The topic of Artificial Intelligence (AI) dominated the media news feed throughout the year. The tone is set by the main newsmakers - Elon Musk and Mark Zuckerberg, discussing the dangers and benefits of using Artificial Intelligence in human life. Russia and China have declared the development of AI as a priority direction in the digital economy. 2018 will be a year of development and further study of the possibilities of using AI, especially the method of deep learning, as the most promising branch of Artificial Intelligence. I’ll tell you more about this trend in the field of high technology using the example of the use of AI in marketing.
The essence of Artificial Intelligence is to create machines so smart that they will surpass the thinking and analytical abilities of humans. Machine learning, a basic AI method, has such capabilities and is already widely used in many sectors of the economy and areas of human life. However, other, more advanced technologies are rapidly developing.
This is especially noticeable in the pace of development of deep learning, which almost completely replicates the principle of operation of the human brain in data processing and decision-making modeling. In 2017, deep learning became an integral part of technology processes in healthcare and automotive manufacturing. Marketing, as the most dynamic component of every business, has also not remained aloof from the use of advanced technologies. Deep learning has had a revolutionary impact on the entire advertising industry.
The technology used in the deep learning method is based on the principles of interaction of biological neurons. With the help of self-learning algorithms, marketers now obtain descriptions of a customer's buying potential without human assistance. For example, RTB House recently analyzed a huge amount of data, clearly demonstrating that using Artificial Intelligence instead of recommendations from experienced marketers in retargeting campaigns can improve conversion results by 35%. And that is not all. Using the deep learning method, advertisers receive a forecast of user actions based on an analysis of his behavioral characteristics and desires. This greatly simplifies the work of a marketer by offering the best options for targeted advertising messages containing products that the user did not even know about or had not yet seen.
Many major brands have already seen the benefits of implementing deep learning solutions into their products or marketing tools. In 2018, we expect widespread use of deep learning and increased investment in developing its potential.
From “supervised learning” to new horizons
In 2017, there was a move away from the so-called “supervised learning” typical of the machine learning process towards a more complex system of “transfer learning”. This technology is based on transmitting human instructions to a computer: analyze existing decision-making models, examples, data sets and their subsequent analysis.
The way transfer learning works is the ability of a computer to process data from simulations rather than from reality. This process is much simpler and cheaper, as well as faster, which is very important when analyzing huge amounts of data. Using this method, the machine learns to make decisions on its own: with logical conclusions, analogy or deductive method.
For example, using an older machine learning model, a self-driving car could take a person millions of miles while data is being recorded. This data is transmitted to the car, which understands how to drive the car based on the driver's decisions. Thanks to “learning transfer,” there is no longer any need for a real driver. Instead, data can be taken from various driving simulations. By simulating millions of hours of driving, the car itself understands where it needs to go, and it already translates the knowledge into the real world.
The second approach is called “reinforced learning.” Its goal is to train a computer to make the best decisions based on feedback from the environment and the actions taking place in it. For example, how this happens when participating in bidding for the purchase of advertising space. Auction systems are very complex. Even experts often have problems determining the optimal rate that will allow them to achieve the desired results at minimal cost. The car will encounter the same obstacles at the beginning of its movement. However, unlike a person, a car can operate 24 hours a day in a simulation environment. And it can also learn a set of actions, much faster than a human. Returning to our example of buying advertising space, the computer learns from simulating auctions, receiving data on how to act most efficiently and thus win the auction.
New jobs and new challenges
Indeed, the operating principle of deep learning algorithms is absolutely identical to the functioning of the human brain. But, unlike people, computers learn much faster and can analyze enormous amounts of data. Computers don't fall asleep and make a lot of mistakes. This is where super performance comes into play. In a very simple way, AI will strive to surpass human abilities in many areas. Currently, self-learning algorithms are able to recognize actions and images much more accurately than humans.
