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Showing posts with label artificial intelligence. Show all posts
Showing posts with label artificial intelligence. Show all posts
  • ARTIFICIAL INTELLIGENCE HAS LEARNED HOW TO MODEL TISSUE BEHAVIOR BY WATCHING VIDEOS

    Researchers at MIT CSAIL, Nvidia, the University of Washington, and the University of Toronto have created an artificial intelligence system that studies the physical effects that affect tissue materials. AI trained by watching the video. The developers claim that the system can predict the behavior of tissues and their interaction, even if they have not seen such a thing before. For example, create an emulation involving multiple shirts and trousers.


    The researchers created a network of visual causal relationships (V-CDN), which interacts with three modules: one for visual perception, one for structural inference and one for predicting dynamics.

    The developers tried to lay the foundation of the system understanding of the reasons for the AI ​​to create possible alternatives to movement. For example, in an image containing a pair of balls connected to each other by a spring, the system will predict the effect of the spring on the interaction of the balls. Thus, AI makes various predictions.

    The perception model is trained to extract certain key points (areas of interest) from the video. The exposure module then defines the variables that control the interactions between pairs of key points. Meanwhile, the dynamics module learns to predict future movements of key points based on the neural network graph created by the output module.

    Researchers studied V-CDN in a simulated medium containing fabrics of various shapes: shirts, pants and towels of various lengths. The developers interacted with the contours of the tissues to deform and move the clothes, and the AI ​​reacted to their actions and tried to predict how the fabric model would behave. The researchers aimed to create a single model that could process tissues of different types and shapes.

    The results show that V-CDN performance increased as the system observed a large array of video frames. According to the researchers, the operation of the system is comparable to intuition. More previous observations provide a better estimate of the variables that control tissue behavior.

    “The model does not imply access to the main causal graph, nor the dynamics that describes the effect of physical interactions,” the scientists wrote in a text describing the system. “Instead, the system learns to create dependency structures and model causal mechanisms from video without human intervention, which we hope can facilitate future research with more generalized visual thinking systems.”

    Researchers note that V-CDN does not solve the daunting task of causal modeling. Rather, developers see the work as an initial step towards a broader study of creating a physically justified “visual intelligence” that can simulate dynamic changes. Researchers hope to draw people's attention to this task and inspire future research.

    Causation lies at the heart of human knowledge. This allows people to reason about the environment and make hypothetical predictions regarding scenarios, which may differ significantly from previous experience. Modern artificial intelligence does not yet know how to make decisions based on causal relationships. Therefore, one of the main tasks in machine learning is the search and interpretation of cause-effect relationships in large data sets. For example, from videos. Then, the systems are trained based on this information.
  • Artificial Intelligence: How Ai Can Replace You?

    How artificial intelligence solves tasks that were previously considered exclusively “human” Artificial intelligence (AI) is next to us at every step: it gives results in search engines, finds the nearest taxi, manages a home robot vacuum cleaner and does dozens of other household chores. This is familiar and not surprising. But AI also came to those areas that were still considered the prerogative of man.

    Artificial interviewer can reduce bank risks and hire people

    Artificial interviewer can reduce bank risks and hire people

    The volume of consumer lending in China is constantly growing (over the year - by 15%, over two years - by 40%), and the amount of outstanding loans at the end of 2019 reached $ 1.5 trillion . Banks seek to reduce risks, including through AI.

    For example, customers of the Chinese bank Ping An  can take a loan through a mobile application by answering the usual questions in such cases. They do not suspect that while they respond, the application scans their face. AI evaluates facial expressions and recognizes up to 50 signs of lies. If the borrower behaves suspiciously, AI recommends that human employees double-check the client.

    The Skolkovo resident “Importrus” has an algorithm that conducts video interviews, explores the person’s social networks, collects “files” and describes his personal qualities with an accuracy of 99%. While it is used for hiring and evaluating employees, but nothing prevents him from trying himself in other professions that require empathy and insight.

    A sales robot has a conversion like a live operator

    A sales robot has a conversion like a live operator

    Typically, telephone robots route calls or solve typical problems, and to successfully conduct a “cold” call or solve incoming tasks, human operators are needed. In any case, this was before. Today, AI robots work with incoming and outgoing calls as well as a full-fledged sales employee.

    The "Zvonobot" from the company "Widget" (another Skolkovo resident) recognizes speech in several languages ​​and synthesizes the answers. It integrates with CRM systems, can call the entire customer base in 10 minutes or receive incoming calls, conduct surveys, and even do mailings. Moreover, it is 10 times cheaper than the call center and reaches a conversion rate of 47%.

    AI is able to maintain a conversation, even if it follows an atypical scenario. No matter what the interlocutor says, the robot will understand it only a split second after the completion of the phrase and give a meaningful answer. He even pauses in conversation, as is characteristic of people. A conversation with such a robot can not be distinguished from communication with a living person - and this increases its effectiveness. Another similar robot with AI, having made 90 thousand calls in 3 days, achieved a conversion, like a human operator .

    There are telephone robots capable of accurately recognizing a person by voice, making remote service at banks, insurance companies and pension funds more convenient for millions of people. A similar system created by our compatriots from the MDG Innovation company is used in 75 countries of the world - including the world's first nationwide voice recognition system in Mexico.

