Artificial Intelligence — A Technology beyond human control

Original article was published by Shruti Devang on Artificial Intelligence on Medium


Artificial Intelligence — A Technology beyond human control

I started building an interest in reading some enthralling blogs on various topics. among those, the most interesting topic which I came across was about AI and it’s applications in various industries.

That was an absolute kick-start for me to dive deep into the Tech ocean. I feel so fascinated with the idea of machines learning the human mind to make them think and behave as humans do! To improve problem-solving skills and apply them in the areas where human intervention is limited.

What exactly is AI Technology

As soon as you hear about Artificial Intelligence, you start imagining a robot, isn’t it? Sophia, an AI humanoid robot developed by Hong Kong-based company Hanson Robotics is the best example.

Now, picture a scenario of Sophia organising your closet or serving your favourite food which makes your day super easy. Well, these robots or machines are the outcomes of Artificial intelligence. These are not just ordinary machines that perform the given tasks, but it’s way beyond your imagination!

The reason why it’s been called as artificial intelligence is that they have artificially incorporated with human-like intelligence to perform the tasks which we do! And it is built using complex algorithms and mathematical functions.

Artificial Intelligence is undoubtedly a game-changer, as it is being used in different industries to solve the real-world problems such as Health Industry, Agriculture, Social Media, Banking, Finance, Gaming, Space Exploration, Automation Industry and more. It’s a boon to the tech world which is absolutely priceless.

Components of AI

  • Generalised learning: The ability to react appropriately to a new situation.
  • Reasoning: The ability to draw the inference based on the circumstances.
  • Problem Solving: The ability to find the solution for a problem by using the given input.

These are the main three key components that make the robots artificially intelligent. To cut a long story short, AI provides machines, the capability of learning, reasoning and providing solutions.

Categories of AI:

AI is broadly classified into two categories:

  1. Weak AI or Neural AI — It focuses only on one particular task.

The best example of weak AI is Alexa echo dot. When you ask Alexa to play your favourite song it recognises your speech and picks up the keywords “play” and “your favourite song” and it plays the song by running the program that has been trained to different variants and it cannot answer to a question it is not trained to answer.

2.Strong AI: These are the robots that only exist in fiction as of now. The best example of strong AI is Ultron from Avengers as it’s self-aware and eventually develops emotions. This makes the AI response unpredictable.

Why AI is important?

AI is booming and its gaining popularity in recent years. The reason is, earlier we had a very small amount of data and it was not sufficient to predict the accurate result. But, now there is a humongous amount of data being generated.

It has been estimated that about 2.5 quintillion bytes of data are produced every day. The world is seeing an exponential increase in generating data, and it’s been forecasted that the size of the data will reach around 463 zettabytes by 2025.

It has been estimated that 70% of businesses are likely to implement AI. This is because traditional business intelligence and analytics methods can’t keep up with the vast amount of data. And hence, there is a huge scope for developing advanced algorithms and high-end computing power and storage to deal with this large amount of data as it gives insights, opportunities, potential and helps to make better choices and decisions about the future.

How does AI work?

AI is a technology which works with a combination of different concepts like Machine Learning and Deep Learning. Machine Learning is a subset of Artificial intelligence, and Deep Learning is a subset of Machine Learning. Quite confusing is it?

The below picture gives you a clear idea about the difference between these concepts.

  1. MACHINE LEARNING

It is an application that facilitates the systems to possess the capability to automatically learn without being explicitly programmed. The system analyses for the data patterns so that it can perform better which results in improving the decision-making capacity.

This application is indeed a boon to understanding various data sets such as language, images, sound, and much more. With the use of machine learning application, it has become possible to figure out the data and make a decision in no time as compared to humans!

2. DEEP LEARNING

Deep learning is a part of machine learning that involves artificial neural networks that learn by processing data. We can say that Artificial neural networks are just like human neural networks in the brain.

This is how exactly it works; Artificial neural networks work together with multiple layers to learn a single output from multiple inputs, the best example is, identifying a face clear image of a face from a mosaic texture of tiles. The machines learn through positive and negative reinforcement of the tasks they carry out, which requires constant processing and reinforcement to progress.

There are other forms of deep learning such as speech recognition, which enables the voice assistant in phones to understand questions like, Siri and Alexa.

AI in a nutshell

At last, I want to conclude that AI is a very diverse topic where each technology includes a different type of working principle and approach. These technologies are undoubtedly a boon which is being used on a large scale right from our day to day activities, healthcare, and in various industries. For me, it’s really amazing to see machines learning and acting like humans! isn’t it wonderful? Please, share your thoughts.