Does this mean that there is a danger of people being completely replaced by robots? Not really. According to the World Economic Forum, 65% of children entering primary school today will be given jobs that do not currently exist. The current level of AI development allows companies to look for more IT specialists, data analysts, and programmers. Next year we'll likely see a boom in new job offers for data scientists. Although now such a proposal is not yet popular.
Innovations of 2017 will receive a powerful impetus for development in 2018
The goals pursued by the implementation of the deep learning method are to simplify our lives and increase the efficiency of human activity. This is why the use of AI is no longer a standard, but a necessity for companies that want to be competitive in the global market. This is not about the ability to personalize or improve the capabilities of the final product, but also about a number of other indirect activities such as data collection and analysis. Already, companies have such a large amount of data to analyze that they cannot cope with its processing.
This situation directly affects the decisions made by their employees and therefore their financial results. Companies whose business specializes in collecting and analyzing data for various enterprises will be increasingly in demand. Businesses with larger budgets will use AI to classify: what to offer to customers, what terms to recommend to suppliers, how to instruct employees, what to say and do in real time. It should also be assumed that many new startups will soon emerge offering solutions based on self-learning algorithms as this technology becomes widespread.
In 2017, artificial intelligence became part of our daily lives and public discussions. In the coming years, the focus will be on developing various AI-based technologies that will replace humans in many complex industries, ultimately making our lives much easier. But this will require a lot of work.
Ericsson has named the 10 most popular consumer trends for next year
Artificial intelligence and virtual reality: 10 consumer trends for 2017. Photo: elearningindustry.com
Ericsson has presented its forecast for the most popular consumer trends of the next year. The top trend of 2017 will be artificial intelligence, which is gradually penetrating our everyday lives.
So, Ericsson called the most popular consumer trends for 2017:
More and more people want artificial intelligence to penetrate their lives. 35% of Internet users would like to see artificial intelligence as their work assistant, and 25% as their manager. However, 50% of respondents consider artificial intelligence dangerous. In particular, this technology may cause many people to lose their jobs, because their functions can easily be performed by robots.
Applications are actively used to simplify and automate certain aspects of life. At the same time, the development of the Internet of Things is accelerating. 40% of respondents are confident that the time will come when smartphones will be able to learn the habits and perform a number of functions of their owners.
And again about the loss of jobs - soon artificial intelligence will replace drivers too. 25% of respondents support the idea of replacing drivers with autopilots, because they believe that this will be much safer for pedestrians. 65% of respondents would like to buy a car with autopilot.
80% of respondents are convinced that in just three years virtual reality will reach such a level of development that it will be impossible to distinguish it from the physical world.
Respondents predict that the development of new technologies will have a negative impact on people's health. In particular, the use of virtual and augmented reality applications will cause motion sickness, for which 33% of respondents are willing to take corresponding pills.
Despite the fact that most people try to protect themselves as much as possible, 60% of respondents admit that using smartphones carries risks.
More than 50% of respondents would like to have augmented reality glasses. Among the possible options for their use: highlighting dark areas, warning about danger, the ability to change or eliminate environmental elements that irritate.
More than 30% of respondents are convinced that there is no such thing as privacy on the Internet anymore, so 50% of study participants are satisfied with a “reasonably good” level of privacy.
According to experts, in just five years all Internet users will be provided with all products and services from the five largest IT companies.
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Previously we wrote about the fact that.
Kai Fu Lee, chairman of SinovationVentures, believes that AI is "aimed at large-scale job losses" while concentrating wealth in the hands of companies that develop or adopt AI. Others believe that similar fears were present with the advent of all world-changing technologies, right back to the printing press in the 15th century.
The Economist reassures readers that "AI is creating demand for jobs" and a growing number of people around the world are "providing digital services online." Which companies and countries will thrive in the era of AI? Which segments will disappear, change, or be created? How will the nature of work change?
Warfare
Proponents of armed drones argue that such weapons can hit targets with much higher accuracy than humans; and the larger the role they play in the theater of operations, the less often technicians will use them to harm.