    AI freed journalists from routine work

    AI freed journalists from routine work

    Since 2014, subscribers to the largest publications have been reading notes written by artificial intelligence. The Associated Press entrusted him with a routine: articles-reports on the financial results of companies for which you need to collect data for a long time, but you do not need to give expert opinion. AI makes it 15 times more productive than human journalists. Each quarter, AI analyzes 3,000 corporate reports and publishes up to 4,400 notes, while people managed to make only 300 before. Also, AI  can report on baseball games. By taking on such "non-creative" topics, AI freed up 20% of the time for journalists for more complex and interesting tasks. Later similar systems were used by Bloomberg and Reuters .

    And in  The Guardian in 2019, the first story came out for the authorship of AI. He analyzed the statistics on donations for political parties in Australia, gave his conclusions, compiled a rating of parties for the article, and drew graphs.

    AI helps investigate crimes

    AI helps investigate crimes

    Dutch police use self-learning algorithms to analyze large amounts of data. AI helps not only find the relationship between suspected and criminal networks, but also quickly search in texts and images for suspicious words, faces and objects associated with weapons, drugs, terrorism, etc. This helps to reveal the crimes committed and identify those preparing.

    However, the use of AI has so far been limited for legal and ethical reasons. For example, the courts and the police must be sure that he will not have “tunnel vision” when, based on the processed statistics, the AI ​​forms a “prejudice” against certain groups.

    Robots teach English, reducing school costs by 50 times

    Robots teach English, reducing school costs by 50 times

    Since 2020, English has become a compulsory subject for all Japanese students since grade 3. The country needed more teachers and especially English teacher assistants. But the salary of an assistant is about $ 44,000 a year, and many schools cannot afford to hire more staff.

    Predicting this risk, the Ministry of Education of Japan in 2018 launched a project to create a robot teacher . Now such robots work already in 500 classes and help to teach children spoken language. They conduct dialogs and check the pronunciation of each student - this is what teachers' assistants usually do. The robot stores information for each lesson of each student, so that a living teacher can easily check his progress. At the same time, the robot costs about $ 900 - 50 times less than the assistant’s annual salary. It is quite accessible for schools and will allow them to fulfill the curriculum.

    AI makes diagnoses, speeding up the work of doctors up to 22%

    AI makes diagnoses, speeding up the work of doctors up to 22%

    By learning from the accumulated medical data, AI can help doctors. For example, the treatment of cancer begins after the doctor performs a biopsy and determines the type of cancer. It happens that the picture is unclear, and then the doctor asks for a “second opinion” from colleagues. But if you transfer the tests to another doctor, the start of treatment is delayed. Therefore, instead of a living colleague, doctors turn to AI.

    The adaptive artificial intelligence created by Philips instantly evaluates test results and gives a second opinion with the same accuracy as a human doctor. The findings of AI and the doctor coincide in 86-87%, and two independent doctors - in 80-90% of cases. Already today, adaptive AI can accelerate the work of doctors up to 22% .

    AI, which previously diagnosed oncology, has come to the forefront in the fight against coronavirus. Hospitals are not designed for emergency x-ray diagnostics of thousands of people, and test systems are sorely lacking. Therefore, the AI ​​of the Skolkovo company “Third Opinion” is now checking X-ray images of the lungs, looking for signs characteristic of COVID-19 and making a  diagnosis with an accuracy of 94%. AI helps to detect pneumonia at an early stage, connect a person to mechanical ventilation in time, or change treatment tactics. In the first weeks of using AI, more than 400 cases of pneumonia caused by COVID-19 were detected.

    And the Skolkovo resident BID Technologies developed an industrial robot with AI that makes Yaroslavl shopping centers safer in the context of the coronavirus epidemic - they disinfect shopping carts after each visitor in  30 seconds .

    AI leads planes safer than humans

    AI leads planes safer than humans

    Air crashes occur very rarely (in one of  five million flights ), and in 60% of cases - due to the fault of people. To reduce risks, flights of airliners are increasingly transferring “to the hands” of AI.

    Already on a regular flight, a Boeing 777 pilot flies a plane manually for only 7 minutes per flight, while an Airbus pilot is even less. In January 2020, Airbus learned to take off without human intervention , and by the end of the year the company plans to test the automatic landing. And  by 2025, you can wait for the first unmanned airliners. They can make flights safer, but also cheaper, allowing airlines to save up to $ 35 billion annually and lower ticket prices by 10%.

    True, polls show that  54% of passengers are not yet ready to fly planes without a human pilot. But building trust in them is a matter of time.

    AI helps visually impaired people better represent the world

    AI helps visually impaired people better represent the world

    According to WHO, there are 285 million visually impaired and blind people in the world. To help them, states improve their habitats, and technology giants create electronic assistants.

    For example, the Chinese assistant gadget for blind and visually impaired people Baidu DuLight looks like a miniature camera connected to an earpiece. AI recognizes the image from the camera and through the earpiece tells the owner what is in front of him: what is the road sign, what products are on the shelf in the refrigerator, what brand of clothing is in the store, and so on. Also, the AI ​​remembers and recognizes the faces of people and informs the owner when a friend, relative or acquaintance comes towards.

