Artificial intelligence has been a buzzing technology in the world for quite some time now. Initially only heard of in movies and sci-fi stories, AI is no longer a fiction. It is real and it is here to stay. Like all other developing technologies, AI too is going through new advancements with every passing day. Allied technologies of machine learning and deep learning are further bringing this remarkable invention closer to reality. Used interchangeably with artificial intelligence, machine learning, and deep learning are in fact one step ahead of AI.

People who are less familiar with the technical side of these technologies can hardly differentiate between the three concepts. But in reality, these are three different facets of the same concept. Let first have a look at them one by one.

Artificial intelligence or AI:

The performance of tasks by machines that are characteristics of human beings in an intelligent manner is known as artificial intelligence. The tasks generally performed by AI machines include planning of various activities and processes, understanding different languages, recognition of objects and patterns, distinguishing sounds, learning of new information and solving problems of various types.

Artificial intelligence machines can be categorized into two classes. The first one would be able to perform various different types of humanly characterized activities. This is the general AI machine. However, the second form of AI machines includes the narrowly specialized ones that can only perform one specialized task.

In terms of technology, AI is a broad discipline that attempts to make computers and machines to think like human beings. It attempts to create a stimulation of activities that human do. In doing so, AI aims to enhance the speed and quality of problem-solving processes performed by machines and computers.

Machine Learning:

Machine learning is one step further to the development of AI machines. Very simply put, it is a method of acquiring AI technology in machines. It is the ability of a machine to learn new things without the need for explicit programming. Machine learning is a requirement for stable and long-term sustainability of AI. Without machine learning, AI would become a huge, time consuming and cumbersome task that would require large amounts of code development and complex programming.

So, in other words, machine learning is programming a computer to learn. It is the training of an algorithm for learning like humans. It requires entering large amounts of information, codes, and data into the machine program so that its algorithm can make adjustments on its own.

For clarity you can consider the following example:

Computer vision is used for recognizing various images and pictures. By improving the vision, we can enhance the computer’s image recognition capabilities. For this purpose, you can collect millions of pictures and let humans tag them. This may include pictures with dogs or without them. When you feed and train your algorithm to tag similar pictures like humans, the computer will become learned about what a dog will look like. This means that instead of programming machines with codes to accomplish various tasks and goals, you give them huge amounts of data and information as a sample to come up with learning and patterns recognition themselves.

Throughout history, scientists have used many different ways to create superior AI technology. But the most successful and long-lasting have been through machine learning.

Deep learning:

Now that we have found out about AI and its relationship with machine learning, the next important concept to understand is deep learning. It is one of the approaches towards achieving machine learning for AI. There are other ways of achieving machine learning capabilities as well but deep learning is the most effective one.

The very concept of deep learning is an inspiration from the human brain. It tries to replicate the structure and functioning of the brain units called neurons. In order to create an interconnected network of brain neurons, scientists have come up with ANN or artificial neural networks. These are computer algorithms that try to copy the human brain and its working. They help in the classification of information and data in a manner to similar to that of humans.

Talking about artificial intelligence ANNs are the major breakthrough in AI development and machine learning. Although there are many facets of these ANNs, deep learning is the most advanced one. It is based on probability. It requires being fed with a large set of data and information that can be used by the computer to make critical decisions, produce statements and present forecasts about various situations.

In the example of the dog pictures, deep learning allows the machine to be 75% confident that there is a dog in the picture. The level of probability will enhance if the requirement is to point out just an animal in the picture. To further enhance the accuracy, the users let the computer know whether the answers were correct or wrong. This improves future answers and solutions.

All three of the described technologies are interrelated with each other. Machine learning and deep learning are building blocks for a superior AI system.

Changing the world through AI systems:

Starting as a science fiction concept, artificial intelligence and its related technologies have now become a global technological phenomenon. The products and services based on AI systems are now becoming part of our daily lives and work places. The main focus of these systems is on the automation and optimization of various processes and activities in the real world. They are not just cool gadgets and devices to enjoy but real-time machines that can tremendously increase productivity and efficiency of human beings. AI systems can be utilized to actually solve big problems and change the way the world works.

AI systems and products cannot be restricted to just one industry or facet of society. It is a large technology that can bring improvement in almost all walks of life. From healthcare to education, from business to national security everything in the world can be transformed in a positive manner using this amazing technology. The benefits of using AI machines with deep learning capabilities are immense and limitless. Integrated with existing technologies, these machines can augment human skills and intelligence to conquer the impossible.

