Today is 2020-08-05 Wednesday,Welcome to this site 

Common problem

Top 10 strategic technology development trends in 2019, automation technology tops the list

Word:[Big][Middle][Small] QR Code 2018/11/19     Viewed:    
From October 14th to 18th, at the Gartner Symposium / ITxpo 2018 conference, analysts discussed the top 10 strategic technology trends that companies and organizations need to explore in 2019 (Gartner Top 10 Strategic Technology Trends 2019).


Gartner defines a strategic technology trend as a strategic technology trend with huge disruptive potential. The strategy has begun to break from emerging and further develop into applications with broader impact-or a fast-growing trend, with a high degree of volatility in Reaching a tipping point in the next five years.

"In the future, smart devices will be featured, providing increasingly insightful digital services everywhere. We call it smart digital grid." Gartner vice president and researcher David Cearley said: "Smart digital grids have China has always been one of the focus and has been the main driver of 2019. Trends under these three themes are a key factor driving the continuous innovation process as part of the ContinuousNEXT strategy. "

-Intelligence: How artificial intelligence penetrates almost all existing technologies and creates entirely new categories.

-Digital: Blend the digital world with the real physical world to create an immersive world.

-Grid: Leverage the growing connection between people, businesses, devices, content, and services.

"For example, artificial intelligence (AI) in the form of automation and enhanced intelligence, used in conjunction with the Internet of Things, edge computing and digital twins, can provide a highly integrated smart space. The combined effect of these multiple trends will create new opportunities and drive The new wave of disruption is a sign of Gartner's top ten strategic technology trends for 2019. "

Although science fiction may portray artificial intelligence robots as bad guys, some tech giants have now begun using them for security management. Companies such as Microsoft and Uber use Knightscope K5 robots to patrol parking lots and large outdoor areas to predict and prevent crime. Robots can read license plates, report suspicious activity, and collect data to report to their owners.

人工智能 These artificial intelligence-driven robots are just one example of "automating things". It is one of Gartner's top ten strategic technologies in 2019, which may bring major disruptions and opportunities in the next five years.

Gartner pointed out that technologies such as blockchain, quantum computing, enhanced analytics and artificial intelligence will promote the creation of disruptive new business models.


Gartner's top ten strategic technology trends for 2019 are:
1. everything in automation


Autonomous devices such as robots, drones, and autonomous vehicles will rely on using AI to automatically perform functions previously performed by humans. Their automation goes beyond the automation provided by rigid programming models, and they leverage AI to provide advanced behaviors that interact more naturally with their surroundings and people.

 "With the proliferation of autonomous things, we expect to shift from independent intelligent things to a whole bunch of collaborative intelligent things, with multiple devices working together, whether independent of humans or human input," Mr. Cearley said. "For example, if a drone inspects a large oil field and finds it is ready for production, it can dispatch an 'automated oil extraction machine' to perform the task. In the logistics delivery market, the most effective solution may be to use automatic Drive the vehicle to move the package to the target area. Robots and drones on the vehicle then ensure the final delivery of the package. "

There are five main types of "automated things":

-Robot

-Vehicle

-Drone

-Home appliances

-Medium


These five types occupy four environments: ocean, land, air, and digital. They all have varying degrees of ability, coordination and intelligence. For example, they can span drones that are assisted by human-assisted flight in the air, operating entirely autonomously in agricultural fields. This paints a broad picture of potential applications-almost every application, service, and IoT object will employ some form of AI to automate or enhance processes or human operations.

Explore the possibilities of AI-driven autonomous functions in any physical object in an organization or customer environment, but at the same time keep in mind that these devices are best suited for narrowly defined purposes. They differ from the human brain's ability in decision-making, intelligence, or general learning.


2. Enhance analysis

Augmented analysis represents the third wave of data and analytical capabilities, as data scientists can use automated algorithms to explore more hypotheses and possibilities.

Enhanced analytics focuses on specific areas of enhanced intelligence, using machine learning (ML) to transform the way content is developed, consumed, and shared. Enhanced analysis capabilities will quickly advance to mainstream applications as key features of data preparation, data management, modern analysis, business process management, process mining, and data science platforms.