    Replacing sellers and cash registers, AI increased store turnover by 50%

    Replacing sellers and cash registers, AI increased store turnover by 50%


    About 14% of purchases in the world went online, and in developed countries there are more and more non-cash payments (in Sweden - 98% of all payments, in the USA - 80% ). The next step in the automation of trade is retail, in particular, Amazon GO stores without sellers and cash desks.

    After collecting goods from the shelves, the buyer simply leaves the store, and their cost is automatically debited from his Amazon account. This is monitored by the AI, which collects information from many channels: from  RFID tags on goods , video cameras in the hall, etc. As a result, buyers quickly and without queues make purchases, and the company reduces expenditure items such as salaries of sellers, maintenance of cash registers and collection. Overall, according to RBC Capital Markets analysts, Amazon Go stores average 50% more revenue than regular convenience stores.

    AI creates advertising and art

    AI creates advertising and art

    In 2018, at a Christie's auction for $ 432,000, the painting “Portrait of Edmond Belami” was sold. It was created by artificial intelligence, having previously studied 15,000 portraits of the XIV-XX centuries. Moreover, the AI ​​had two independent parts: the “artist” painted pictures similar to a real portrait, and the “controller” evaluated each option as “real” or “artificial”.

    AI also has talent in music - for example, the British startup Jukedeck composes electronic music, which non-specialists do not distinguish from sets of real DJs.

    In addition, AI is already creating feature and commercial films. One system, having studied the best car ads, wrote a script for a Lexus ad . Another AI came up with the script, dialogs and music for the fantastic Sunspring short film, an anti-utopia in which robots took away work from people. The third seems to leave marketers and SMMs out of work. The Skolkovo resident Cubo platform analyzes various types of online advertising: SEO, context, email. For a week, AI develops an individual advertising strategy taking into account the specifics of the business and redistributes budgets for the advertising that leads customers. This reduces the visitor’s cost by up to 20% and increases conversion by 42%.

    Questions about the future

    Questions about the future

    Artificial intelligence takes on new challenges, and the AI ​​market will grow from $ 37.5 billion in 2019 to $ 100 billion by 2023. This raises a lot of questions. Some are global: how to protect the interests of people in order to prevent the Sunspring scenario? Others are private, but no less complex. For example, who owns the rights to the work of AI - is he himself or the author of the algorithm? What AI products will get the right to enter people's lives?

    The world seeks answers at universities, company headquarters, and global thematic conferences such as AI World in the USA, AI & Big Data Expo in the Netherlands. The next such online conference - Startup Village Livestream (May 21-22) - is organized by the largest Russian innovation center Skolkovo, which celebrates its 10th anniversary this year. Experts and businessmen participate in such meetings to find ways to develop AI in a joint discussion. Those who plan to work with AI - to hear new ideas, find investors and launch their project. And all together - to lay the foundation for future relationships between people and AI.
  • 7 Industries Of The Future That Will Change Our Lives

    What will this life be like when Industries Of The Future, completely displaces a person from entire spheres and industries, leaving him the role of a passive observer and recipient of services? Dmitry Grishin, chairman of the board of directors of Mail.Ru Group and founder of Grishin Robotics, together with RBC magazine selected seven industries that already exist and promise to become huge

    Unmanned Vehicles


    Unmanned Vehicles

    “We'll turn parking lots into parks again”, a quote from John Zimmer, co-founder of Lyft taxi calling mobile app, best illustrates the development prospects of the unmanned vehicle industry. The technology, which several years ago was part of a series of futuristic projects, is booming with the help of technology corporations and automakers and threatens to change the way the whole economy of the future. Analysts of leading consulting companies in the world are confident that the auto Industries Of The Future is on the verge of an “unmanned” revolution. McKinsey predicts that by 2030, 15% of all new cars sold will be driven without driver assistance. Goldman Sachs experts in the same horizon expect an indicator of 60% of sales. Even in a less distant future - 2020 - 10 million vehicles will be honing unmanned technology on roads around the world, BI Intelligence experts calculated.

    Tesla began to equip all new cars with autopilot function, Renault unmanned electric vehicles brought ruTonomy startup to Boston streets, Google cars drove more than 3 million km on five states, GM bought a startup for developing unmanned vehicles Cruise for $ 600 million, Uber and Volvo launched in Pittsburgh a test project of unmanned taxis worth $ 300 million, and Otto (which was bought by Uber in June for $ 680 million) organized the first ever commercial cargo transportation (50 thousand cans of beer) - all this is news only in recent months. According to the forecast of Morgan Stanley, the mass introduction of technology will happen in 2026, when unmanned trucking will finally move from the category of utopia to economic reality, and the tipping point will come at the turn of the 2020s.

    In the coming years, market players will have to agree on the rules for the "existence" of unmanned vehicles with regulators. According to the Geneva Convention, a person must be present at the wheel of a vehicle, and experiments in all countries are still being carried out in coordination with the authorities. They also need to bring to mind the technology of completely "inhuman" control, when driver intervention will not be required at any stage of the movement.

