By: Anurag Edlabadkar

Artificial Intelligence and Machine Learning Have Taken Center Stage – Here’s Why?

Data Science | AI | ML

Are you aware that we are stepping into the world of Artificial Intelligence (AI) and Machine Learning (ML)? Both the categories are evolving to upgrade the measures of footing. It is only due to the fact we are moving into the era of scientific, where every little technology is getting into its actuality and materiality. There are of course multiple fields, where you may find these engineering sciences getting its possession. For instance, you may watch them dwelling in Cloud computing, Industry Transformation, Customer Service Execution, Academic Output, Film Making, Finance and much more services that are endless. Mostly, Machine learning appears to be the sub-branch of Artificial Intelligence.

AI and ML are not new launches. Investigations prove that, right from 1950, materialized projects were under continuous research to make it process through AI and ML. It is only from past 5-10 years, the Artificial Intelligence and Machine Learning are shining into reality and stamped its real presence.

AI Software- Definition

Artificial Intelligence is the art of science to drive machines to perform the intellectual operation, thinking and working identically to humans. It comprises of broad categories of strategies that will instruct a computer to execute various assignments. AI Software involves a set of algorithms to instruct the computer to respond to specific tasks. This set of instructions also involves networks of hardware and software that imprecise the web of neurons within the human brain. Machine Learning is, of course, a teaching technique for the machines to abstract intuitive commands and orders, and then to react accordingly. The tasks may include, problem-solving, speech recognition, planning, and machine learning of new technologies that are trendy.

In the process of creating intelligent software, replicating number of potentialities such as perception, reasoning, logical thinking, and knowledge representation, becomes the core commands of its algorithm. In today’s world, the application of Artificial Intelligent Software is in wide practice like in your smartphone assistant, Voice and Image recognition techniques wherever implemented, ATM and in the software of the ads of various websites, that you tend to come across every time you access them. These applications are just the beginning stage of the AI platform, where you will soon spot its tremendous growth in various other real-time practices.

Artificial Intelligence & Machine Learning takes Center Stage


• Research Computing – It is because of the development of the research-computing platform, assimilation of the public cloud and advancement of Graphics Processing Units became possible. This largely led to the growth of AI. With the usage of cognitive computing for handling research, the interest in the development of AI also became huge. When HPC (High-Performance Computing) systems and other Bio-informatics fields required enlargement of methods and expansion of software tools, research computing gave hand at the right time.

Research Computing

The accessibility of Public Cloud infrastructure and the steady growth of HPC systems, entitled the research to become computationally persistent. The research also gained its intensity with the growing need for GPUs. All these are for no doubt, going to be supercharging technological research based on AI.

• More areas getting beneficial- AI offers assistance to human-like decision-making capabilities for its algorithm. These algorithms have the tendency to accept or reject the recommendation with precise reasoning. Areas like Medicine will have assistance on diagnosis with effective solutions too. AI can work to present output, just under a second, that humans actually cannot. The AI-based system can very well accomplish complex tasks, which the humans are not efficient in performing and time-consuming process like repetitive steps.
These AI defined systems tend to increase the efficiency of the overall output and can handle huge amounts of data. Right from the storage and accessing process of data, industries find the AI-based technology to be more productive.

• In Education- As per the revelation of industry beholders, the coming times of higher education will entirely take its focus on personal development, instead of on the accession of knowledge with the evolution of Machine Learning. For the companies to face AI and robotic process automation, they demand high-level talented professionals for the execution of the intended pathway.

This is the period where you could discern AI and robots making a difference in the behavior of people and transition in society. In order to mold the future generation, we should make the students focus on their personal growth. This makes them shine out of the ordinary, to understand the technology better. With the evolvement of AI, it is not that we are changing like machines, but to change machines to execute like humans. Make the generation to work for AI, but not to work as an AI.

• Future of AI- The true success of AI is in inter-relating HPC systems and frameworks jointly. Figuring out the demand in computing, storage, and network, in most industries, the enhancement in the significant growth of research in AI, is on its way to reaching the goal. Connecting these complex systems is incredibly a true challenge. However, Artificial Intelligence is pushing its development pace to make you enter the golden period of research computing soon.

Future of AI

As stated earlier, the presence of AI and ML is trying to accomplish numerous platforms. As in the current situation, let us have an overlook on the various stages where you may find these technologies marking their productivity and remarkable efficiency.

Machine Learning Propelling Finance Services

Banks are thriving to advantage this technology in their ‘self-driving finance’ envelope. A company such as Forbes, predict that its higher percentile of customers will only count on Artificial Intelligence to benefit their finance and consequently, to attain their goal. Companies like Amazon Web Services, Google’s Cloud computing, and Microsoft Azure are becoming the leaders of MLaaS (Machine Learning as a Service) providers. This is possible only because of the premier research of Artificial Intelligence by these organizations. The revenue-based on MLaaS for these companies may easily cross $20 billion by the end of the year 2025. The highly competitive cloud computing service is moving towards the next phase, as it becomes an easy-to-implement task with the convenient Machine Learning key as a differentiator.