自动 Automated insights from enhanced analytics will also be embedded in enterprise applications, changing the process by which businesses generate analytical insights. For example, human resources, finance, sales, marketing, customer service, purchasing, and asset management. These collaborations and matching will optimize the decisions and actions of all employees in their environment, not just for analysts and data scientists. Augmented analytics automates data preparation, insight generation, and insight visualization processes, eliminating the need for professional data scientists in many cases.

"This will lead to the further popularization of data science, an emerging set of features and practices that enable users who work primarily outside the field of statistics and analysis to extract predictive and normative insights from data," Cearley Mr. said.

"By 2020, the number of ordinary citizen data scientists will grow five times faster than the number of expert data scientists. Organizations can use citizen data scientists to fill the data science and machine learning talent gap caused by data scientist shortages and high costs . "

"By 2020, more than 40% of data science tasks will be automated." Enhanced analytics can identify hidden patterns while eliminating personal biases. Between citizen data scientists and enhanced analytics, data insights will be more widely used across the enterprise, including analysts, decision makers, and operations workers.

3.AI-driven development

The market is rapidly shifting from a model where professional data scientists must work with application developers to create most AI-enhanced solutions, to a model where professional developers can operate independently using predefined models provided as a service. This provides developers with an ecosystem of artificial intelligence algorithms and models, as well as development tools tailored to integrate AI functions and models into the solution.

As AI is applied to the development process itself to automate various data science, application development, and testing functions, another opportunity “peak” for professional application development has emerged. By 2022, at least 40% of new application development projects will have AI co-developers on their teams.

"Ultimately, highly advanced AI-based development environment automation applications will usher in a new era of 'civilian application developers' in both functional and non-functional terms, and non-professionals will be able to automatically generate new The solution. Tools that enable non-professionals to generate applications without coding are nothing new, but we want AI-driven systems to increase flexibility, "Mr. Cearley said.

驱动 AI-driven development looks at the tools, techniques, and best practices for embedding AI into applications and using AI to create AI-driven tools for the development process. This trend is developing along three areas:

-The tools for building AI-based solutions are expanding from tools for data scientists (AI infrastructure, AI frameworks and AI platforms) to tools for professional developer communities (AI platforms, AI services).

-The tools for building AI-based solutions are being given AI-driven capabilities that can help professional developers and automate tasks related to the development of AI-enhanced solutions.

-AI-enabled tools are evolving from assisting and automating application development (AD) related functions to higher level activities using business domain expertise and automating AD process stacks (from general development to business solution design).

The market will shift from a data scientist focused on working with developers to a developer who operates independently using a predefined model provided as a service. This enables more developers to take advantage of these services and increase efficiency.

4. Digital twins

Digital twins refer to the digital representation of real-world entities or systems. By 2020, Gartner estimates that there will be more than 20 billion connected sensors and endpoints, and digital twins will connect billions of physical devices. Business organizations implement digital twins from the start. They will evolve over time, improve their ability to collect and visualize the right data, apply the right analysis and rules, and respond effectively to business goals.

"One aspect of the development of digital twins beyond the Internet of Things is that companies implement their organization's digital twins (DTO). DTO is a dynamic software model that relies on operations or other data to understand how an organization implements its business model and connects its current Status, deploy resources and respond to changes to meet expected customer value, "Mr. Cearley said. "DTO helps increase the efficiency of business processes and creates more flexible, dynamic, and responsive processes that can automatically respond to changing conditions."

Digital twins can also be connected to create twins for large systems, such as power plants or cities. The idea of digital twins is not new. It goes back to a computer-aided design representation of things or an online profile of a customer, but today's digital twins differ in four ways:

-The robustness of the models, focusing on how they support specific business outcomes;

-Links to the real world, which may be used for monitoring and control in real time;

-Apply advanced big data analysis and artificial intelligence to drive new business opportunities;

-Ability to interact with them and evaluate "what if" scenarios.

