Accentuating the cycle of innovation by advancements in AI and ML technologies

Artificial intelligence and machine learning are driving the frontiers of change and innovation in various technological domains. The commercial potential of machine learning is profound in federated machine learning. Similarly, the applications of artificial intelligence within the healthcare sector are preparing us for any future pandemics if they are to occur. We are also seeing innovation in natural language generation with the help of AI and ML breakthroughs. As the scope of AI and ML is increasing, the demand for professionals in this sector is also rising. There are two options that are available before us. The first option is to reskill our workforce so that they cope up with the new and emerging trends in machine learning and artificial intelligence. The second option is to provide machine learning training in Bangalore and other Metropolitan cities where thousands of jobs are popping up that require the above-mentioned skills. Let us take a look at some of the most important facets of change and innovation that are a direct result of advancement in AI and ML technologies.

Federated machine learning

Federated machine learning is popularly called a cloud in a pocket methodology. This is because the tools and techniques that are used in federated machine learning are not dependent upon the cloud environment. All the information can be stored in the device itself. The advantage of federated machine learning is that the privacy and sensitivity of data can be properly taken care of. It needs to be noted at this point in time that the prediction of AI modeling is still available when it comes to federated ML. The commercial applications of federated machine learning include the Apple M1 chip and advanced neural engine. Other applications of federated machine learning include the detection of frauds in the banking sector and the prediction of boom and bust market cycles in the financial sector.

Health stack

The present pandemic has exposed the lacuna in the healthcare sector. Apart from many negatives, one of the prospective technological advances that we have been able to make is the integration of AI technology into the health stack. A Health stack is a repository of patient records and keeps track of prescriptions, advice, medicines, tests, and other investigations that are critical for understanding the health of a patient. Health stack not only gives access to the medical history of the patient but also helps doctors in quick examination and diagnosis. The preliminary idea of health stack has been developed in India but it is present in a concrete shape in developed countries like Japan. Japan has already integrated its health care system with artificial intelligence technologies to pave the way for medical advancement and research.


Personalization is extremely important in a time when the digital domain is flooded with e-commerce firms. To compete in a thriving market, it is necessary to create personalized products and services according to the needs of the customers. When customers are provided with personal recommendations, it leads to brand positioning and strengthening customer relationships. The targeted marketing campaigns that we are seeing in the present times are also being personalized by taking inputs from AI and ML in the e-commerce sector.

The chatbots operating in the E-Commerce sector make use of machine learning techniques to enhance their cognitive capabilities and understand the needs of the customers in a better way. We may conclude that machine learning techniques are inevitable for strengthening the grievance redressal mechanism and boosting the growth as well as revenue of a company in the long run.

Natural Language Generation

With the help of machine learning, natural language processing, understanding as well as generation has drastically improved the cognitive capabilities of robots and humanoids. Other systems which are dependent upon natural language processing and generation have also evolved due to advances in machine learning. One of the best examples of natural language generation is presented by Google smart compose. In the future, we may see the development of smart assistants, smart companions, and smart chatbots given the advances in the natural language generation sector.

Concluding remarks

The innovations that are a direct consequence of artificial intelligence will pave the way for rapid advances in various sectors. The need of the hour is to prioritize research labs, think tanks, and idea factories that are pushing the limits of artificial intelligence and machine learning. In one word, it is difficult to envisage the advancement of industry 4.0 without diversification of AI and ML technologies.

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