But what if such weapons become independent and work independently, without human intervention? Will removing people from the military personnel list lead to an even more severe and unstoppable arms race?
An open letter published during the 2015 International Joint Conference on Artificial Intelligence warned that autonomous weapons "require no expensive or hard-to-find raw materials and will therefore become ubiquitous and cheap for all significant militaries to mass produce." Will an era with automated weapons be more peaceful or more militant?
RAND researchers are calling for an analytical framework and international effort focused on the use of long-range armed drones in counterterrorism and targeted assassinations.
Making decisions
Politicians are constantly faced with a huge number of choices and motivations - many more in the days of social media than twenty years ago. Such information overload makes it difficult to cope during a crisis, let alone multiple crises.
Recently, a proposal arose to pass “all decisions that the president makes through a computer - not to make the final choice, but to help the leader in the person of a person.”
But while AI is now largely blameless, the RAND study highlights the risks of algorithmic biases in filtering news, influencing criminal justice, and even the delivery of Social Security benefits and visas. What decisions should be entrusted to AI? What should remain in the hands of man? In the hands of a team of people?
Creation
The world has become accustomed to AI that can perform breathtaking feats of computation and beat humans at popular board games (it's been just over 20 years since the IBMDeepBlue supercomputer famously defeated chess grandmaster Garry Kasparov). How will it further progress in people's creative space?
Artificial intelligence researcher Jesse Engel believes it will “transform the creative process...by augmenting it with smart tools that provide new possibilities for expression.” Others are not so optimistic. Journalist Adrienne Lafrance notes that AI can already “flirt,” “write novels,” and “fake famous paintings with amazing accuracy.” What does it mean to be creative? Moreover, what does it mean to be human?
Discussions of AI often veer to extremes, be it the promise of a utopia free of human suffering or the danger of a dystopia where robots enslave their human creators. More balanced and rigorous analysis is needed to help shape policies to mitigate risks and maximize benefits. Certain steps need to be taken to overcome fears that AI will overwhelm the state and society.
How can AI impact a country's national interests? What types of AI, if any, can be considered strategic technologies based on government criteria? Where should market forces play a role, and where should politics play? While AI remains largely the stuff of science fiction, these questions are becoming more and more important.
Making forecasts is a thankless task, especially since progress in the field of modern machine learning methods has outstripped our wildest expectations in recent years. But I would venture to name some areas in the field of training deep neural networks in which significant advances can be expected in the near future.
Firstly, this is the development of the ideas of neural network reinforcement learning, which will allow the development of new self-learning algorithms for agents interacting with the environment. These can be both robots and programs operating in virtual space, for example, playing intellectual games like Go (already done) or Starcraft (in progress). The main goal here, of course, will be to create an algorithm that can adapt “on the fly” to a new complex game or environment.
Secondly, it is the development of new methods of learning on the fly and meta-learning. The first allows a computer to grasp new concepts and meanings from a few examples, just as a human does, and unlike modern neural networks, which learn a new concept after being exposed to thousands or tens of thousands of examples.
The second allows the neural network to select the parameters of its learning method itself. Now the quality and speed of training of neural networks significantly depends on the setting of a number of parameters (usually called hyper-parameters to distinguish them from the network weights, which, in fact, are adjusted during training), as well as on the architecture of the network itself. Currently they are determined by humans or semi-automated procedures that are far from optimal. Because of this, neural networks learn longer and worse than they could.
Work that appeared in 2016 shows that this work can, in principle, be entrusted to an auxiliary neural network. As we all remember from high school, the end of the Industrial Revolution is when “machines start making machines.” Perhaps in the future, an equally important milestone will be the moment when neural networks begin to train neural networks, and there is reason to believe that this will happen as early as 2017.