    According to the National Transportation Safety Administration (NHTSA) classification, the digitalization of the driving process can be divided into five levels. The first three levels are combined under the acronym ADAS - advanced driver assistance systems, "advanced driver support technologies." The first is “help”, when the car helps the driver to perform one specific action (for example, holding the speed with cruise control), but the person controls it. The second level is “building confidence”, when the machine itself moves along a certain route, but in case of deviation from the given parameters returns “reins of government” to a person. This is, for example, the Tesla autopilot. The third level is called "control capture" and involves the ability of the machine to perform maneuvers (for example, rebuild in another row when obstacles arise on the way). This skill can boast of a prototype Audi A7, already plowing California tracks.

    A person at the third level takes control when weather conditions disrupt the operation of sensors or there is no marking on the road. The fourth level - “inside the college” - involves fully autonomous vehicle movement, but only in a limited area known to autopilot, for example, on the campus. Finally, the fifth level - “maturity” - is an unmanned vehicle capable of driving itself in any place and under any external conditions. Neither the driver, nor the gas and brake pedals are just a fully autonomous car, in which a person can spend as much as he wants. To this level, Google, one of the industry's pioneers, wants to bring its product up. And startups Delphi and Mobileye promise commercial copies of cars of levels four and five in 2019-2020.

    When the technology is scaled up, unmanned vehicles will reduce the statistics of fatal accidents, which in 90% of cases occur due to the fault of the driver. According to WHO, an average of at least 3.5 thousand such accidents per day occur in the world. Tesla's accumulated statistics show that autopilot at least halves the risk of the “human factor”. The first “unmanned” accident in which the driver died died in June 2016, after cars from Ilon Mask drove over 200 million km in automatic mode. In an ordinary car, the probability of death on US roads is 1 per 97 million km. Also, unmanned vehicles will reduce harmful emissions into the atmosphere by at least 20%, according to the results of the European  Industries Of The Future experiment SARTRE. According to Morgan Stanley, cars account for 45% of global fuel consumption - about 1,

    Delivery Drones


    Delivery Drones

    June 2016 was a milestone in the history of the American industry of unmanned aerial vehicles (UAVs), or, as they are often called in everyday life, drones. The United States Federal Aviation Administration (FAA) has agreed to use the devices for commercial purposes. At the same time, the regulator stipulated a whole set of restrictions: the drone operator must not lose sight of it, the drone cannot rise to a height of more than 121 m and weigh more than 25 kg, the business must re-register with the FAA every two years.

    These barriers are designed to minimize the risk of drones colliding with airplanes and other objects in the air, but they also inhibit the most ambitious projects using quadrocopters, for example, to deliver goods to the world's largest online retailer Amazon.com. Nevertheless, even the industry’s half-hearted decision was met with glee: for example, the world's largest drone manufacturer, the Chinese DJI (investors estimate $ 12 billion, revenue in 2019 $ 1 billion), called the approval of the US regulator a “vote of confidence”.

    U.S. Secretary of Transportation Anthony Fox in an interview with Wired magazine promised to further liberalize the booming  Industries Of The Future until his resignation in January 2019. It is possible that drones will release certain trajectories and limit their use in aviation flight zones. Strict regulation is necessary in any country with developed domestic air traffic: only in the United States, such flights take place at 30 thousand per day, Fox explained. He draws inspiration for future reforms from the success story of Zipline startup, which attracted about $ 50 million from investors. Zipline is the first example of a manufacturer and operator of drones that has harmonized the flight system of aircraft at the national level.

    Since October 2019, American drones have been delivering drugs and biomaterials between 21 medical facilities in Rwanda.

    According to the forecast of the analytical company Markets & Markets, the industry's growth rates will not drop below 32% year-on-year until at least 2020, when the market volume reaches $ 5.6 billion. BI Intelligence experts are even more optimistic and give a forecast of the market volume of $ 12 billion by 2021 year. Investors reinforce these expectations with solid investments: according to estimates by CB Insights experts, in 2015-2016, the volume of investments in drone manufacturers exceeded $ 830 million, which is almost 4.5 times more than the cumulative indicator of the previous three years.

    DJI's hegemony is threatened by ever new competitors, often not initially focused on the development of drones. For example, in the direction of drones, the business of the manufacturer of “extreme” GoPro cameras is organically developing (revenue in 2015 is $ 1.4 billion). In July 2016, the Facebook drone - Aquila, went on a test flight. This drone with a wingspan comparable to the Boeing 737 is a tool for the implementation of Mark Zuckerberg’s visionary venture to spread the Internet in the most inaccessible areas of the globe (Google is also working on a similar technology, the implementation is scheduled for 2017). Such giants as UPS and DHL do not leave any hope for the introduction of drones in the supply chains. In 2016, a German corporation, for example, successfully conducted an experiment to deliver parcels to the highlands of the Alps. Also, industry scaling is important for chip manufacturers - NVIDIA, Intel, Qualcomm and Ambarella. For them, drones are a new growth driver amid stagnating sales of mobile devices and decaying personal computers.

