Artificial Intelligence (AI), Big Data and Machine Learning (ML) are the topics of every article. What is the reason? Applications of these technologies are affecting every domain of business. But all of the big data, Artificial Intelligence (AI) and machine learning (ML) are distinct from each other. If you are a non-technical person and want to adopt these new technologies but you are not sure which technology is beneficial for your business and in which technology you should invest. In this article, you will get a clear understanding of big data, AI, Machine learning and in which technology you should invest.
Analyzing inputs by applying logic and making decisions on the basis of analytics this process is known as intelligence and It is called artificial intelligence if this process is done by machine. AI can take inputs (audio or visual), process them and make decisions and output desired results just like humans. Artificial Intelligence is creating intelligence machines to reduce human workload in an efficient and more reliable way. AI is very common these days in every domain although this is just the beginning of AI age, we can see it everywhere, from games to fully-autonomous cars, imagine the potential of this technology. We are moving with AI in our pocket in the form of Samsung’s Bixby, Apple’s Siri, Amazon’s Alexa and google assistant and consider a day without them, It is beyond imagination because we are relying on them for many of our daily routine tasks. Many projects that require a certain level of precision, human rely on machines for these difficult tasks. But can AI completely work on its own? The answer is No! because AI is in its initial stages it requires human interaction. It is due to AI that organizations are capable of performing online identity verification for KYC compliance and can combat identity theft to stop crime as their part of the duty. Even at initial stage AI is much precise, efficient and providing better results than human.
Machine learning is an application of artificial intelligence. How a machine can become intelligent? It has to learn how to process data. It is a method through which computers can learn to think and act like humans. But a machine can’t learn on its own. It is a process similar to how babies learn. Machine learning is becoming so popular because it works like magic to solve a particular problem but it is based on how you made it intelligent, it is a software called learning model. Learning models are different for different scenarios. For instance, if your problem is to verify numbers using a camera than your ML model would be based on teaching numbers to a machine with distinct images stating number in a given image. Running algorithms over this data are also processes of machine learning (ML). Machine recognize patterns and predict labels of new data. By this advanced training, ML models are able to make predictions about unseen data.
Big data is less complex than AI and machine learning. Simply it is a large amount of data of millions of users which contains a huge variety of distinct sources. Big data is used for machine learning and many other purposes. The more variety of data means better accurate results of machine based on these models. Variety is critical, the same type of large volume of data is useless. Big platforms use a large amount of data collected by customers to provide better services. But they make sure that this data is protected but they can’t fully get rid of risks. Privacy is a major concern for the security of user’s data and companies are efforting to secure it under the regulations by authorities. Organizations are taking measures to secure data by making strong privacy policies, strict rules for employees of data collection and providing more choices to users to decide what can be collected.
AI, ML, and big data are distinct but they are interdependent and can’t exist or move further without each other. Researchers predict that one day AI will completely overtake the human load due to the pace of its advancements but eliminating humans is distant because humans are more flexible than machines.