Many critics believe that AI can lead to job reduction and human replacement. But this is not true. The idea behind the AI application is to augment the human thinking and working rather than replacing humans. Computers that can overpower the human thinking cannot be created. With the most complexly interconnected and superior neural brain system, humans have the most sophisticated inbuilt computer in the world. AI can be used for complementing this thought process to come up with better ideas and solutions.

Changing work through AI:

Let us look at the various ways that AI, machine learning and deep learning are impacting and changing the world.

  • Healthcare and Medicine:

 

Precision medicine is a growing AI and machine learning trend in the industry. It is an approach towards the treatment of various diseases and how to prevent them. It encompasses the information from the variability of human genetics, the environments they live in and their individual lifestyles. It is a personalized approach towards medicines where healthcare providers will be able to choose the exact treatment that may be suitable for each different patient. It will use the information and data of large sets of patients and divide into groups based on various genetic and medical variations.

Ayasdi is one such AI algorithm using a system that focuses on deep learning for enabling doctors and healthcare providers to better analyze large amounts of medical data. IBM and Enlitic are utilizing similar systems for the detection of tumors and upgradation of radiological systems.

  • Financial Services:

 

There is a number of applications of AI systems in financial services and banks. They can and are actually transforming the way banks work. Examples of these applications include anti-money laundering detection patterns. Also known as AML Pattern Detection it allows bankers to detect any money laundering patterns in financial transactions automatically. It is a faster and more accurate way of detecting money transfer patterns.

Chatbots based on AI and deep learning are already used in a number of banking systems to provide nonstop customer services to clients. These are automated chat systems that provide answers to queries and collect data without human interaction. Chatbots provided by RosponseAI is best known for the purpose. They are fast and accurate and provide the best solution to banks for their customer service needs.

  • Education systems:

 

The AI, machine learning, and deep learning technologies can be very beneficial for the education sector as well. AI software like Gooru in schools has reduced the need for keeping huge logs on students’ performance and how well they are absorbing in various concepts.

Other applications of AI and machine learning in education systems include student performance prediction, improved organization of curriculum and academic contents, matched partnerships of students and teachers. Above all, it can eliminate favoritism and lead to the unbiased grading of students. All these and many more AI based systems are being developed to bring about positive improvements in the education sector and institutions.

  • Manufacturing and production:

 

Artificial intelligence and machine learning can bring about automation in the manufacturing sector. This, in turn, can increase the productivity, reduce manual errors, decrease production costs and redirect human skills and intelligence to more productive jobs and tasks.

By implementation of AI systems, companies can reduce operational and maintenance costs by carrying out predictive maintenance. GE’s factory in India is called the brilliant factory because of its AI system called Predix.

Other benefits of using AI and deep learning in manufacturing include consumer-oriented products, improvement in human-robot collaboration, high level of quality controls and upgraded supply chain management.

  • Retailing Sector:

 

Like the banking and other service sectors, AI robots and machines can be a great way to provide customer services to clients. Whether the chatbots are providing information to new clients or making actual sales, machine learning and deep learning can be very useful. Even if the sales are not made, these AI machines can collect valuable information and data that can be further used to make marketing improvements.

Online businesses like Amazon are the best examples of these AI-powered retail businesses. They can provide state of the art customer experiences throughout the day without any enhanced production costs and increased needs for human resources.

  • Cybersecurity:

 

Cybercrime is increasing very fast and there is an ever-growing need for cybersecurity. With such a vast network and millions of users from across the globe, coping up with the huge number of alerts can be a difficult task. The deep learning and automation capabilities of AI-powered systems reduce the burden through cost reduction, enhanced safety, and more effectiveness. Examples of such systems already in the market include Cylance, Deep instinct and SiftScience.

  • Agriculture sector:

 

AI-powered precision farming allows farmers to increase efficiency by reducing wastage and enhancing production while at the same time caring for the atmosphere. AI systems like John Deere AutoTrac ensure that large agricultural machines are planting crops with uniformity and accuracy. It reduces overlapping of the process and eliminates redundancy of work.

Caintus is another such deep learning mechanism that is used in cattle farming to recognize cows from their face. This ensures that large herds of animals can be managed in a better way without the need of many people.

Wrapping up:

These were only a few examples of how artificial intelligence, machine learning, and deep learning are being used in various sectors of the world. The utility and benefits of these high powered technologies are limitless. Used with human integration, they can transform the way the world works. Already we use and see many of the AI enabled gadgets and devices in our homes and offices on daily. They make our lives easier and more effective through their learning capabilities. But there is surely more to come ahead.

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