From machine learning to digital twins, a sea of possibilities with rising (and falling) technology trends New and evolving technologies are rapidly changing the way we work, offering creative opportunities for those developers who don't mind refocusing and learning something new. In this article, we look at 11 new technology trends that experts say could disrupt existing IT practices and create demand for future-oriented developers.
We are not talking about just the next mega-breakthrough (aka Next Big Thing). The source of future opportunities for developers lies in the fusion of several advanced technologies - artificial intelligence (AI), virtual reality (VR), augmented reality (AR), Internet of Things (IoT). Internet of Things, IoT) and cloud technologies... and, of course, in the security issues arising from this merger. If you'd like to expand your personal toolbox, we recommend taking a closer look at these popular technologies, as well as our tips on how to succeed with them.
Internet of Things Security
After tens of millions of connected devices were hacked in 2016, even outside observers are noticing that unprotected IoT devices (IoT = internet of things) lead to terrible security problems. In a recent report, analyst firm Gartner published recommendations for developers and expert teams. It suggests that these specialists should work with each other from the very beginning of the design process. In this case, you can eliminate threats as they arise. For example, by downloading security updates to IoT devices. Demand for Internet of Things security experts is high, especially those who understand the vulnerabilities of the hardware and software used by network-connected devices. “IoT attack vectors are almost identical to those for any distributed network, such as computers or cell phones. So security knowledge will be relevant and important in this area, says Richard Whitney, vice president of product at startup Particle. “Learn the basics of cryptography and authentication and you will achieve great things.” Tom Gonser, founder of DocuSign and partner at Seven Peaks Ventures, says firms now need low-level programming skills for microprocessors. “They also need experience with Bluetooth technology, [Windows Identity Foundation] and spread spectrum technologies. Knowledge of the latest security options of the Linux operating system, especially options optimized for the minikernel, such as Qubes OS, is also appreciated.” Matt Abrams, a partner at Seven Peaks Ventures, suggests focusing efforts on understanding technological processes and how to destroy them. In his opinion, the era of post-quantum cryptography is approaching faster than expected. “Specialists must understand what differential privacy and adversarial networks are.”
Artificial intelligence
Demand for AI-savvy engineers is growing by leaps and bounds in anticipation of a new wave of driverless cars, robots and smart electronics. “We are now at an inflection point, driven largely by advances in ubiquitous computing, affordable cloud services and virtually limitless information storage,” said Nicola Morini-Bianzino, senior executive director and artificial intelligence group leader at Accenture. “Artificial intelligence is now built into literally everything.” Morini-Bianchino predicts demand for software developers, technologists and researchers with experience in the fields of [automation - approx. transl.] translation from one language to another, speech recognition, computer vision, robotics, text processing in natural languages, knowledge representation and logical reasoning. The food for AI is data, so the need for data and content management specialists, data scientists and analysts is also extremely high. Treasure Data vice president of marketing Kiyoto Tamura predicts that artificial intelligence will soon move from niche, mundane applications to much broader—and exciting—applications. Previously, tasks for artificial intelligence looked something like this: “Find the optimal delivery route for a package... or the most suitable sites for a search query.” Now their wording is closer to the following: “play Go at a decent level”, “drive safely”, etc. “It's great, but people still have to tell the computer what to do, and there's nothing you can do about it,” says Tamura Kiyoto. Demand for data scientists, machine learning scientists, and computational linguists is constantly growing. says MindMeld CEO Tim Tuttle, citing a VentureScanner study that listed 910 artificial intelligence companies launched between March and October 2016, with more than half in deep learning/machine learning and data science. natural languages. “Not only is this area growing in numbers, but it's also the area where the most money has been invested, at about $4.5 billion,” says Tuttle. Despite the recent surge in interest in interactive applications, there is an asymmetry between supply and demand in this area. As a result, subject matter experts will remain a valuable resource until academia and industry redress the balance.
Machine learning
A type of artificial intelligence, machine learning, can process enormous amounts of data to quickly find patterns—such as facial recognition—and perform tasks such as recommending movies to stream, without the need for explicit programming. Patrick Spedding, senior director of business intelligence research at Rocket Software, believes that cognitive technologies, together with bots and machine learning, can improve the efficiency of organizations searching for the “useful signal among the noise.” “Machine learning, after all, is based on the capabilities of advanced analytics, formerly known as data mining, which needed only a suitable platform to become more popular,” comments Spadding. The question arises: how to gain Abrams of Seven Peaks Ventures recommends Andrew Ng's online course on machine learning on Coursera. Those who take the course perform better in Kaggle competitions. better results than some practitioners with years of experience. Not every machine learning developer has a computer science degree. “Of course, a computer science degree or a basic engineering degree usually helps technicians succeed in their work “, such specialists are able to carry out experiments over a long period of time and improve machine learning models,” says Mehdi Samadi, CTO and co-founder of Solvvy. “However, I have often seen companies hire candidates without a computer science background and turn them into machine learning specialists.”
