Introduction
Artificial intelligence is a discipline that makes use of machine learning to execute different tasks with a high degree of precision. There is a very thin line of demarcation between artificial Intelligence and machine learning. Most of the time, machine learning and artificial intelligence are used interchangeably. However, we can classify machine learning as a subset of artificial intelligence. The juxtaposition of applied AI, machine learning, and data science gives rise to a plethora of applications. For instance, different types of autonomous vehicles or self-driving cars, robotic drones, sensors, recommendation systems, etc. are some of the applications of Artificial Intelligence and machine learning. In this article, we take a look at the most popular use cases of applied AI and machine learning.
The aerial machines
Aerial machines are the most popular flying machines that we may witness in the times to come. The aerial machines are possible with the collaboration of Mechanical engineering, Automobile Engineering, Computer Science Engineering, Artificial Intelligence, and machine learning. Such types of machines are already undergoing trial and this can be seen in the form of flying taxis and autonomous drones. The flying machines that we would see in the future would not only ferry and transport passengers from one place to another but would also transport cargo in a short span of time. They would boost our logistic linkages and improve connectivity.
Aerial machines like drones would also help in monitoring agriculture. This would boost productivity as well as agriculture exports. Sensagri is a project that helps in monitoring agriculture with the help of drones that are fitted with sensors. These sensors give inputs to the central system which makes the use of artificial intelligence to detect the incidence of various diseases in crops.
Humanoid Technology
Humanoid technology is a direct outcome of artificial intelligence and machine learning that have enabled us to make rapid advancements in erstwhile robotic technology. This indicates that humanoid technology is an advancement over robotic technology and is the successor of the same. Humanoid technology is itself undergoing advancement and we are seeing the birth of social humanoids that are equipped with state-of-the-art thinking and cognitive capabilities. The cognitive capabilities of humanoids have been advanced by deep learning as well as artificial neural networks.
Humanoid technology has already found its fit in the real world as some digital shops make use of this new technology to cater to client requirements. Advanced chatbots are also a subset of this technology as they are equipped with advanced communication capabilities powered by applied artificial intelligence and machine learning. With the help of artificial intelligence, chatbots can understand human language, process it, and then draft suitable replies.
Fintech platforms
As the world moves towards a digital era, the relevance and importance of fintech platforms keep on accentuating. A large number of transactions are now carried out on these platforms. It is in this context that Artificial Intelligence can help us in boosting the cyber security of Fintech platforms. Let us consider a case where critical data, as well as sensitive data of customers, comes under cyber attack. This means that the entire financial system would become vulnerable and this may lead to a digital invasion by intruders and hackers.
It is in this context that applied artificial intelligence and machine learning can help in conceiving a security framework that plugs the loopholes and vulnerabilities in our cybersecurity architecture.
The different techniques that would help in improving our digital security infrastructure include ensemble models and other machine learning algorithms. For instance, ongoing research suggests that ensemble models like gradient boosting are very much accurate in the detection of threats in advance. Early detection can help in raising security alarms and protecting sensitive information.
Other use cases
In addition to the use cases mentioned above, there are a large number of other applications where artificial intelligence and machine learning have brought about a significant impact. In the education sector, artificial intelligence now allows us to understand the lacuna in student preparations. It also allows us to evaluate students individually using CBT examination and conceive a grievance redressal mechanism tailored to their requirements. In the healthcare system, artificial intelligence is the prime technology behind the formation of the national health stack that helps in the storage and processing of patient records and early diagnosis of various ailments. Artificial intelligence and machine learning also find applications in the e-commerce sector, logistics sector, stock market, and recommendation systems.
