Most of us, technology geeks or not, are eager to stay first in line to catch up with the latest game-changing technology trends. Here we are to know which technologies will thrive in 2019!
The Potential Technology Trends You Need To Explore In 2019
Have you ever looked up at the sky and clapped your eyelids on a bat? This is commonplace. But what if it was a drone. Or would it be a flying fleet? Since we don’t belong to the Jetsons family, the latter is not expected but we are close to it! 2019 is definitely a transformative year for technological innovation!
According to Gartner, the Top 10 Strategic Technology Trends for 2019 are Block chain, Artificial Intelligence, Empowered Edge, Privacy and Digital Ethics, Quantum Computing, Immersive Experiences, Augmented Analytics, Autonomous Things, and Digital Twins!
This is just the tip of the iceberg. Following are the emerging technology trends and catalyzing technical innovation that we can expect to see more of in 2019!!
Related Reading: Find how digital innovation is transforming today’s business world.
1. Blockchain Technology – The ‘New Internet’
Some call Blockchain technology the ‘New Internet’. The blockchain is the brainchild of a person or group of people known by the pseudonym, Satoshi Nakamoto. It permits digital information to be distributed but not duplicated.
“Blockchain solves the manipulation problem”, says Vitalik Buterin, inventor of Ethereum.
2. Artificial Intelligence (AI)
Apart from AI-powered chatbots, 2019 will witness chip manufacturers such as Intel, NVIDIA, AMD, ARM, and Qualcomm shipping specialized chips that speed up the execution of AI-enabled applications.
2019 will also be the year for hyperscale infrastructure companies like Amazon, Microsoft, Google, and Facebook.
Related Reading: Check out the top AI trends of 2019.
3. Cloud-independent edge computing
The study from IDC illustrates that 45 percent of the entire data created by IoT devices will be stored, processed, analyzed and acted upon close to or at the edge of a network by 2020! Edge computing is a mesh network of data centers that process and store data locally before being sent to a centralized storage center or cloud.
4. Privacy and Digital Ethics
Facebook, recently witnessed the biggest security breach in which 50 million accounts were compromised. Facebook, later clarified that data of 30 million accounts were stolen.
People are becoming more nervous about how organizations and third-parties are using their personal data.
5. Quantum Computing
The world is behind building the first fully-functional quantum computer. Also called the supercomputer, this is expected to be a cloud service rather than an on-prem service. IBM is already offering cloud-based quantum computing services. For instance, the automotive, financial, insurance, pharmaceuticals, military, and research industries have the most to gain from the advancements in Quantum Computing.
6. Immersive Experiences
Conversational platforms are changing the way in which people communicate with the digital world. Virtual reality (VR), augmented reality (AR) and mixed reality (MR) are changing their approaches to know more about people’s perception.
7. Augmented Analytics
Augmented analytics relies on augmented intelligence. This uses machine learning (ML) to transform how analytics content can be developed, consumed and shared.
“Through 2020, the number of data scientists will grow five times faster than the number of experts”, says David Cearley!
8. Autonomous Things
Autonomous things, such as robots, drones, and autonomous fleet, use Artificial Intelligence techniques to automate their functions that were previously performed by humans.
9. Digital Twins
A digital twin is a digital representation of real-world items that are interlinked. Cearley states that there can be digital twins of people, processes, and things!
A DTO is an aspect of the Digital Twin evolution that is a dynamic software model that relies on operational or other data. DTOs help drive efficiencies in business processes.
Apart from these, there are other key technology trends that organizations need to explore in 2019. These include:
10. Cybersecurity and Risk Management
According to the estimates from the firm Gemalto, the data breaches were 4.5 billion in the first half of 2018! The University of Maryland study found that hackers attack computers every 39 seconds.
In 2019 we will be facing a more sophisticated array of physical security and cybersecurity challenges.
Cybersecurity is thus the digital glue that has held IoT, Smart Cities, and the world of converged machines, sensors, applications, and algorithms operational throughout!
11. Smart Spaces
A smart space is a physical or digital environment in which humans and technology-enabled systems interact in an increasingly open, connected, coordinated and intelligent ecosystems, according to Gartner! The world of technology is to enter accelerated delivery of smart spaces in 2019.
12. Self-powered data centers
Data centers grow every minute with the implementation of virtual servers and storage, energy-efficient buildings. In 2019, the data centers are expected to run on its own self-contained power plants!
13. IoT integration
2019 will witness more IoT implementation. An International Forrester IT survey that said among a recent group study, 82% of respondents were unable to identify all of the devices connected to their networks. Of this lot, 54% were nervous about device security, and 55% were concerned about integration!
Related Reading: Find the role of Data Analytics in Internet of Things (IoT)
14. More self-service IT kiosks for business users
2019 will be a year of IT innovation designed to build better communication between IT and end users. The self-service IT kiosks to be set up would enable users to log on and choose what they want for the apps that they build.
15. The Internet of Things and Smart Cities
50 billion equipment, including smartphones, and others are expected by the IoT to be wirelessly connected via a network of sensors to the internet by 2020!
The term “Smart City” means creating a public/private infrastructure to conduct activities that protect and secure citizens. It integrates communications (5-G), transportation, energy, water resources, waste collections, smart-building technologies, and security technologies and services!
To upgrade your business with the latest technology trends on the table, contact the experts at Fingent today! Also, read through our latest blogs to learn more about accelerated technological development!!
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Improving the customer experience is the mantra for survival in today’s highly competitive business environment. More and more businesses have identified machine learning as a reliable tool towards this end.
Machine learning is in essence software coded differently to traditional software. Rather than a long list of if-then-else statements typical of traditional software, machine learning predicts what humans would do given a specific set of inputs.