    Great prospects for drones in agriculture. According to the forecast of the analytical company Juniper Research, already in 2016, 48% of all commercial sales of drones in the B2B segment (their volume is estimated at $ 481 million) will fall on farmers. A drone for high-tech monitoring of farmland for less than $ 1 thousand, for example, is produced by DJI's main US competitor, 3D Robotics. The business potential of drones is also in demand in retail, construction, and video content production - it is difficult to find an  Industries Of The Future that would not use UAV functions.

    According to the results of 2015, PwC analysts estimated the entire capacity of the global market for “solutions using drones for commercial purposes” at $ 2 billion. But by 2020, according to their calculations, the amount would soar to $ 127 billion. The consulting company compared the economic effect for business from the use of drones with the proliferation of personal computers in the 1980s, which also turned many industries around.
    And this study does not yet take into account the segment of the drone market used by the military and police. According to the analyst company Intense Research, the market of “combat” drones will grow to $ 21 billion by 2021 from $ 3 billion in 2014. The main beneficiaries of this boom will be Pentagon contractors who, in foreign military operations, are entrusting more and more authority to drones, such as Lockheed Martin.

    3D Industry


    3D Industry

    In 2012, The Economist magazine published an article programmatically titled The Third Industrial Revolution. In it, 3D printing was put on a par with breakthrough inventions such as a steam engine (the first industrial revolution) and conveyor production (the second industrial revolution). And already in 2015, at the World Economic Forum, decentralized production (distributed manufacturing) was named one of the most important technological trends of the time.

    “Under the traditional system, raw materials are brought and assembled at large factories, the same products are obtained from them, which are then sold to the consumer. In decentralized production, raw materials and templates for production are located in different places, and the final product is released very close to the end user, ”wrote IBM Vice President Bernard Meyerson specifically for the forum site. He cites the American furniture company AtFAB, which sells digital versions of designer furniture manufacturing instructions, as an example of the new economy. Everyone can download them and then print using a 3D printer.

    The foundation for radical changes has been prepared for decades. The current 3D printer market leaders were founded back in the 1980s. In 1986, Chuck Hall, the inventor of laser stereolithography, founded 3D Systems. In 1989, Scott Crump, the author of the stratification process, registered Stratasys. In the same year, EOS appeared in Germany, which subsequently offered the world direct metal laser sintering technology - “direct sintering of metal with a laser." The 1990s and 2000s went to experiment with technology, reducing the cost of installation costs. Gradually, the special term additive manufacturing (AM; “layer production”) came into use. It is customary to use it in order to distinguish the Industries Of The Future use of 3D printing from educational or entertainment.

    A revolutionary breakthrough occurred in the first half of the 2010s. If in 2010 Stratasys revenue amounted to $ 118 million, then in 2015 it was almost $ 700 million, 3D Systems coming in second place finished 2010 with $ 159.9 million, and 2015 - from $ 666 million. “Initially 3D printing was perceived as one of the ways to create a prototype ... However, the technology went beyond prototyping. It turned out that with its help it is possible to make final products, ”explain the success of the Boston Consulting Group.

    According to the American Wohlers Associates, by 2011 additive technologies became the main for several industries, in particular for manufacturers of hearing aids. Actively began to use AM suppliers of dentures, crowns and other dental products.

    Five years later, at the end of 2015, 3D technologies were implemented in 71% of industrial enterprises in the United States, according to PricewaterhouseCoopers. Of these, only 17.4% have not yet determined their attitude to 3D printing (experimenting to determine). At the same time, back in 2014, the share of those fluctuating was significantly larger - 28.9%.

    Among large companies that are already actively using additive technologies, one can find General Electric (jet engines, medical devices, household appliances), Lockheed Martin, Airbus and Boeing (aircraft structural elements), Aurora Flight Sciences (unmanned aerial vehicles), Siemens ( spare parts for gas turbines). Back in 2014, only 0.9% of US manufacturers used 3D printers to produce final products. In 2015, there were already 6.6% of such, according to PwC. At the same time, the number of those who need technology both for prototypes and for goods delivered to the market increased from 9.6 to 13.2%.

    An important sign of the addition of additive technologies to real production is the growing demand for metal 3D printing equipment. INDTechEx analysts call this trend the fastest growing and predict that by 2025 the market capacity will reach $ 3.9 billion. In 2014, total sales growth was 48%, but now it has slowed down. In the second quarter of 2016, sales of 3D printers working with metal increased by 12% compared to the same period in 2015, the British Context indicates. In quantitative terms, this segment accounted for 9% of all sales in the market of industrial 3D-printers, in money terms - 35%.

    Between 2016 and 2022, the additive technology market will grow by 29.2% per year, according to Markets & Markets. The revolutionary tread of 3D printing can lead to a global economic breakdown - the return of world industrial giants to their homeland from China and other countries, where in previous years it was more profitable to place real production.

    Artificial Intelligence

     Artificial Intelligence (AI)
    The prospects for artificial intelligence (AI) have never been discussed so vividly as in 2016. Google’s AI now provides answers to search queries: through text compression algorithms, it determines the relevant information on a specific page and displays it to the user. A neural translation machine from a company that programmers taught to translate from English to Japanese and vice versa, and from English to Korean and vice versa, eventually learned how to translate from Japanese to Korean and vice versa, developing its own internal language, interlingua, not accessible to humans.