Thirdly, neural networks will learn to speak with a person (both in the sense of generating replica texts and in the sense of synthesizing speech indistinguishable from human speech), generating photorealistic pictures and video sequences based on text descriptions, and writing large, meaningful texts. This will become our near future thanks to the rapid progress in the field of so-called. generative deep learning models. Of course, this will lead to the creation of new businesses, the emergence of new types of goods and services, as well as an increase in labor productivity in traditional sectors of the economy, such as mobile operators or banks, which will be able to abandon expensive and ineffective call centers.
Solving all these problems will be an important step towards the Holy Grail of machine learning - the creation of artificial intelligence. AI will certainly not appear next year, but in 5-10 years it will undoubtedly be developed. Moreover, the already existing elements of artificial intelligence will help scientists create full-fledged AI and, thereby, will speed up work in this direction. The creation of AI will be the most important achievement of humanity and will provide it with a powerful civilizational leap forward.
It is important to note that rapid progress in the field of AI has become possible largely due to the fact that these developments are being carried out openly and any person with the minimum necessary training (for example, a graduate of the Faculty of Computer Science at the National Research University Higher School of Economics) can take part in them: even large IT - corporations - leaders in the field of deep learning there are no secrets (except for short-term commercial ones), software implementations of most methods are available, as well as a mathematical description of the algorithms, which turn out to be surprisingly not so complex, taking into account the global nature of the problems solved with their help. This sets machine learning apart from, say, the space or nuclear programs of the mid-20th century.
Additional materials
Lecture by Dmitry Vetrov on machine learning (in order to understand what it is)
Artificial intelligence (AI, English: Artificial intelligence, AI) - the science and technology of creating intelligent machines, especially intelligent computer programs. AI is related to the similar task of using computers to understand human intelligence, but is not necessarily limited to biologically plausible methods.
What is artificial intelligence
Intelligence(from Lat. intellectus - sensation, perception, understanding, understanding, concept, reason), or mind - a quality of the psyche consisting of the ability to adapt to new situations, the ability to learn and remember based on experience, understand and apply abstract concepts and use one’s knowledge for environmental management. Intelligence is the general ability to cognition and solve difficulties, which unites all human cognitive abilities: sensation, perception, memory, representation, thinking, imagination.
In the early 1980s. Computational scientists Barr and Fajgenbaum proposed the following definition of artificial intelligence (AI):
Later, a number of algorithms and software systems began to be classified as AI, the distinctive property of which is that they can solve some problems in the same way as a person thinking about their solution would do.
The main properties of AI are understanding language, learning and the ability to think and, importantly, act.
AI is a complex of related technologies and processes that are developing qualitatively and rapidly, for example:
- natural language text processing
- expert systems
- virtual agents (chatbots and virtual assistants)
- recommendation systems.
National strategy for the development of artificial intelligence
- Main article: National strategy for the development of artificial intelligence
AI Research
- Main article: Artificial Intelligence Research
Standardization in AI
2019: ISO/IEC experts supported the proposal to develop a standard in Russian
On April 16, 2019 it became known that the ISO/IEC subcommittee on standardization in the field of artificial intelligence supported the proposal of the Technical Committee “Cyber-physical systems”, created on the basis of RVC, to develop the “Artificial intelligence” standard. Concepts and terminology" in Russian in addition to the basic English version.
Terminological standard “Artificial intelligence. Concepts and terminology" is fundamental to the entire family of international regulatory and technical documents in the field of artificial intelligence. In addition to terms and definitions, this document contains conceptual approaches and principles for constructing systems with elements, a description of the relationship between AI and other end-to-end technologies, as well as basic principles and framework approaches to the regulatory and technical regulation of artificial intelligence.
