Top 10 Trends In Artificial Intelligence That Will Dominate 2019

Everybody is talking about the latest trends in “Artificial Intelligence” — the new normal, which is almost part of every work process in every industry. Throughout 2018, you have observed an exponential upthrust in applications, tools, and platforms assembled on Artificial Intelligence and machine learning technologies. These technologies not just left an impression on software or the internet trade but also other dimensions of health-care, agriculture, manufacturing, and many more.

So, most of you might be wondering about “what is the future of artificial intelligence in 2019 heading to 2020?” whereas, some may be stuck onto “uniqueness” of Artificial Intelligence. Others are still thinking “AI is all buildup and not in work”.

All unanswerable questions to think upon.

With new technologies emerging their wings, Artificial Intelligence has made a significant breakthrough in 2018. If you don’t trust me, have a look around yourself and witness the subtle convenience AI has proffered to you. The response promoter in Gmail, Alexa at your centre table, automatic voice calls to schedule your salon appointment for “Me Time” and how can you forget self-driving cars on the road.

Apart from the above mentioned scenarios, there are a lot of other industries harnessing the rise of applied AI. As per the latest report from Statista, the revenue from the latest trends in Artificial Intelligence is expected to witness a massive growth in the coming years. Therefore, making it crystal clear “early acceptor are boosting their Artificial Intelligence investment, launching more ventures, and getting positive returns”.

This growth is further accelerated by investments in the emerging technologies in artificial intelligence by a distinctive ratio of 21% and is expected to rise more in the coming years. Suffice to say, there will be an upward trajectory witnessed in 2019 as well.

Time to look at top trends of Artificial Intelligence in 2019:

1. Conventions in AI

The ethics of AI is a vital part of the ethics of technology. Instead, this is a broad topic and simultaneously a personal quest for some.

As uncle Ben said in Spiderman “With Great Power Comes With Great Responsibility”, this axiom holds for the latest Artificial Intelligence applications. Amidst debates and discussions of AI replacing the human race, the bottom line to be answered is

**“**Are the self-ruling and intelligent systems developed in a manner that consists individual and social ethical values”?

2018 was the year to witness a lot of presentations, videos, white papers, and what else you can count for this topic. This topic grows with every passing day, even in 2019.

Possibly, you must be thinking what the few things are done to be sure of the ethical design of AI-based applications are?

Following the IEEE Global Initiative On Ethics for the autonomous and intelligent system, it is mandatory to have policy and guidelines keeping the following areas in mind:

Transparency: This is not only to enforce the policy of data usage but also for validated access to the rules inculcated in the system besides the audit trails.

Legit Accountability: Instead, it is a property law or any legal authority for any harm caused by AI applications.

Giving Values To AI Applications: This is possible in a way by expressing values in terms of obligations and prohibitions that can be performed arithmetically.

Administration Framework: The Guidelines, process and procedure not to breach upon the fundamental human rights.

Policies: The policies around the impacts and association of this application should be at the appropriate place.

2. The Emergence Of AI Based Chips

Distinct from other Softwares, the latest development in the field of artificial intelligence reckons on the specially designed processors that complement CPU. Moreover, the fastest and latest CPU might not be able to improve the speed of training an AI based model. While presuming, the model requires additional hardware to work on complex mathematical calculations to accelerate the task like facial recognization or object detection.

In 2019, the giant chip manufacturers like Intel, NVIDIA, AMD, Qualcomm, ARM will issue customized chips that speed-up the execution of AI-based applications as a blink of eye process. These chips will be specially optimized for particular cases and scenarios related to computer vision, processing of natural language, and speech recognization.

Moreover, they will be seen cementing footprints with next-generation applications in the dimension of healthcare and automobile field. Some of the chips will assist the next-generation database in accelerating the query processing and predictive analytics.

3. Convergence Of IoT, Blockchain, And AI At The Verge

2019, will be the year witnessing examples of the convergence of Blockchain with AI, and IoT (Internet Of Things) with AI.

As a matter of fact, self-driven cars is not a rational thought without IoT working with Artificial Intelligence. The sensors established in the car to collect real-time data is enabled and accessed by IoT, whereas the latest innovations in artificial intelligence models accustom the programs used by the vehicle for decision-making.

For a better understanding, the deep learning AI algorithms take necessary actions and make decisions based on this data. Some include path planning, driver monitoring with an eye-tracking feature, natural language processing to understand the voice commands, or you can assume a self-direct control to commence for a gas station when running low on fuel.

This is not all; the other added feature to these autonomous vehicles will be the ability to communicate, so the traffic as a whole is streamlined.

Wait! There is another tremendous integration — Blockchain and AI. You all know Blockchain technology has some demurs in the dimensions of security and scalability while AI undergoes from privacy and trust issues. But, when both combine to address these issues, the Blockchain accustoms the decentralized data marketplace, and AI works to be more trustworthy and sheer.

4. Automatic Machine Learning Will Be The Next High Point : “Reinforcement Learning”

Reinforcement learning is the next big thing in the latest development in the field of artificial intelligence. Yes, it differs from supervised and unsupervised methods. Supervised learning involves learning with descriptive datasets and giving an output that is generic to that particular dataset(finding the price of a specific land piece given the land value in one specific location). Whereas, unsupervised learning includes finding the association between unlabeled data or arraying that data. (imagine a cluster of photos that are not labelled but have parameters like colour, size, shades, etc. And, the program will result in output whether the image is flower or animal).