Today's focus is on digital twins in the Internet of Things-it can improve business decisions by providing information about maintenance and reliability, insights on how products perform more efficiently, new product data, and increased efficiency.

5. Empowerment Edge

Edge refers to endpoint devices that people use or embed in the world around us. Edge computing describes a computing topology where information processing, content collection, and delivery are closer to these endpoints. It tries to keep traffic and processing closer to 'localization', with the goal of reducing traffic loss and latency.

In the short term, the edge is driven by the Internet of Things, which requires processing to be closer to the endpoint rather than a centralized cloud server. However, cloud computing and edge computing are not creating new architectures, but are developed as complementary models. Cloud services are managed as centralized services-not only on centralized servers, but also in local distributed servers and edge devices themselves. .

ArtGartner expects that in the next five years (2028), dedicated AI chips and more powerful processing power, storage and other advanced functions will be added to a wider range of edge devices. The extreme heterogeneity of the embedded IoT world and the long life cycle of assets such as industrial systems will pose significant management challenges. In the long run, as 5G matures, the ever-expanding edge computing environment will return more powerful communications to centralized services. 5G provides lower latency, higher bandwidth, and (very importantly the edge) the number of nodes (edge endpoints) per square kilometer has increased dramatically.

At present, most of the focus of this technology is that IoT systems need to provide disconnected or distributed functions in the embedded IoT world. This type of topology will address challenges such as high WAN costs and unacceptable levels of latency. In addition, it will implement the details of digital business and IT solutions.

6. Immersive experience (immersive technology)

Conversational platforms are changing the way people interact with the digital world. Virtual reality (VR), augmented reality (AR), and mixed reality (MR) are changing the way people perceive the digital world. This combination of perceptual and interaction models will transform the immersive user experience of the future.

"Over time, we will transition from considering personal devices and decentralized user interface (UI) technologies to multi-channel and multi-modal experiences. Multi-modal experiences connect people with the digital world, including traditional computing devices, wearables , Automotive, environmental sensors and consumer electronics, hundreds of edge devices. "Mr. Cearley said.

"Multi-channel experiences will use all human senses and advanced computer senses (such as heat, humidity and radar) in these multi-mode devices. This multi-experience environment will create an environmental experience in which the space around us defines" "Computers", not individual devices. In fact, the environment is a computer. "

20By 2022, 70% of enterprises will try to use immersive technology for consumption and enterprise use, and 25% will deploy to production. The future of conversation platforms, from virtual personal assistants to chatbots, will combine extended sensory channels to enable the platform to detect emotions based on facial expressions, and they will become more smooth in their interactions.

7.Blockchain

Is a distributed ledger that promises to reshape the industry by achieving trust, providing transparency and reducing friction between business ecosystems, thereby reducing costs, shortening transaction settlement times and improving cash flow. Today, trust is placed on banks, stock exchanges, governments, and many other institutions as central authorities to securely maintain a "single version of the truth" in their databases. Centralized trust models increase transaction delays and friction costs (commissions, fees, and time value of money). Blockchain provides another model of trust without a central agency to arbitrate transactions.

"Current blockchain technologies and concepts are immature in mission-critical, large-scale business operations, and little is known and unproven. This is especially true for complex elements that support more complex scenarios," Mr. Cearley said . "Despite the challenges, the huge potential for disruption means that CIOs and IT leaders should start evaluating blockchains, even if they will not actively adopt these technologies in the next few years."

At present, many blockchain plans do not implement all the attributes of the blockchain, such as highly distributed databases. These blockchain-based solutions are positioned as a means to achieve operational efficiency through automated business processes or through digital records. They have the potential to enhance information sharing between known entities and improve opportunities to track and trace physical and digital assets.

However, these methods miss the value of the true disruptive impact of blockchain and may increase vendor lock-in. Those organizations that choose such practices should be aware of these limitations and be prepared to gradually complete blockchain solutions over time to ensure that the same results can be achieved through more effective and efficient use of existing non-blockchain technologies .

ArtGartner predicts that blockchain will create 3.1 trillion business value by 2030.