Currently, marketers and others leverage machine learning to further customer experience through improved personalization, enhancing the computer vision, improving natural language, greater decision support, through analytics optimization, and augmented analytics.
1. Machine Learning Aids Personalisation
Today’s highly pampered customers prefer and even demand personalized engagement and experiences. Machine Learning facilitates it to the hilt. Data and analytics allow marketers to understand customer preferences. Using machine learning in combination with new data sources from the Internet of Things (IoT,) telematics, geolocation beacons, and social data improve the insights.
Several marketers now apply machine learning based algorithms to understand the nuances of their customer’s preferences and engage them on their terms. Marketers use such algorithms to develop highly relevant marketing campaigns, such as a matching audience profile with highly targeted video content. These steps improve the call-to-action.
Customers receive tailored offers rather than irrelevant non-contextual offers. Such non-contextualized offers have a very low probability of conversion.
Segmentation gets better. For instance, insurance companies do not have to go by general assumptions or time-honored conventions to offer the highest automobile insurance premiums to a 16-to-25-year-old male. They can factor in everything specifically related to the customer, and tailor the premium based on individual rather than class factors.
The creation of such relevant content is the godsend at a time when over 90% of online users in the U.S. and Europe feels advertising is more intrusive today compared to two years ago.
Related Infographic: Machine Learning- Deciphering the most Disruptive Innovation
2. Machine Learning Facilitates Computer Vision
Machine Learning technology detects everything and anything, from objects and people to complex scenes within the images and videos. Applying the technology to enhance the quality of digital assets is a sure-shot way to win the customer’s heart.
One big success story is Twitter’s Magic Pony, which leverages machine learning technology to make pixelated images sharper, and enhances the quality of video captured on mobile phones in poor lighting conditions. Apart from delighting the customer, the spin-off benefit of Twitter is lower data usage, and by extension improved streaming abilities.
3. Machine Learning Aids Natural Language Processing
The next big thing revolutionizing human interactions with computers is speech recognition technology. The ability of computers to recognize human speech and act on it not only spares the hassles of keyboard typing but also unlocks a host of new possibilities. While speech recognition technology has been around for a while, the application of advanced machine learning technologies has made the system highly accurate, with error rates far lower than humans. Google’s Cloud Speech API now recognizes over 80 languages and variants, with a high level of accuracy.
Marketers can, and are leveraging advanced linguistic data and cognitive technologies spawned by speech recognition capabilities to create highly engaging content, targeted at the customer. In a sense, it furthers the cause of personalization in a big way.
Marketers benefit from natural language capabilities in myriad other ways also. A case in point is the intuitive new tool launched by Relative Insight, a UK based start-up. The tool converts natural language into data, offering marketers a wealth of information to connect with specific audiences instantly and deeply.
4. Machine Learning Improves Decision Support
Machine learning allows the marketers to predict the future. The “machine” becomes capable enough to predict the customer’s likely course of action, based on the data at his disposal, and his present behavior. The market is now flooded with several digital tools and services which provide advanced recommendations on this front.
On the anvil is “copyless paste,” where machine learning will save users time by proactively offering to share information between apps. Marketers will leverage the concept further to offer proactive product suggestions. Integration with other systems also offers the scope for proactive and automatic delivery.
5. Machine Learning Facilitates Analytical Optimization
Businesses leverage the immense analytics opportunities offered by machine data to fine-tune their operations, deliver new business models, and offer new products and services in tune with customer demand. The insights gained, predict not just how a customer may behave or act, but also how the competition may move in the future.
One sector where machine learning algorithms are already in widespread use is the financial sector. Financial services companies use various machine learning algorithms such as random forest and gradient boosted models for a host of applications, from predicting the probability of being ranked at the top of aggregator portals to predict midterm cancellation rates on policies, and more. These applications have a direct bearing on customer satisfaction. For example, banks and financial institutions predict volumes for credit card lines, to adjust rates and terms, and thereby attract the right type and volume of customers for the specific product.
Related Reading: Top Artificial Intelligence Trends to Watch Out for In 2019
6. Machine Learning Facilitates Augmented Analytics
The scope of machine learning improves with the development of technology. Neural networks support better classification and forecasting, decision trees support more complex rule and relationship-based customer experience programs. All these improve the organization’s ability to support complex decisions, forecasts, and optimizations.
Augmented analytics, which co-opts these latest and emerging technologies, combines various elements of the ecosystem, such as data preparation, business intelligence, predictive analytics and machine learning capabilities into a single, automatic and seamless process. Enterprises would be able to cleanse their data easily, to uncover latent insights and patterns.
Today’s huge data create millions of variable combinations impossible to process manually or even with traditional tools. Augmented analytics, powered by machine learning, deliver quicker insights, reducing customer frustration.
What exists now is just the tip of the iceberg. The future holds a world of possibilities. A case in point is the fragmented nature of the machine learning ecosystem being all set for a big churn. Increased competition, the hyper-fast paced changes in technology, and the proliferation of big data at an alarming frequency force many open source machine learning libraries, algorithms and frameworks to join forces and deliver a better deal to their customers. The lower-level personalization commonplace today will make way for a more robust collaborative filtering, delivering a much higher degree of personalization and contextualization than present levels.
Side-by-side, the machine learning ecosystem is becoming increasingly easier to use, and more affordable. Hitherto, only enterprises with large analytics teams could really afford to play around with machine learning. The advent of various solutions delivered in a cloud-based subscription model makes the power of machine learning available to the masses, including start-ups, freelancers, and even individuals.
Marketers and brands can leverage the improved ecosystem to generate a better picture of their customers’ true context, and serve them better. Simply put, customers will get better food, movie, music, travel, product and purchase recommendations.
Related Reading: AI To Solve Today’s Retail Profit Problems