Following the meeting of the relevant ISO/IEC subcommittee in Dublin, ISO/IEC experts supported the proposal of the delegation from Russia to simultaneously develop a terminological standard in the field of AI not only in English, but also in Russian. The document is expected to be approved in early 2021.
| The development of products and services based on artificial intelligence requires an unambiguous interpretation of the concepts used by all market participants. The terminology standard will unify the “language” in which developers, customers and the professional community communicate, classify such properties of AI-based products as “security”, “reproducibility”, “reliability” and “confidentiality”. A unified terminology will also become an important factor for the development of artificial intelligence technologies within the framework of the National Technology Initiative - AI algorithms are used by more than 80% of companies in the NTI perimeter. In addition, the ISO/IEC decision will strengthen the authority and expand the influence of Russian experts in the further development of international standards. |
During the meeting, ISO/IEC experts also supported the development of a draft international document Information Technology - Artificial Intelligence (AI) - Overview of Computational Approaches for AI Systems, in which Russia acts as a co-editor. The document provides an overview of the current state of artificial intelligence systems, describing the main characteristics of the systems, algorithms and approaches, as well as examples of specialized applications in the field of AI. The development of this draft document will be carried out by a specially created working group 5 “Computational approaches and computational characteristics of AI systems” within the subcommittee (SC 42 Working Group 5 “Computational approaches and computational characteristics of AI systems”).
| As part of their work at the international level, the Russian delegation managed to achieve a number of landmark decisions that will have a long-term effect on the development of artificial intelligence technologies in the country. The development of a Russian-language version of the standard, even from such an early phase, is a guarantee of synchronization with the international field, and the development of the ISO/IEC subcommittee and the initiation of international documents with Russian co-editing is the foundation for further promoting the interests of Russian developers abroad,” he commented. |
Artificial intelligence technologies are in wide demand in a variety of sectors of the digital economy. Among the main factors hindering their full-scale practical use is the underdevelopment of the regulatory framework. At the same time, it is the well-developed regulatory and technical framework that ensures the specified quality of technology application and the corresponding economic effect.
In the area of artificial intelligence, TC Cyber-Physical Systems, based on RVC, is developing a number of national standards, the approval of which is planned for the end of 2019 - beginning of 2020. In addition, work is underway together with market players to formulate a National Standardization Plan (NSP) for 2020 and beyond. TC "Cyber-physical systems" is open to proposals for the development of documents from interested organizations.
2018: Development of standards in the field of quantum communications, AI and smart city
On December 6, 2018, the Technical Committee “Cyber-Physical Systems” based on RVC together with the Regional Engineering Center “SafeNet” began developing a set of standards for the markets of the National Technology Initiative (NTI) and the digital economy. By March 2019, it is planned to develop technical standardization documents in the field of quantum communications, and, RVC reported. Read more.
Impact of artificial intelligence
Risk to the development of human civilization
Impact on the economy and business
- The impact of artificial intelligence technologies on the economy and business
Impact on the labor market
Artificial Intelligence Bias
At the heart of everything that is the practice of AI (machine translation, speech recognition, natural language processing, computer vision, automated driving and much more) is deep learning. It is a subset of machine learning, characterized by the use of neural network models, which can be said to mimic the workings of the brain, so it would be a stretch to classify them as AI. Any neural network model is trained on large data sets, so it acquires some “skills,” but how it uses them remains unclear to its creators, which ultimately becomes one of the most important problems for many deep learning applications. The reason is that such a model works with images formally, without any understanding of what it does. Is such a system AI and can systems built on machine learning be trusted? The implications of the answer to the last question extend beyond the scientific laboratory. Therefore, media attention to the phenomenon called AI bias has noticeably intensified. It can be translated as “AI bias” or “AI bias”. Read more.
Artificial Intelligence Technology Market
AI market in Russia
Global AI market
Areas of application of AI
The areas of application of AI are quite wide and cover both familiar technologies and emerging new areas that are far from mass application, in other words, this is the entire range of solutions, from vacuum cleaners to space stations. You can divide all their diversity according to the criterion of key points of development.
AI is not a monolithic subject area. Moreover, some technological areas of AI appear as new sub-sectors of the economy and separate entities, while simultaneously serving most areas in the economy.
The development of the use of AI leads to the adaptation of technologies in classical sectors of the economy along the entire value chain and transforms them, leading to the algorithmization of almost all functionality, from logistics to company management.