8. Smart Space

Smart space refers to the physical or digital environment, human and technology-supported systems that interact in an increasingly open, connected, coordinated and intelligent ecosystem. Multiple elements-including people, processes, services and things-will be brought together in a smart space to create a more immersive, interactive and automated experience for target populations and industry scenarios.

"This trend has been integrated for some time, such as smart cities, digital workplaces, smart homes, and connected factories. We believe that the market is entering a period of accelerated provision of powerful smart spaces, and technology has become an integral part of our daily lives. Whether as an employee, customer, consumer, community member or citizen, "Mr. Cearley said.

The five key dimensions of smart space expansion are: openness, connectivity, coordination, intelligence, and application scope.

9. Digital Ethics and Privacy

Digital ethics and privacy are a growing concern for individuals, organizations, and governments. There is growing concern about how organizations in the public and private sectors use their personal information, and only those organizations that have not proactively addressed these issues continue to raise objections.

"Any discussion of privacy must be based on the broader digital ethics theme and the trust of customers, voters and employees. Although privacy and security are fundamental building blocks of trust, trust is really more than just these components, "Mr. Cearley said. "Trust is the acceptance of the truthfulness of a statement without evidence or investigation. Ultimately, an organization's position on privacy must be driven by its broader stance on ethics and trust. Moving from privacy to ethics and making conversations transcend" "Are we compliant?" And turned to 'Is we doing the right thing?' "

Governments are increasingly planning or passing regulations that companies must comply with, and consumers are carefully protecting or deleting information about themselves. Companies must gain and maintain trust with their customers to be successful, and they must also adhere to internal values to ensure that customers see them as trusted partners.

10. Quantum Computing

Quantum computing (QC) is a non-classical calculation whose operation is based on the quantum states of subatomic particles (eg, electrons and ions), which represent information as elements of qubits (qubits).

For example, although a classic computer reads every book in a library in a linear fashion, a quantum computer reads all books at the same time. Quantum computers can theoretically process millions of calculations simultaneously. Quantum computing that is commercially available, affordable, and in the form of reliable services will change an industry.

The parallel execution and exponential scalability of quantum computers means that they are superior to problems where traditional methods are too complex, or traditional algorithms take a long time to find a solution. Industries such as automotive, finance, insurance, pharmaceuticals, military, and research institutions benefit the most from advances in quality control.

For example, in the pharmaceutical industry, quantum computing can be used to simulate molecular interactions at the atomic level to speed up the market for new cancer treatments, or quantum computing can accelerate and more accurately predict protein interactions, leading to new pharmaceutical methods .

The real world applications of quantum computing have gone from personalized medicine to a wide range of phenomena such as image recognition optimization. The technology is still emerging, which means it's a good time for businesses to increase their understanding of potential applications and consider any security risks.

"CIOs and IT leaders should begin planning for quality control by increasing understanding and how to apply it to real business problems. When technology is still emerging, start investing. Identify those quantum computing with the potential to go Solve real-world problems and consider the possible impact on security, "Mr Cearley said. "But at the same time, don't expect it to change something completely in the coming years. Most organizations should understand and monitor the application of quantum computing by 2022, and may need to start using it from 2023 or 2025."

Gartner Symposium/ITxpoAbout Gartner Symposium / ITxpo
ArtGartner Symposium / ITxpo is the world's most important gathering of CIOs and senior IT leaders, combining the global CIO community with tools and strategies to help them lead the next generation of IT and achieve business results. With more than 25,000 CIOs worldwide, senior business and IT leaders will come together to gain the insight they need to ensure their IT initiatives will be key contributors and enablers of their business success.




Disclaimer: This article is transferred from www.ca800.com. All works that indicate the source of this website are works that are legally copyrighted or authorized to use on this website. Reprints are welcome. Please indicate the source when reprinting. The works not from this website are from the Internet. The purpose of reprinting is to convey more information. It does not mean that this website agrees with its views and is responsible for its authenticity. If copyright issues are involved, please contact us to delete them.

Go Back
Print
400-118-7786
浏览手机站