    Also, Google AI algorithms developed with the support of researchers from Oxford University are 35% better than a professional linguist who can read lips: by feeding AI 5 thousand hours of video, the authors of the experiment later chose 200 random fragments on which a person could “read” 12% of the words, and "machine" - 47%. Finally, the search giant launched an experiment for ordinary users - the game Quick, Draw! In 20 seconds, a person must draw a given object on the screen, and AI, relying on the accumulated database, must guess what his “living” opponent represents.

    Microsoft’s experiments were no less exciting: in May, the corporation launched on Twitter a self-learning bot using AI algorithms called May, who immediately learned “tricks” from troll users and after a day of talking with the audience began to admit sympathy for Adolf Hitler and release sexist comments . And the text recognition algorithm Deep Text from Facebook in an experimental format is trying to guess the wishes of the audience, based on content posted on the social network. For example, the AI ​​through the messenger will prompt the user to call a taxi, if that “text” informs about the intention to move to a certain place.

    AI technology, according to Mark Koch, an analyst with Frost & Sullivan consulting firm, is rapidly “democratizing.” Science fiction turns into a business: according to the forecast of Bank of America Merrill Lynch, by 2020, the market for AI-based services will grow to $ 153 billion, of which $ 83 billion will come from robotics solutions, including drones and unmanned vehicles, and $ 70 billion to the big data analytics segment.

    A key subsection of AI, the driver of emerging market growth, is machine learning. Algorithms of artificial neural networks, which "comprehend" data on the principle of the human brain, are increasingly becoming the basis for end-user oriented products. For example, hundreds of thousands or millions of images pass through neural networks in order to be able to accurately guess the appearance of a particular person or process photos in the style of a particular artist. In February, Russian startup N-Tech.Lab released the world's first mobile dating application FindFace, which identifies a person with an accuracy of more than 70% if they have an account on the VKontakte social network. And in the summer, the Russian market captured the Prisma photo-processing application, which also relies on the neural network algorithm (for today, according to TechCrunch,

    A little earlier, the first product - the OpenAI Gym platform - was introduced by Tesla founder EIlon Mask and Y Combinator president Sam Altman OpenAI. Businessmen have promised to invest at least $ 1 billion in the development of an open, accessible and friendly AI without the risk of inventing a competitor hostile to humanity. Gym - software for the development of “reinforcement learning” algorithms, in which the learning object develops by interacting independently with the external environment. Systems built on the platform from OpenAI can, for example, learn desktop and video games or control robots.

    The new market requires new skills from specialists: AI developers, unlike traditional programmers, do not just write code, but manage programs that independently process data, removing part of the work from a person. The “personnel” issue threatens not only programmers: AI technologies are the Industries Of The Future that will destroy many professions, from factory workers to Wall Street brokers: in the next two decades, Bank of England predicts 48% of all jobs replaced by robotics and software, and ArkInvest analysts predict a loss of 76 million workers places only in the USA (for comparison, this is almost 10 times more than was created during the presidency of Barack Obama).

    So far, developers, despite the successes in the development of machine learning algorithms, can boast of progress only in what is defined by researchers as a “narrow” (Narrow) AI, noted in an October study by the US National Council on Science and Technology (NSTC). Machine learning allows the technology itself to recognize speech or an image, play strategies, drive a car along a highway, plan trips, recommend advertisements and solve other applied problems. General AI, as opposed to narrow, remains the technology of the future. It will be an imitation of “developed”, integrated human thinking, experts say NSTC.

    Augmented Reality


    Augmented Reality
    People started talking about augmented and virtual reality (AR and VR) a long time ago: the first developments appeared in the USA in the 1960s. So, the scientist Morton Heilig in 1962 patented the Sensorama system - an outwardly resembling a gaming machine that showed a 3D image. And one of the first helmets of virtual reality was created by the American developer Ivan Sutherland in 1968. But these projects were more like scientific experiments.

    The first boom in virtual reality happened in the 1990s with the massive release of 3D video games and movies, Goldman Sachs analysts wrote. Then the VR revolution did not happen due to insufficiently developed technologies. The start of a new boom, according to Goldman Sachs, marked the purchase by Facebook of the social network Facebook in 2014 for $ 2 billion startup Oculus, who developed a virtual reality helmet.

    Unlike the 1990s, computers are now able to depict the virtual world realistically, and displays and sensors have become better and cheaper, although the VR and AR market is just beginning to take shape. According to the forecast of the analytical company IDC, in five years it will grow 30 times - from $ 5.2 billion in 2016 to more than $ 162 billion in 2020.

    First of all, the development of augmented reality technologies is facilitated by the massive spread of smartphones and mobile Internet. A typical example is the success of the game Pokémon Go, which a few hours after the release in July 2016 topped the ratings of applications in iOS and Android and in a week raised the capitalization of the owner-company Nintendo by 70%. And just four years ago, the same developer, Niantic, already released an augmented reality game - Ingress, but the revenue from it for three years, according to SuperData and SensorTower estimates, turned out to be less than the income from Pokémon Go per day ($ 1.1 million against $ 1.4 million).

