Data Science

What is Artificial Intelligence?

What is Artificial Intelligence?

AI is a broad branch of computer science. The goal of AI is to create systems that function intelligently and independently.

Artificial intelligence for people in a hurry- video

The easiest way to think about artificial intelligence is in the context of a human.

Humans can….

  • Speak and listen and communicate through language. This is the field of Speech Recognition. Much of speech recognition is statistically based and hence is called Statistical Learning
  • Write and read text in a language. This is the field of Natural Language Processing (NLP
  • Human can see through their eyes and process what they see. This is the field of Computer Vision. Computer vision falls under the symbolic way for computers to process information. Humans can recognize a scene around around them, through their eyes that create images of that world. This field of Image Processing (not directly related to AI) is required for computer vision
  • Humans can understand their environment and move around fluidly. This is the field of Robotics

  • Humans have the ability to see patterns, such as grouping of like objects. This is the field of Pattern Recognition. Machines are even better at pattern recognition because they can use more data and dimensions of data. This is the field of Machine Learning.
  • The human brain is a network of neurons, used to learn things. If we can replicate the structure and function of the human brain we might be able to attain cognitive abilities in machines. This is the field of Neural Networks. If these networks are more complex and deeper and we use those to learn complex things, that is the field of Deep Learning. There are different types of deep learning in machines, which are essentially different techniques to replicate what the human brain does.

  • If we get the network to scan images from left to right, top to bottom it's a Convolution Neural Network (CNN). A CNN is used to recognize objects in a scene. This is how computer vision fits in, and Object Recognition is accomplished through AI.
  • Humans can remember the past-like what you had for breakfast yesterday. We are able to get a neural network to remember a limited past. This is a Recurrent Neural Network (RNN)

We can see there are 2 ways AI works; Symbolic based, and data based, called Machine Learning. For machine learning we need to feed the machine lots of data before it can learn. e.g. If you had lots of data for sales vs advertising spend you can plot that data to see some kind of a pattern. If the machine can learn this pattern then it can make predictions based on what has been learnt.

While 1, 2 or even 3 dimensions is easy for humans to understand and learn, a machine can learn in many more dimensions. Thats why machines can look at lots of high dimensions data and determine patterns. Once patterns are learnt predications can be made that humans can't even come close to.

We can use all these machine learning techniques to do 1 of 2 things.

Classification or Prediction

e.g. When using information about customers, and assigning new customers to a group like young adults you are classifying that customer. If using data to predict if a customer is  likely to defect to a competitor you are obviously making a prediction, which is likely to be derived from a learning algorithm.

If you train an algorithm with data that also contains the answer it's called Supervised Learning.

e.g. If you trained a machine to recognize your friends by name you would need to identify them for the computer.

If you train an algorithm with data where you want the computer figure out the patterns then it's Unsupervised Learning.

e.g. You might want to feed the computer information about celestial objects in the universe and expect the machine to derive patterns in the data by itself.

If you give any algorithm a goal and expect the machine, through trial and error to achieve that goal it's called Reinforcement learning.

e.g. A robots' attempt to crawl over a wall until it succeeds.

44% of larger organizations fear they'll lose out to startups if they're too slow to evaluate and deploy Al in their organization

- Microsoft Digital Research

It is expected that the global artificial intelligence market will grow at a compound annual growth rate of 42.2% from 2020 to 2027 to reach USD 733.6 billion by the end of 2027

-Insights from Grandview Research

Augmented intelligence?

Unlike the term artificial intelligence, 'augmented intelligence ' has a neutral connotation. A growing number of businesses realize that they can grow faster with an insights driven approach that utilizes the strengths of both the human, and the technological solution. This is where our interests lie and our focus - to democratize data science enabling all companies to become insight driven.

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