Artificial Intelligence (AI)

Artificial Intelligence uses complex mathematics run on computers and machines to solve problems that could previously only be solved by the human mind

Artificial Narrow Intelligence (ANI)

Where AI is today, it can solve very specific tasks such as
  • Playing Chess
  • Counting the number of objects on a conveyer belt

Artificial General Intelligence (AGI)

The AI has learned concepts it has learned across multiple domains. This is what people do and AI can not do this today!!

Artificial Super Intelligence (ASI)

Going beyond Artificial General Intelligence where the machines learn to communicate with themself and actively drive change independently of humans.

From our respective, the Artificial Super intelligence would be equivalent to a god.

What is Artificial Intelligence today?

Deep learning (DL) vs. Machine Learning (ML)
The levels of artificial intelligence: deep learning, machine learning, artificial intelligence
Source
The terms Deep Learning (DL), Machine Learning (ML), and Artificial Intelligence (AI) tend to be used interchangeably depending on the person and the context. But actually Deep learning is a subfield of Machine Learning and Machine Learning is a subfield of Artificial Intelligence.

Deep Learning (DL)

Deep learning uses something that is called a neural network. The original design of a neural network took inspiration from the connections in the human mind to create a mathematical formulation with a large number of parameters that can be learned to do a specific task.

Machine Learning (ML)

Machine learning uses techniques from Deep Learning, statistics, and other computer algorithms to imitate how humans learn to perform a specific task.

When applied to a specific task, such as image classification where one attempts to teach the computer how to label what is in an image. t can learn how to classify different dog breeds at a superhuman level. But using the same model that is specialized on dog breeds, to predict if it is a cat, dog, or a horse, it would fail spectacularly unless it got retrained for the new task.

Artificial Intelligence (AI)

Machine Learning enables a computer to do a specific task such as detecting if something is in an image. The next level is to use the results and perform decision-making and let it take direct action.

For example, it could be something as simple as on a production line, detecting if there is a defect in what is being produced and discarding the damaged item, this is referred to as defect detection.

Applications for Artificial intelligence

Artificial intelligence is so flexible and powerful that there are very few areas where it can not be applied.

Application areas of Artificial Intelligence AI Machine Learning ML Deep Learning DL

Computer Vision

Use computers to extract meaningful information from images, there are several well-established tasks in this area such as detecting objects and classifying images.

Speech Recognition

The computer learns to understand speech. There are several different subtasks such as directly understanding speech such as Apples Siri known as automatic speech recognition (ASR). Another common task is to simply convert the speech to text.

Fraud detection

Financial institutions and banks commonly use Artificial intelligence to detect suspicious transactions that should be investigated further.

Recommendation engines

An online retailer needs to make relevant product recommendations, here is where Artificial intelligence comes in. Using historical patterns in the user consumption data the AI can come up with the ideal recommendations for effective cross-selling.

Chat bots

The ability to help customers as fast as possible at any time of the day is important for customer satisfaction. That is why chatbots are replacing humans more and more. They can easily answer frequently asked questions such as shipping rates, shipping times, suggested sizes, etc.

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