7 Technologies That A Developer Should Dig Into
7 Technologies That A Developer Should Dig Into
These seven technologies are driving innovation. Here's how to position yourself for success in fields ranging from IoT security to data science.
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From IoT security to virtual and augmented realities, opportunities are emerging and successfully transforming current tech trends.
New and emerging technologies are successfully reshaping the entire software industry by offering endless opportunities for developers to pivot and embrace new skills. Further speaking about the industry, there’s always something new on the horizon, and this post explores a few tech marvels, such as AI, VR, AR, IoT, and machine learning — all of which is technology coming up with an eye on the future.
Internet of Things Security
The forthcoming revolution of the Internet of Things and smart home tech has arrived. But even after last year's massive cyber attack on DYN, observers did not show any further interest in these unprotected IoT devices. The good news is that now developers and security teams have started working together to address the problem more wisely by, for example, providing the ability for IoT devices to download security updates.
The attackers in IoT are most likely to be identical to those of any other distributed networks, like computers or smartphones. So, having same security knowledge is quite acceptable. Demand for professionals with IoT skills is increasing day by day, especially those who are well-versed in the potential vulnerabilities of the hardware and software used by net-connected devices. In addition to this, a better understanding of differential privacy and adversarial networks will be an added advantage.
The next big thing of autonomous vehicles, robots, and smart electronics is the need for AI-savvy professionals. Although science fiction often portrays AI as robots with human-like characteristics, AI can encompass anything from Google’s search algorithms to autonomous weapons. It is a going to have a huge impact on software development, with developers becoming more like data scientists and AI officials.
AI entirely changes how a software is written. With the help of deep learning and accelerated analytics, developers train the software to make it more intelligent and give it the ability to interact. There has been speculation about smart machines which means there will be a need of coders with different skills. Engineers curate the data and take the software through the process of learning by itself, writing scripts to interact with software more effectively.
With the recent explosion of interest in interactive applications, there has been a mismatch between supply and demand. Thus, experts excelling in the subject will always remain a valuable commodity until and unless the equation gets balanced.
Much like artificial intelligence, machine learning can receive massive amounts of data, such as recommending a movie to stream, without being explicitly programmed to do so. In recent years, the technology has successfully emerged to assist and enhance Google’s core search engine algorithm. In the year 2017, machine learning updates are expected to enter almost any and every type of consumer application.
Based on mature analytics capabilities, the technology is trending toward the new normal, with people expecting such kinds of artificial intelligence. Now, not every developer comes from a computer science background. Hence, more and more people are being recruited and trained to become machine learning professionals.
Having a core engineering background benefits an engineer to be more successful by continuously running experiments and improving machine learning models.
Another trending area, data science requires profoundly skilled professionals for different industries. A developer needs to be well-experienced with machine learning and AI to research through large amounts of data, the results of which can be used to make quick business decisions.
A thorough understanding of probability and statistics is key for those who wish to make their careers in this area in particular. Plus, one also needs to master the math of data science.
Software models tied to physical and virtual sensors can predict product or service failures so that the organization can plan and assign resources to make repairs before the failure occurs.
The digital twin model has the potential to boost efficiency and bring down operating costs over the life of a jet engine or power plant. Many organizations have launched digital twins with large upfront projects for the best long-term solutions.
Virtual and Augmented Realities
Virtual and augmented realities are finally having their moment. Developers creating a product based on such technologies have a golden opportunity to go beyond creating isolated gaming experiences. A consistent increase in the relevance of technology has been seen in the product marketing and immersive selling arenas.
In the present age, we will observe smartphone companies developing products incorporating AR- and VR-based features like image-recognition-based, location-based, and sensor-based technologies, and of course, 360 cameras that will help to push AR and VR out into early adopter’s hands.
Humanlike assistants are the next stage of artificial intelligence. A main benefit is that it eliminates all the clunky tools currently being used to interact with the digital world. In this case, most workplaces would be integrated with intelligent apps in order to increase overall productivity. Researchers reveal that the technology is an extension of human brains that is free to drive analytical and critical thinking.
AI is cited as one of the most breakthrough technology emerging in the year 2017. Apart from these aforementioned technologies, strong communication skills are very important soft skills for engineers in this field.
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