated in the programme. They did not start sowing until they were notified by SMS. As a result, they harvested 30-40% more crops than usual.
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Sphere of application 7: entertainment and arts
Last year applications using neural networks for photo and video processing were released and instantly became popular: MSQRD from Belarusian developers (later the service was bought by Facebook), and Russian Prisma and Mlvch. Another service, Algorithmia, paints black and white photos. Yandex is successfully experimenting with music: the company's neural networks have already recorded two albums: in the style of Nirvana and "Civil Defense". And the music written by the neural network to the classical composer Alexander Skryabin was performed by a chamber orchestra, which makes you think again about whether the robot will be able to compose a symphony. The neural network, created by Sony staff, was inspired by Bach. The Japanese algorithm wrote the book "The Day the Computer Wrote a Novel". Despite the fact that people helped the inexperienced writer with the characters and storylines, the computer did a great job - in the end, one of his works passed the selection stage of the prestigious literary prize. Neurosets also wrote sequels to Harry Potter and the Game of Thrones. In 2015, the AlphaGo neural network, developed by the Google DeepMind team, was the first program to win the professional Go player. And in May this year, the program defeated the world's strongest go player, Kae-jae. This was a breakthrough, because for a long time it was believed that computers do not have the intuition needed to play go. О
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Sphere of application 8: security
A team of developers from the University of Technology of Sydney presented drones for beach patrol. The drones will focus on finding sharks in coastal waters and warning people on the beaches. Video data analysis is carried out by neural networks, which has a significant impact on the results: the developers claim that sharks are up to 90% likely to be detected and identified, while the operator viewing video from drones only recognizes sharks 20-30% successfully. Australia is the second largest shark attacker in the world after the USA. In 2016, 26 shark attacks were recorded in that country, two of which resulted in the death of people. In 2014, Kaspersky Lab reported that their antivirus registered 325,000 new infected files daily. At the same time, a study by Deep Instinct company showed that the new versions of viruses are almost the same as the previous ones - the change ranges from 2% to 10%. The self-learning model developed by Deep Instinct, based on this information, is able to detect infected files with high accuracy. Neural networks are also able to search for certain patterns in how information is stored in cloud services and report detected anomalies that could lead to security breaches.