We are living in a world where computers and machines are interacting with each other without human interaction in between. Self-driving cars are racing on the roads, handy devices such as Alexa, and Siri is understanding human commands and performing the tasks with zero mistakes. Technological advancements made things simple, accurate, transparent, and more importantly fast.
We have witnessed many technologies in recent times, and all most all of them have changed the way we live. It has been a while, and some words have created a trend in the tech world, those are Artificial Intelligence, Machine Learning, and Analytics. These technologies have brought significant change in every field. The terms Artificial intelligence, and Machine Learning both are interchangeable. Machine learning is the subset of the Artificial intelligence, and it depicts significant part of AI.
Artificial intelligence is a process of developing systems to behave according to the situations and ability to think like a human. Machine Learning is the process of pattern recognition and computational learning theory which gives computers ability to perform without explicitly programming, and Analytics is nothing but computing the raw data and make interpretations out of it for the decision-making process which enables the higher authority to take a right decision which would help in the growth of an organization.
When we put Artificial Intelligence, Machine Learning, and Analytics all together, we would get an acronym called AIMLA. The AIMLA is revolutionizing the industry by introducing automation, which leads to the elimination of repeated works, and the final output would be the manufacturing of quality goods and services in less time, at low cost, with an active delivery pattern, and Quick response to customer Queries. AIMLA has created an innovation in every industry and which results in industry development and thereby contribution to the economy, and social development.
Driving factors of AI
With the enormous progress in technology leads to use of AI to mimic the human activities and decision making process by machines in the more humanoid way. According to McKinsey the below are the three key driving factors of AI
- Developments in Machine Learning and Deep learning
- Availability of Scalable hyperspace through the cloud
- Generation of a vast amount of data that can be used to train IOT
The above are the key factors which are helping in the development of the AI and in spreading it to all corners of the work environment.
AI, Machine Learning, and Neural networks
Artificial intelligence makes devices act intelligently like human beings. According to Arthur Samuel, American pioneer in the field of AI, and computer gaming coined the word Machine learning in 1959 and expressed that in future it might be possible to program computers to learn themselves with little or no interaction of the human. Now the technological scientists have developed the programs to think like human beings, connect them to the internet and give all access to the information. Then the data is classified in the neural networks to recognize same way as the human brain does. A neural network is a system developed to understand the information and label them according to the components it contains.
Machine learning applications can do the following tasks such as Image Recognition, speech recognition, medical diagnosis, statistical arbitrage, learning association, classification, prediction, extraction, and regression it can do a lot more complicated technical tasks very quickly. Sometimes it can also do the things like playing music according to human commands, and it can analyze the mood of a person whether He or She is happy or not for a particular song if not even it can compose a song on its own which makes listener happy. The above are all possibilities facilitated by the systems based around Neural networks and Machine Learning.
Impact and beyond
We had seen in old science fiction movies that machines used to interact with humans more naturally. When it’s come to reality Technological advancements, and machine learning is enabling computers to communicate with humans more naturally. Another field of AI is the NLP which means Natural Language Processing, and it is also one of the groundbreaking achievements in technology segment. NLP applications attempt to understand the human written, and spoken language, and in return, it communicates with the same natural language. ML is also used to realize different nuances of different styles by systems and learn to respond in a manner which is comprehended.
Combination of Analytics and Artificial Intelligence
The importance of data Analytics has been increasing over the years because of its valuable contribution in taking the right decision at the right time. It helps in analyzing the historical data to predict the future consequences. Artificial intelligence has become more powerful because of the vast amount of data sets, which is life, and blood to the AI. To get massive development in the field of Artificial intelligence, we need more and more data. Data is categorized into two segments one is Quality data, and another one is less quality or sometimes no quality at all. The data must be Qualitative one to implement it in AI. Artificial Intelligence, and Analytics both are redefining the business world in multiple ways and transforming the organizations to the next level of the modern world.
With effective implementation of artificial intelligence and machine learning and Analytics, organizations can plan their future and even can predict the adverse effects early, and they could have a chance to take preventive measures for controlling them. Analytics is the best source to predict the future wants, and needs of the customer through historical data, before even customer knows them.
Conclusion
AI and machine learning have made a significant change in each sector, and soon, we are going to experience AI services in a more humanoid way. These technological advancements are inevitable according to the scientists. Instead of worrying about the automation and fear of losing jobs, people must have to re-skill their skills to be able to perform and get the future jobs. Artificial intelligence, Machine Learning, and Data Analytics all together are going to make a new wave in the technical world. We must be ready to use the disruptive technology soon.
Guest article written by: 
Vinodh Kumar, postgraduate from the Business Administration background. He is currently working as a content contributor for Mindmajix and loves to write tech related niches. Contact Vinod at [email protected] connect to Vinod at LinkedIn and Twitter.