Data Science
Data science is another trendy field that requires a variety of interdisciplinary skills, with each industry having its own. Experience with machine learning and artificial intelligence may be required to transform large volumes of data into useful data for business decisions. “Experienced data scientists are a scarce commodity,” says Spadding. “It seems to me that the areas where you can create technologies that help in decision making, such as cognitive bots and guided analytics, are areas of extremely profitable opportunities.” For those who wanted To work in these areas, a thorough knowledge of probability theory and mathematical statistics is a key requirement, says Gary Kazantsev, who heads the machine learning group at Bloomberg. “Engineering skills, such as the ability to write the code needed to create a system, are a plus.” However, with the advent of tools such as the machine learning library TensorFlow or Jupyter notebooks, this task is greatly simplified.To practice data science, good research skills are useful, that is, the ability to formulate hypotheses, test them, study modern literature and constantly monitor news in your area." Gunter Ollmann, chief security officer at Vectra, says many companies currently treat data scientists separately from designers, R&D teams and developers. As deep learning and machine learning tools improve and training courses become more effective at educating senior engineers about what's new in data science, the distinction between data science and software engineering will gradually disappear. In the future, a fusion of skill sets and proficiency with both instruments will be a must."
Transaction block chain
The benefits of this method of creating a distributed financial accounting tool for transactions include both transparency and security, although the lack of standardization has slowed its adoption across a wide range of industries. Peter Loop, assistant vice president and principal technology architect at Infosys, is optimistic about the technology: “Despite the misconception that we are years away from blockchain technology, we are already in the next "This year we'll see full deployments in financial services, insurance and healthcare. It will completely disrupt our payments system internationally." Other emerging technologies have steeper learning curves, says Robert Bardunias, co-founder and chief tax officer of IRIS.TV, who admires the technology's entrepreneurial focus. “These technologies are growing from day one with a focus on operational business applications, so developers don't have to imagine use cases—they emerge and evolve in real time,” Bardounias comments. “Keeping up with new developments and changes will be challenging. challenge for anyone who wants to become a professional in this field. I remember how I once developed minor professional skills such as reading websites - and trade magazines. This is the last thing I wanted to do, but today it is mandatory part of the training of a developer who would like to gain and maintain a competitive advantage in the global market."
Mesh Applications and Services Architecture (MASA)
There is also an ever-growing demand for applications that can maintain an uninterrupted connection, switch and work as we move around the house. “The point of a mesh is high availability: all the elements are connected to each other,” says Joseph Carson of Thycotic. “If a route is not available, another device will be found to establish the connection. This is used, for example, for Tile's tracking devices , as well as for cryptocurrencies such as Bitcoin as a distributed means of financial accounting." Other experts point to a potential bottleneck in the lack of sufficient device compatibility. “All vendors, in their own way, are trying to build consumer trust by keeping their ecosystems, if they exist at all, closed,” says Derek Collison, CEO of Apcera (formerly of Cloud Foundry). “I think artificial intelligence will be trained in the clouds, on huge amounts of data from all users,” says Collison. “These algorithms will continuously update their execution models, which will be transmitted wirelessly to endpoints and used to update firmware "on our phones, cars and home devices. Data processing will take place on the hardware of local devices, and training will take place using software in the cloud."
Digital twins
Connected to physical and virtual sensors, software models can be used to predict product and service failures, allowing companies to plan and allocate resources to perform repairs before failure occurs. Advances in machine learning and the introduction of artificial intelligence technologies are reducing the cost of such predictive modeling, called “digital twins,” which makes it possible to significantly increase efficiency and reduce operating costs over the life of, say, a jet engine or power plant. According to Matias Woloski, CTO and co-founder of Auth0, businesses will be able to use digital twins also at the conceptual and design stage, conducting simulations of new software products with step-by-step changes until a satisfactory result is achieved. The information obtained from digital twins will be taken into account when creating the product. “Several organizations are already using digital twins. This technology is mainly in demand in those projects where the upfront costs are too high, and, consequently, the price of failure,” shares Voloshsky. SpaceTime Insight CTO Paul Hofmann says digital twins use machine learning to make them more effective at predicting failures than condition-based maintenance models. “With IoT and machine learning systems, companies can be confident that their resources will not randomly fail, and if they do, the company can make the best decision in real time for the long term.”
