Top strategic technology trends for 2019
Technology is now central to most industries. So, advances in technology in 2019 will be closely followed to interpret the new possibilities and challenges they present.
Gartner, the international research and consulting organisation, has presented their top strategic technology trends for 2019. To Gartner, the future strategic technology trends focus around making artificial intelligence (AI) along with machine learning (ML) converge and support continuous innovation across a digital world, virtual world, and the real world.
In other words, how to make AI and ML a part of our everyday lives at home and in work.
We are going to get more tools and apps that do the work for consumers and business owners, automating lives in many ways so that boring, time-consuming tasks can be automated, which will also increase the demand for connected devices.
Whether it’s a car or a robot, autonomous applications use AI to perform tasks traditionally done by humans. The sophistication of the intelligence varies, but all autonomous things use AI to interact more naturally depending on the environment they are in.
Virtually every application, service and IoT (Internet of Things) object will incorporate some form of AI to automate or augment processes or human actions.
Collaborative autonomous things will increasingly be seen as the future of AI systems. But you do need to keep in mind that these devices are best used for narrowly defined purposes. They do not have the same capability as a human brain for decision making, intelligence or general-purpose learning.
AI in 2019 will cross the chasm into the mainstream, solving real problems for people in a variety of industries, not just ads, search and self-driving cars.
Data scientists now have increasing amounts of data to prepare, analyse and group data from which to draw conclusions.
Given the amount of data, there is the risk of “analysis paralysis”, where the possibilities become infinite. This means businesses can miss key insights from hypotheses the data scientists don’t have the capacity to explore.
Augmented analytics represents a third major wave for data and analytics capabilities using automated algorithms to explore more hypotheses.
Data science and ML platforms have transformed how businesses generate analytics insight.
Augmented analytics identify hidden patterns while removing the risk of personal bias.
Improved human and AI collaboration.
AI-driven development looks at tools, technologies and best practices for embedding AI into applications and using AI to create AI-powered tools for the development process.
The tools used to build AI-powered solutions are expanding from tools targeting data scientists to tools targeting the professional developer community.
With these tools, the professional developer can infuse AI powered capabilities and models into an application, speeding up the development process.
By empowering a wider range of mainstream software developers to develop applications it should also mean that the automating activities can be applied to a broader range of business domains.
As more developers utilise the services, it should increase the speed of the development cycle.
Cyber security – hackers never sleep.
As hackers become more sophisticated, a new generation of security methods to address the new cyber security threats needs to use a more active approach tapping into ML and other methods to identify attacks.
Trends are already showing that the tech world is focusing on how to address cyber security risks by using ML and AI to predict and protect against attacks.
The majority of cyber-attacks are not planned or highly targeted. They are automated and indiscriminate, exploiting known vulnerabilities within commonly used IT systems.
With so many businesses now relying on technology such as websites, social media, facilitating online sales and cloud services it makes them vulnerable to malicious cyber-attacks, data loss and reputational damage. And as long as a business connects to the internet it immediately becomes vulnerable.
In the past few years hackers have turned to unsecure IoT devices to create an extensive botnet which then they could use to push enough traffic to create a Distributed Denial of Service attack (DDoS).
Gartner forecasts that 20.4 billion connected things will be in use worldwide by 2020. And with the rise of autonomous things there is a good chance that many of these things will not have a high level of security.
In 2019, it will be paramount for IoT manufacturers and all of their supply chain to dramatically increase the security in all the products. It can be a connected refrigerator, a robot, a drone, a vehicle, or a health tracker.
In 2019 there will be a convergence between AI, ML, and Deep Learning in business applications.
These technologies will unlock a large amount of value for business as they become integrated into standard processes, leading to productivity gains and better results.
The future of conversational platforms, which range from virtual personal assistants to chatbots, will incorporate expanded sensory channels to detect emotions based on facial expressions.
AI powered chatbots are frequently used for basic customer service and in operating systems as virtual assistants, programmed to behave and communicate with an audience as a human being would.
The use of chatbots is still evolving, but currently encompasses a wide range of services and their ease of use and usefulness has grown in recent years.
Very few websites that you visit these days, don’t involve some kind of pop-up asking if you need help. Chatbots are able to respond to simple questions taking on some of the boring admin tasks.
Natural language processing (NLP) is an emerging technology that uses voice recognition. It’s a form of AI that focuses on analysing the human language to draw insights and context from what is being written or said.
When you’re typing a text message on your smart phone, you’ll see word suggestions based on what you type and what you’re currently typing. That’s natural language processing.
As NLP develops, devices such as Google’s Assistant and Amazon’s Alexa, digital or virtual assistants will see improved human to AI interaction.
Gives us a whole new mode of experience to communicate with the digital world.
Advances in Augmented Reality (AR), Virtual Reality (VR), and Mixed Reality (MR), all of which can be summarized in R+ will provide going forward new practical applications for industries.
With the next generation of VR able to sense shapes and track a user’s position and MR enabling people to view and interact with their world.
R+, which once was only found in video gaming has been quickly advancing to become a useful tool in industries such as engineering design, manufacturing, healthcare, space exploration, and many others.
In 2019, VR and AR are going to open up to innovative industrial applications that will change how people work and collaborate as the cost of entry drops, the number of applications will rise as VR and AR become more mainstream.
By 2022, 70% of enterprises will be experimenting with immersive technologies for consumer and enterprise use, and 25% will have deployed to production.
A Blockchain comeback.
Blockchain allows companies to trace a transaction and work with untrusted parties without the need for a centralised party (i.e., a bank). This greatly reduces business friction and has applications that began in finance, but have expanded to government, healthcare, manufacturing, supply chain and others.
Blockchain could potentially lower costs, reduce transaction settlement times and improve cash flow. The technology has also given way to a host of blockchain-inspired solutions that utilise some of the benefits and parts of blockchain.
A smart space is a physical or digital environment in which humans and technology-enabled systems interact within connected, coordinated and intelligent ecosystems.
Essentially, smart spaces happen when individual technologies start to converge and create a collaborative and interactive environment.
The most extensive example of smart spaces is smart cities, where areas that combine business, residential and industrial communities are being designed using intelligent urban ecosystem frameworks, to link social and community collaboration.
Digital ethics and privacy
Consumers have a growing awareness of the value of their personal information, and they are increasingly concerned with how it’s being used by public and private entities.
You need look no further than Facebook to see the public backlash against companies perceived as using data without permission.
Governments are increasingly planning or passing regulations with which companies must comply such, as the recent GDPR. As the Facebook incidents have shown, consumers are carefully guarding or now removing their information from the public domain.
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