Automated Machine Learning

The unique trend that is radically going to flip over the true face of ML-based techniques is Automated Machine Learning (AutoML). Top-notch companies declare their prediction of empowering their business analysts and developers to unfold machine-learning methodologies to identify extreme complex structures. What more to expect from AutoML? It is for no doubt that AutoML is going to be more flexible, versatile and customizable, helping your business analysts to target on various industrial concerns in spite of taking charges on technical stratagem and workflow systems.

AI to scope for Tremendous Opportunities

Artificial Intelligence, a modern approach is becoming competitive enough to create sufficient jobs across the globe. Variable sources are expecting AI to pursue delivering thunderstruck breakthroughs in the upcoming years. AI applications are capable of solving real-world problems according to the insights of Analytics. With the help of ML, data analysis can create models that can easily automate decisions, acknowledge pattern and set predictions. Concentrated attention on Machine Learning along with AI will result in supporting human psychology like ever before.
Studies show that by the end of the year 2019, AI and ML will be generating numerous job opportunities than the current circumstance. It can find its positions in other platforms like healthcare, education and the public sector. Despite the loss of human jobs due to automation in various companies, you need to overlook the number of jobs AI would otherwise offer in the future.

With the increased demand for AI and ML professionals in technical and data science platforms, other domains like legal, social and customer experience solutions are encountering the shortages. Finding the best-talented experts in AI and ML is always been the tough part for many business organizations.

Also Read: Future scope for RPA (Robotic Process Automation)

Adaptive Learning through AI

Adaptive Learning (AL) is an approach of a much larger perspective of personalized learning. Adaptive Learning Algorithm literally focuses on the use of engineering science to personalize learning. In an AL methodology, the system is capable of maintaining track on everything that a learner is up to. The set of algorithms of AL can easily judge the entire action of the learner and is helpful in training the particular individual as per the requirement.

Adaptive Learning through AI

The future of AL largely depends on Artificial Intelligence. The technology used for AL is still in its infancy stage. It is only when the inventors exert away the algorithms, AI can start upgrading from the current growth rate. Just to explain the scale of progress, Google’s Deepmind’s AlphaGo made its way by winning the world’s most popular Go players recently. This complex game shows the real victory of AI when implemented through a consistent Adaptive Learning. This machine learning process, which is helping to learn new methodologies and concepts, will definitely mark its presence in the world of AI. Henceforth, Artificial Intelligence learning methods can supportively provide psychomotor domain training through simulations coordinating the real-life scenarios.

AI Recognition in Real-World Applications

Smart devices such as the Alexa and Google, are just the beginning of voice recognizing technology as a striking launch for the real-world applications. There is a prediction that more such AI devices will soon manifest their exceptional utilization in this superior technological world. Renowned electronic labels have already unveiled their launch of devices that will work with the voice- recognized controls. Sony, LG, Whirlpool and Hisense, all come under the list. They are working for the launch of their stipulated devices, which can ultimately work and process through smart AI devices like Alexa. This will also make way to renovate every home to work under automation. What more? Image recognition processing is also in its infancy stage, making Artificial Intelligence strikes its way to the field of Medicine and even road traffic. For detecting License plates and diagnosing diseases with a better approach, here AI comes under usage.

Businesses Investing in Data Quality

Every business is continuing to invest in maintaining their data quality and Information Architecture. The emergence of Artificial Intelligence in Business covers every sector precisely, keeping one thing to be as the top challenge for AI. Maintaining Data Quality and organizing an AI-worthy domain, remains to be the top question unanswered. AI adopters will pursue to pay towards Information Architecture in order to put their business perception in actuality. AI development in building a better substructure for manipulating data and qualifying their business users will tend to continue in its ultimate process.

AI Supports Marketers to Refine Targets

With the reliability of predictive analytics, marketers tend to integrate data mining, machine learning, AI and modeling. As with the traditional concept of using the information to propel decisions, marketers were in the mesh to handle huge Data processing method with the inefficient output. By making use of AI, they begin to foresee the activities of the customers with a much bigger amount of reliability and precision. They are capable of identifying the content having the most influence, address the points early and optimize their way of handling business.

Decision Making with the Elevation of Prescriptive Analytics

While the predictive analysis anticipates the budding future outcomes, prescriptive analytics helps in presenting the courses of actions with its respective solution. This stratagem can help business in pinpointing specific suggestions via heuristics, Deep learning, and other AI prospects. With the evolution of more industries empowering prescriptive analytics, we do have a future of contemplating intelligent supply chains, productive outputs, and satisfied systems. Ultimately, this will give rise to happy customers and automatically well-fulfilled business.


Here, we are in the world of Artificial Intelligence creating buzz across the globe. There is no sector, where you can find the absence of AI. Either directly or indirectly, the evolution of AI and Machine Learning is under swift progress to attain a world filled with ease of living and prosperity. This period of development is exactly where you find science fiction becoming naked truth and certainty. There are proofs that AI and ML are into the system of gaining large amounts of traction, to retain in the center stage.

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