What is Artificial Intelligence (AI)?
AI is the simulation of human intelligence in machines that are programmed to think and act like humans and mimic their actions. Artificial intelligence is a branch of computer science concerned with building machines capable of performing tasks that require human intelligence.
Norvig and Russell defined the AI as:
- Thinking humanly
- Thinking rationally
- Acting humanly
- Acting rationally
While addressing a crowd at the Japan AI Experience in 2017, DataRobot CEO Jeremy Achin defined AI as:
“AI is a computer system able to perform tasks that ordinarily require human intelligence… Many of these artificial intelligence systems are powered by machine learning, some of them are powered by deep learning and some of them are powered by very boring things like rules.”
There are two categories of AI
1. Narrow AI: Also known as weak AI, is programmed to perform a single task perfectly. Their context and intelligence are very limited.
A few examples of Narrow AI include:
-Image recognition software
-Siri, Alexa, and other personal assistants
2. Artificial General Knowledge: Also known as strong AI, these types of machines have intelligence similar to a human being and can solve any problem.
AI is currently used in:
e-mail filtering: Email services use AI to filter incoming emails. Users can program their spam filters by marking emails as spam and filtering out unwanted emails.
Personalization: Online services use artificial intelligence to personalize and customize the user experience. These services like Netflix, Amazon, Flipkart, and Hotstar use your purchase history and the purchase history of other users to recommend relevant content to the users.
Protection from fraud: Banks use AI to check if there is strange activity on users’ accounts. Unexpected activity can be detected and blocked by the algorithms.
Speech recognition: Smartphones use AI to optimize speech recognition functions. Alexa, Siri, Google Assistant.
Machine learning feeds computer data and uses statistical techniques to help it to learn how to get better at a particular task, without having been specifically programmed for that task, without the need of writing long codes. Machine learning consists of both supervised learning and unsupervised learning
Deep learning is a type of machine learning that runs inputs through neural network architecture similar to the structure of neurons in our minds. The neural networks contain several hidden layers through which the data is processed, allowing the machine to go “deep” in its learning, making connections and weighting input for the best results.
How machines learn:
Machine learning can be categorized into three general types:
1. Supervised learning: For example, pictures of dogs labeled ‘cars’ will help the algorithm identify the rules to classify pictures of ‘cars’.
2. Unsupervised learning: The data fed into the learning algorithm is not labeled, the algorithm is asked to identify patterns in the given data. E.g. the recommendation system of e-commerce like Amazon and Flipkart where the learning algorithm shows similar items often bought together.
3. Reinforcement learning: The algorithm interacts with a dynamic environment and provides feedback in terms of rewards and punishments. It’s like a carrot and stick approach. For E.g. self-driving cars are rewarded to stay on the road.
At NEXT BIG TECHNOLOGY, we provide you with Artificial Intelligence-based services, we integrate AI into our web development, mobile app development, and e-commerce sites to give recommendations to the users, in AI-powered chatbots and integrate them into the websites and the list is endless.