Driverless cars, robots and home appliances
Household appliances, industrial equipment, cars and drones are becoming smarter thanks to artificial intelligence and machine learning. Research firm Gartner estimates that by 2020, 61 million connected vehicles will roll off automakers' production lines per year. “Entire economies are growing here,” says Vince Jeffs, director of product strategy and marketing at Pegasystems. — For example, there are startups and already formed companies that deal with artificial intelligence, which have become quite firmly established in the field of autonomous vehicles. For example, MobileEye is a company with $500 million in venture capital that specializes in small cameras placed throughout the car. Likewise, there are companies that sell physical robots—SoftBank Robotics, for example, specializes in hotel concierge robots. They have $250 million in venture capital." Advances in deep learning have led to improvements in computer vision, natural language processing and speech, as well as the ability of machines and software to "strive for reward" and maximize productivity, says Wayne Thompson, chief SAS data scientist: "The result is a new generation of machines capable of seeing the world, hearing and reading natural languages, communicating with people and self-regulating both mechanically and behaviorally in a way that is completely unprecedented." Although many people see automation as a nightmare , putting people out of work, others argue that these technologies are leading to a brighter and more humane future. “I often get asked about the consequences of automation,” says Michael Hubbard, director of global communications at ServiceNow. — Intelligent automation is not a threat, but a tremendous opportunity. It can free us from routine activities, opening the door to creativity and allowing us to create stronger, more productive work relationships."
Virtual and augmented reality
After decades of intrusive advertising, virtual and augmented reality are finally reaching a turning point. And for those who want to develop products based on these technologies, new horizons are opening up: expanding the sensations during games. “These technologies are not yet very common, but they have become much more mature in recent years,” shares Anup Nair, vice president and technical director of Mphasis Digital. “I believe that in the biomedical and healthcare industries, AR /VR will bring enormous benefits, both for training purposes and for sharing information about complex surgical procedures. We see plans for AR activities aimed at performing in-depth analysis in the social media control centers of large banks, as well as in the exchange floors where they will provide There's endless space for stockbrokers to analyze data and collaborate." Christian Sasso, an associate professor in the VR/AR graduate program at San Jose-based Cogswell College, sees augmented reality as the biggest technology trend of the year. "AR will be a reality very soon. to service customers when they need to repair a company-produced device,” Sesso says. “For example, in a project I'm working on, augmented reality glasses are used to communicate with a customer service consultant in the event of a broken TV or monitor. When speaking directly with a customer through an augmented reality interface, a company representative can obtain all the necessary information by visually inspecting a broken screen, without having to describe the problem over the phone or search for a serial number." "AR and VR technologies will not be widespread until more affordable and high-quality hardware for them,” says Vishwa Ranjan, head of augmented and virtual reality at Infosys. “As early as 2017, we will see smartphone companies begin to develop augmented and virtual reality capabilities, such as technologies based on facial recognition, location detection, the use of sensors and 360-degree cameras, which will play a significant role in promoting sales of AR and VR devices to early buyers."
Humanoid helpers
This is the next stage of artificial intelligence! We will do away with the clunky tools we currently use to interact with the digital world. According to experts, we will soon be using assistive tools for more than just online ordering of goods and services or searching the Internet. They will become an extension of our own brain. We will no longer need to remember as much information: with the help of technological tools, we will free up resources for analytical and critical thinking." What should we pay attention to if we are interested in the development of such assistive technologies? "The greatest demand now is for deep knowledge," “says Günther Ohlmann, Head of Security at Vectra. “For example, expert knowledge in the field of information security (web application security, network forensics, malware disassembly).” David Parmenter, data scientist and chief technology officer at Adobe Document Cloud, says the key to this, even more than a computer science degree, is a passion for math and logic. “Creativity, a desire to constantly learn, customer-centric thinking, resilience in the face of failure—the results of machine learning are by no means a finished product—and communication skills are the most important soft skills for engineers working in this field.”
And the winner... is a combination of all this!
While artificial intelligence is probably the most frequently cited disruptive technology of the year, the most important trend is the convergence of rapidly evolving emerging technologies. Canonical's Maarten Ectors lists more than a dozen different technologies that, when combined, yield more than the sum of their parts: "cloud, mobile, IoT, artificial intelligence, blockchain, augmented reality, voice interfaces, software controlled radio communications, the 'fourth industrial revolution' [automation and data communication in industry], robotics, edge computing and driverless cars." Patrick Spadding, of Rocket Software, says separate technologies are coming together largely because of companies' need to get out of their own data, such as when analyzing website traffic. “When you add in the growth of new data sources like the Internet of Things,” he says, “it’s not easy to just keep up with the volume of information available to make business decisions.” Spadding believes that the prospects for merging cognitive technologies, bots and machine languages will increase as they become more understandable. A new generation of digital natives will accelerate the adoption of these combined technologies, he says, as they expect ease of use, game-like interfaces, and the ubiquity of augmented and virtual reality.
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