Using AI for Defense and Military Affairs
Use in education
Using AI in business
AI in the fight against fraud
On July 11, 2019 it became known that in just two years artificial intelligence and machine learning will be used to combat fraud three times more often than in July 2019. Such data was obtained during a joint study by SAS and the Association of Certified Fraud Examiners (ACFE). As of July 2019, such anti-fraud tools are already used in 13% of organizations that took part in the survey, and another 25% said that they plan to implement them within the next year or two. Read more.
AI in the electric power industry
- At the design level: improved forecasting of generation and demand for energy resources, assessment of the reliability of power generating equipment, automation of increased generation when demand surges.
- At the production level: optimization of preventive maintenance of equipment, increasing generation efficiency, reducing losses, preventing theft of energy resources.
- At the promotion level: optimization of pricing depending on the time of day and dynamic billing.
- At the level of service provision: automatic selection of the most profitable supplier, detailed consumption statistics, automated customer service, optimization of energy consumption taking into account the customer’s habits and behavior.
AI in manufacturing
- At the design level: increasing the efficiency of new product development, automated supplier assessment and analysis of spare parts requirements.
- At the production level: improving the process of completing tasks, automating assembly lines, reducing the number of errors, reducing delivery times for raw materials.
- At the promotion level: forecasting the volume of support and maintenance services, pricing management.
- At the level of service provision: improving planning of vehicle fleet routes, demand for fleet resources, improving the quality of training of service engineers.
AI in banks
- Pattern recognition - used incl. to recognize customers in branches and convey specialized offers to them.
AI in transport
- The auto industry is on the verge of a revolution: 5 challenges of the era of unmanned driving
AI in logistics
AI in brewing
AI in the judiciary
Developments in the field of artificial intelligence will help radically change the judicial system, making it fairer and free from corruption schemes. This opinion was expressed in the summer of 2017 by Vladimir Krylov, Doctor of Technical Sciences, technical consultant at Artezio.
The scientist believes that existing solutions in the field of AI can be successfully applied in various spheres of the economy and public life. The expert points out that AI is successfully used in medicine, but in the future it can completely change the judicial system.
“Looking at news reports every day about developments in the field of AI, you are only amazed at the inexhaustible imagination and fruitfulness of researchers and developers in this field. Reports on scientific research are constantly interspersed with publications about new products bursting onto the market and reports of amazing results obtained through the use of AI in various fields. If we talk about expected events, accompanied by noticeable hype in the media, in which AI will again become the hero of the news, then I probably won’t risk making technological forecasts. I can assume that the next event will be the appearance somewhere of an extremely competent court in the form of artificial intelligence, fair and incorruptible. This will happen, apparently, in 2020-2025. And the processes that will take place in this court will lead to unexpected reflections and the desire of many people to transfer to AI most of the processes of managing human society.”
The scientist recognizes the use of artificial intelligence in the judicial system as a “logical step” to develop legislative equality and justice. Machine intelligence is not subject to corruption and emotions, can strictly adhere to the legislative framework and make decisions taking into account many factors, including data that characterize the parties to the dispute. By analogy with the medical field, robot judges can operate with big data from government service repositories. It can be assumed, that
Music
Painting
In 2015, the Google team tested neural networks to see if they could create images on their own. Then artificial intelligence was trained using a large number of different pictures. However, when the machine was “asked” to depict something on its own, it turned out that it interpreted the world around us in a somewhat strange way. For example, for the task of drawing dumbbells, the developers received an image in which the metal was connected by human hands. This probably happened due to the fact that during the training stage, the analyzed pictures with dumbbells contained hands, and the neural network interpreted this incorrectly.
On February 26, 2016, at a special auction in San Francisco, Google representatives raised about $98 thousand from psychedelic paintings created by artificial intelligence. These funds were donated to charity. One of the most successful pictures of the car is presented below.
A painting painted by Google's artificial intelligence.
