Top 10 latest technologies in IT industry

The technology is now evolving at such a rapid rate that annual trend forecasts may appear outdated even before being published as a blog post or published article. As technology advances, it enables even faster change and progress, causing the rate of change to accelerate until it finally becomes exponential.

The latest technologies in IT industry are:

1. Artificial intelligence (AI)

Artificial intelligence, or AI, has already received a lot of attention in recent years, but it's still a trend to watch because its effects on the way we live, work, and play are only in the early stages. In addition, other branches of artificial intelligence have been developed, including machine learning, which we will discuss below. AI refers to computer systems designed to mimic human intelligence and perform tasks such as image recognition, speech or pattern recognition, and decision making. AI can perform these tasks faster and more accurately than humans.

AI is part of what we generally call automation, and automation is a hot topic due to possible job loss. Experts say automation will cut 73 million more jobs by 2030. However, automation creates and reduces jobs, especially in AI: Experts predict that jobs in 'AI will be 23 million by 2020.

2. Machine learning

Machine learning is a subset of AI. With Machine Learning, computers are programmed to learn to do something they are not programmed to do: they learn by discovering patterns and ideas from data.

Although Machine Learning is a subset of AI, we also have subsets in the area of Machine Learning, including neural networks, natural language processing (NLP), and deep learning. Each of these subsets offers the opportunity to specialize in a professional area that will only grow.

Machine learning is rapidly being implemented in all types of industries, creating a high demand for qualified professionals. The Machine Learning market is expected to reach $ 8.81 billion by 2022. Machine Learning applications are used for data analysis, data mining, and pattern recognition. On the consumer side, Machine Learning optimizes web search results, real-time advertising, and network intrusion detection, to name a few of the many tasks it can perform.

3. Automation of robotic processes or RPA

Like artificial intelligence and machine learning, robotic process automation, or RPA, is another technology that automates work. RPA is the use of software to automate business processes such as application interpretation, transaction processing, data processing, and even email response. RPA automates the repetitive tasks that people used to do. These are not just the subordinate tasks of a low-paid worker: Up to 45% of the activities we do can be automated, including the work of financial managers, doctors, and CEOs.

For you as a forward-thinking IT professional trying to understand technology trends, RPA offers many career opportunities, including developer, project manager, business analyst, solution architect, and consultant. And these jobs pay well. Job Search Engine says the average RPA salary is $ 73,861, but it's the compiled average of salaries from junior developers to senior solution architects, with the top 10% earning more than $ 141,000 a year.

4. Cyber Security

Cyber Security may not seem like an emerging technology, as it has been around for a while, but it evolves like other technologies. This is in part because threats are constantly new. Hackers attempting to illegally access data will not give up any time soon, and will continue to search for ways to carry out even the most stringent security measures. This is also partly because new technologies are adapting to enhance security.

5. Internet of things (IoT)

Many "things" are being built with WiFi connectivity, which means they can connect to the Internet, and to each other. Hence, the Internet of Things, or IoT. The Internet of Things is the future, and it has already enabled devices, appliances, cars, and much more to be connected and exchange data over the Internet. And we are only in the early stages of IoT: the number of IoT devices reached 8.4 billion in 2017 and should reach 30 billion in 2020.

As consumers, we already use and benefit from IoT. We can remotely close our doors if we forget when we go to work and preheat our ovens on the way home from work, while following our fitness in our Fitbits and welcoming Lyft. But companies also have a lot to gain now and in the near future. IoT can enable better security, efficiency, and decision-making for businesses as data is collected and analyzed. It can enable predictive maintenance, accelerate healthcare, improve customer service, and deliver benefits we don't even have

6. AR, VR and MR

Augmented reality (AR) adds digital elements to a live view often by using the camera on a smartphone. Examples of augmented reality experiences include Snapchat lenses and the game Pokemon Go. 

Virtual reality (VR) implies a complete immersion experience that shuts out the physical world. Using VR devices such as HTC Vive, Oculus Rift or Google Cardboard, users can be transported into a number of real-world and imagined environments such as the middle of a squawking penguin colony or even the back of a dragon.

In a Mixed Reality (MR) experience, which combines elements of both AR and VR, real-world and digital objects interact. Mixed reality technology is just now starting to take off with Microsoft’s HoloLens one of the most notable early mixed reality apparatuses.

7. Big Data

Big data is a field that treats ways to analyze, systematically extract information from, or otherwise deal with data sets that are too large or complex to be dealt with by traditional data-processing application software. Data with many cases (rows) offer greater statistical power, while data with higher complexity (more attributes or columns) may lead to a higher false discovery rate. Big data challenges include capturing data, data storage, data analysis, search, sharing, transfer, visualization, querying, updating, information privacy and data source.

 Big data was originally associated with three key concepts: volume, variety, and velocity. When we handle big data, we may not sample but simply observe and track what happens. Therefore, big data often includes data with sizes that exceed the capacity of traditional software to process within an acceptable time and value.

8. Block Chain

Blockchain, sometimes referred to as Distributed Ledger Technology (DLT), makes the history of any digital asset unalterable and transparent through the use of decentralization and cryptographic hashing.  

A simple analogy for understanding blockchain technology is a Google Doc. When we create a document and share it with a group of people, the document is distributed instead of copied or transferred. This creates a decentralized distribution chain that gives everyone access to the document at the same time. No one is locked out awaiting changes from another party, while all modifications to the doc are being recorded in real-time, making changes completely transparent.

9. SMAC

Social media, Mobile computing, Analytics and Cloud computing will rule the roost in the coming time. By 2020 there will be more than 5 billion mobile devices connected to internet. This means people will use internet more frequently and generate variety of data like photos, comments, status on social media, data related to browsing behavior, location related data etc. So techniques like digital marketing, big data analytic, distributed computing will be no more business enablers but become drivers of business. The need for vast amount of storage capacity and distributed computing will actually work in favour of cloud computing.

10. LiFi

It is a technology related to telecommunications but can have significant impact on information technology. LiFi is a communication technology which is 100 time faster than WiFi. It takes the help of light signals to transmit data. Because of its speed it can have impact on computing technologies like Big Data Analytics.