Reinforcement learning is a distinctive approach from the above mentioned methods. It is an approach of machine learning that is inspired by a behaviourist psychologist, similar to how a child learns to perform the task. In technical language, it is a framework that does not use the data-recognization techniques. Instead, it uses experience-driven decision making.

In the context of trends in Artificial Intelligence, it is a dynamic learning programming that prepares an algorithm based on a system of rewards and punishment.

The use of reinforcement learning is still under consideration, yet industries are exploring the application and would continue to experiment with it in the coming years.

Lookout for the use of some of the Industrial cases that are under consideration:

• Higher Education — The useful purpose of reinforcement learning for customized learning and teaching experience.
• Health Maintenance — Take a healthy Decision for treatment policies for chronic illness like Diabetes, delusions, and many others.

5. The Dawn Of Quantum Computing With AI

Artificial intelligence and quantum computers are the very two enthralling frontiers. Every day, it seems to be an innovation with the most advanced quantum computers. So, before you allay with any myth in the new artificial intelligence technologies that would make quantum computing better in 2019, somewhat its good to be a little pushy in the right direction for creating better quantum computing devices. Nevertheless, it would be a small increment but still a huge focal point in the arena of AI.

Quantum computers work solely on quantum physics that compute calculations much faster than a supercomputer. You must be equipped with the computer system using bits and bytes. Unlike a conventional system, a quantum computer uses Qubits to store information.

However, it’s a long way to go in terms of dealing with demurs of Quantum computing in regards to maintain the coherence of the qubits or expel the noisy and not needed computations.

Whereas, the most awaited solution will be to solve the almost unsolvable problems like tracing other planets like Earth in the galaxy, climate change, or our body having the ability to destroy cancerous cells.

6. Social Economic Models

The most prominent question on everybody’s lip at the time of attending any AI event is “Would Artificial Intelligence future trends take away the jobs ?”. The answer in a single outline is “it depends”.

While Artificial Intelligence is taking over every day-to-day task where resources are scarce, it is instantaneously proffering new jobs with a unique skill set. The main reason being the risk of widening the skill gap and holding the potential for creating polarized societies.

As you know, current trends in Artificial Intelligence is attracting new skills and jobs; it is mandatory to complement it with value-creation. For instance, automation might erase the need for a specific, but there would be a pursuit for high-touch jobs on the same note.

7. A Digital Drift Of Neural Networks

A natural assumption for “Neural Network in Artificial Intelligence” is to replicate the brain’s capabilities and functionalities, encompassing being intelligent. They store all the data in the digital form — text, time, or sensory that is further used to classify the information.

The mounting need of neural network is no more a surprise, to improvise predictions in the stock market, diagnosis of particular health concerns or even composing music. Moreover, they act as an essential stepping stone in “Deep Learning”. The neural network creates powerful algorithms used for processing natural language, speech recognization. It acts as a helping hand for autonomous vehicles, detecting traces of cancer, or fraud detection.

Undoubtedly, 2019 will be a year proven to increase the research that goes deep into it so that you can harness the benefits of the power of the latest Artificial Intelligence applications for real-time altering solutions.

8. Facial Recognization: An Innovation

The face is a unique identity of an individual. It plays a significant role in communicating with other persons in society. Considering these facts, facial recognization is established in the real world and is unfurling the benefits of Artificial Intelligence future trends.

Facial recognization is defined as a technology that helps in identifying a person using their digital image or patterns of facial features. 2019 is witnessing a drift in the usage of this application with precision and reliability.

You must be familiar with Facebook’s Deepface program, which makes tagging your friends and family in photos a lot easier job.

Nevertheless, the boom in personalizing everything — from updating your wardrobe to marketing, this technology is cementing its footprints for every biometric identification.

9. Biased Data

This biased data trend in Artificial Intelligence topic is turning increasingly imperative as machine learning models are used for decision making like — social beneficial norms, mortgage loans, hiring and lot more.

For a better understanding, consider a fictional case of decision for promoting women. The traditional data for employment shows women getting less promoted than men and therefore creating a discriminatory AI-based application.

So, with the increased use of the latest Artificial Intelligence applications, there would be a gradual increment in learning how to deal with biased data. The affliction lies with the businesses to consider proactive steps to accept principles of non-discriminatory data.

Some of the ways to prevent this approach are an inspection of potential risks, active inclusion from diversified inputs, and a perfect balance between speed and performance.

10. Privacy And Policy

The introduction of GDPR was the talk of the town in 2018. And, 2019 is also experiencing privacy and policy conversational concerns for the latest development in the field of artificial intelligence. This is mandated in pursuit to safeguard the privacy and assure the organization approaches data privacy concern earnestly.

Many among you might be unaware of how your digital information can be used. Sometimes it is lost in the prints and sometimes not even informed about its usage. Facebook’s latest crisis over privacy concern is the tip of the iceberg.

The laws surrounding AI is still new and also need further understanding. Whereas, countries across the globe also continues to work on strategies and initiative to guide the development of AI regulation.

Wrapping Up,

The trends in Artificial Intelligence is shaping today and tomorrow. The technology has benefited the modern society with an outlook of a better world that not only peep out of the curtain at present but give a significant and clear picture of an improved and happy world.

Therefore, if you want to hire the best Artificial Intelligence application developers for your next Artificial Intelligence project, you should rely on the companies outsourcing highly skilled and qualified experts who understand the value of your dream and herald in the technology for better.

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