    The proliferation of productive smartphones has spurred the advent of low-cost virtual reality helmets, IDC analyst Chris Chute, whose words were quoted in a company announcement in August 2016, explained. Such a cheap device was released, for example, by Google in 2014. The virtual reality helmet from Google is a small cardboard box with two lenses costing from $ 7 to $ 15, on which the smartphone is mounted. Lenses allow the user to see a three-dimensional image, launching appropriate applications, such as games, on the device.

    More advanced virtual reality helmets have been released by many major electronics manufacturers: Microsoft, Samsung, HTC, Samsung, LG, Sony. According to the results of 2016, Samsung will be the leader in sales of VR helmets, according to the SuperData forecast: the company will supply 3.5 million Samsung Gear VR devices. Another 2.6 million PlayStation VR helmets will be sold by Sony, 0.7 million by Oculus Rift and 0.4 million by HTC Vive. Prices for devices are reduced, helmets are becoming more affordable for consumers. Goldman Sachs draws an analogy with how gadgets became cheaper in the past: for example, the cost of a laptop for 20 years, from 1994 to 2014, fell by an average of 6.5% per year, the price of a smartphone dropped by an average of 5% over ten years annually.

    In the first two months of 2016, investments in VR and AR technologies exceeded the annual mark of $ 1 billion, DigiCapital analysts found out (for comparison: for the whole of 2015, total investments in the market amounted to $ 700 million). The lion's share of this amount came from one investment: in February, one of the most secret startups, Magic Leap, attracted almost $ 800 million from a group of investors, including Alibaba, Google, Warner Bros, JP Morgan and Morgan Stanley. Little is known about Magic Leap: as Wired magazine wrote, the company is working on glasses of the so-called mixed reality (MR), which show the user virtual objects, but remain transparent, so that he sees the world around him. After the last round of investments, the valuation of a company that has not yet presented its product amounted to $ 4.5 billion, which is three times more than all the funds it raised.

    Wearable devices are only part of the nascent market. By 2025, 56% of the augmented and virtual reality market revenues will come from equipment sales, and 44% will come from software, Goldman Sachs analysts say (according to the baseline scenario of their forecast, the market will total $ 80 billion). And how people will use new gadgets depends on what kind of applications developers will create for them, according to IDC.

    If only 25 years ago you had to learn how to manage a computer, now users of smartphones and tablets just pick them up and start working. Virtual and augmented reality technologies will again change the way we interact with a computer and make it even more intuitive, Goldman Sachs experts write. To give commands, we will use gestures and graphics, and the image will not be limited by the size of the display.

    New Medicine


    New Medicine
    In early June 2016, Forbes magazine “nullified” the status of the youngest woman in the list of billionaires - the founder of the biotechnological startup THERANOS Elizabeth Holmes. The company, which investors valued at $ 9 billion, had previously been convicted of fraud: the allegedly innovative Theranos blood test technology was ineffective compared to traditional analysis methods. The damage was inflicted on the reputation not only of a single startup, but of the entire market, blowing bubbles around revolutionary (Industries Of The Future) Ideas that did not prove their worth in practice.

    Companies that develop innovative technology solutions for medicine can learn a lesson from Theranos failure. “A business cannot reach such proportions without a proper level of disclosure and verification of diagnostic results,” Munish Tevari, a professor at the University of Michigan, said in an interview with Wired. The “take a step backward, then take two forward” strategy sometimes works. For example, the company of Sergey Brin's ex-wife Ann Wojitski 23andMe, which the US Food and Drug Administration (FDA) forbade conducting genetic tests for individuals in 2013, changed the business model, switching to clinical studies of the accumulated results. As a result, in 2015, the startup attracted new investments in the amount of $ 115 million,

    The market is constantly in search of breakthrough projects. In May 2016, an experiment with the participation of 21 hospitals began in New York: doctors, when receiving patients according to the results of the survey, fill out a form in a diagnostic program based on the analysis of large data arrays. According to the results, the "machine" estimates the likelihood of a disease. The list of diagnoses from artificial intelligence is still small, but he is already able to determine the risk of pneumonia with a high degree of probability. According to the developers of the program, their solution will help to save on tests and medicines, for example, up to 25% on the use of antibiotics.

    Google teaches its algorithms for diagnosing diabetes, which affects more than 420 million people around the world: the neural network recognizes signs of the disease by photographs of the retina, comparing the image with a database of almost 130 thousand photos. The first clinical results of the effectiveness tests were not inferior to the examinations of high-class ophthalmologists who participated in the project. The role of research using machine learning will inevitably grow: according to the calculations of analyst Peter Hinssen, in 2011 alone, the total amount of data accumulated in healthcare amounted to 150 exabytes and has since grown by 1.2–2.4 exabytes per year (1 exabyte - the amount of data that will fit on 250 million DVDs).

    Advanced research allows researchers to conduct and robotics. For example, in June, the FDA approved the diagnosis of a new ARES medical robot from the classified startup Auris Surgical, created by Frederick Mall, the founder of the manufacturer of the most famous da Vinci robot surgeon on the market - Intuitive Surgical (more than 3 thousand da Vinci - each costing about $ 2 million - since 2012, they have performed more than 200 thousand operations worldwide under the control of surgeons-operators). ARES, according to IEEE Spectrum sources, in the future will carry out operations without the help of a person on the throat, lungs and stomach. Auris in 2015 raised $ 150 million from leading Silicon Valley venture capital investors, including Peter Thiel.

    Another example of a medical robot is Hero from a Texas-based startup of the same name. The machine, similar to a coffee machine, helps patients clearly adhere to the schedule of taking medications: the Hero program records data on the frequency and length of the period of administration, as well as loading containers with tablets or pills. Hero does the rest himself: exactly at the appointed time, he “wakes up” and gives out the necessary dose of medicines. The mission of the startup is to reduce the number of mistakes when taking the medicine: only in the USA, according to the statistics of the National Institute of Narcology, 4.6 million people suffer from the consequences of the wrong dosage or violation of the deadline for taking medications per year. Hero entered the market in the summer of 2016 at a price of $ 399 apiece, its creators hope that the robot will be useful to both clinics and private users.

    The most promising and non-commercial-oriented robots in Industries Of The Future are produced in the bowels of university research laboratories. In November 2016, Harvard scientists, for example, published an article in the journal Cell Systems describing a robot smoker. It is an artificial bronchus with living human cells. The robot reinforced scientific statistics on the negative effects of smoking in the form of an increased risk of developing chronic lung disease.

    Smart Homes


    Smart Homes
    In 2018, The New York Times wrote about sensors that respond to sound and movement, or cameras that monitor the condition of older residents, as developments that have a chance to fill smart homes. Already in the mid-2000s, these projects became a reality: electronics manufacturers began to offer the first products to the market. Siemens in 2006 introduced the Gigaset Home Control - a home control system via a cordless telephone. With it, you can, for example, remotely control lighting and heating, turn the stove on and off, receive SMS messages about the end of the wash, or answer the doorbell on your mobile phone.

    A more advanced system that Siemens came up with at the same time is Smart Home Solutions by SURPASS. It allowed you to connect devices to a single control point via a local network. The user could customize the scenarios of the system. For example, when the video player is turned on, the blinds were automatically closed in the room, and telephone calls were transferred to the answering machine. The German holding compared the introduction of smart home technologies with the mass distribution of refrigerators, electric stoves and television in the 1950s, but still called it the business of the future.

    But ten years ago, for the widespread adoption of new technologies of “smart” home, the Internet was too poorly developed: the low connection speed did not allow equipping the house with devices that communicate with each other. Now the technology of “smart” home is associated with the development of the Internet of Things (Internet of Things; IoT), which connects devices to each other and allows them to exchange data. The number of consumer “things” connected to the Internet in 2016 should increase by a third, to 4 billion, and by 2020 will reach 13.5 billion, according to a forecast by the consulting company Gartner.

    The development of the Internet of things can ultimately lead to the fact that almost all devices will somehow be connected to the network, according to a study by Deloitte. Experts cite TVs as an example: three years ago devices with access to the Network were rare, but now it’s hard to imagine a TV without the ability to connect to the Internet (Smart TV). In many ways, the development of streaming services such as Netflix contributed to this.

    Many large IT companies began to develop for the "home assistant". Apple in 2014 introduced the HomeKit system for device manufacturers, which allows you to control technology through gadgets on the iOS operating system. HomeKit supports some types of Philips lamps, August and Schlage smart door locks, Honeywell and Hunter thermostats, and Eglato Eve wireless sensors.

    Google took up the technology of the “smart” home with the purchase of the manufacturer of Nest connected thermostats in the Network in 2014 for $ 3.2 billion. And a few months later, Nest acquired Dropcam, a company producing home surveillance cameras that broadcast video onto a smartphone or laptop via Wi- Fi Based on Nest technologies, the corporation created a platform for developers and invited manufacturers of any devices to integrate the system into their products so that users could connect to their smart home control system.

    Amazon created the Alexa home-based voice control system and introduced it in 2014 as well. According to the idea of ​​the developers, the Echo device, specially designed for voice recognition, resembling a router, should carry out user commands - for example, turn on the light, turn on the washing machine, call a taxi or find information on the Internet. Now Echo costs $ 179 and can include music, read audio books and news aloud, control lighting and thermostats, if the corresponding devices are compatible with the Alexa system.

    According to CB Insights, 2014 was a record year for world investments in smart home technology: it amounted to $ 585 million. In August, the research company counted startups involved in smart home technologies in Industries Of The Future and received investments: 67 companies were included in the list, the majority of which one way or another engaged in protective systems. Among them, for example, is the manufacturer of “smart” calls Ring, in which Dmitry Grishin also invested. The idea of ​​a device costing $ 200–250 is simple: it tells the landlord about a doorbell through a smartphone application, a user can see a guest using a video camera, open a door for him or see who came to him for a certain period.

    According to Markets & Markets estimates, the market for technologies and devices for smart homes will grow to $ 122 billion by 2022 from $ 47 billion in 2015. However, while the market is fragmented, the problem of data protection and privacy has not been resolved, says GfK. In addition, the cost of solutions is still high, which, according to a GfK survey, is the main obstacle for potential consumers.
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