Introduction
Artificial intelligence has been around for decades, but it’s only recently become really interesting. You can use AI in many different ways, including helping doctors diagnose diseases and even creating robots that can do household chores like vacuuming or cooking meals.
What is AI?
AI is a branch of computer science that uses principles from machine learning to make computers intelligent. It encompasses many different subdisciplines, including neural networks and fuzzy logic. AI is sometimes called “the science behind the science fiction.”
The AI field was born in 1950 when John McCarthy coined the word “artificial intelligence” at Dartmouth College as he was trying to create an effective way for computers to learn without direct human supervision. The term has since been used frequently throughout popular culture—for example, movies like 2001: A Space Odyssey have included references to AI (” HAL 9000″) while TV shows such as Star Trek use it regularly as well (TNG’s Data).
AI is a branch of computer science that uses principles from machine learning to make computers intelligent. It encompasses many different subdisciplines, including neural networks and fuzzy logic. AI is sometimes called “the science behind the science fiction.”
There are two different kinds of artificial intelligence: deep learning and reinforcement learning.
Deep learning is a branch of machine learning that uses neural networks to learn patterns in data. Reinforcement learning is another branch, which uses rewards or punishments to guide behavior. These techniques have been used for decades in games like chess and Go, but recently they’ve become more common in applications such as speech recognition (Google) and self-driving cars (Tesla).
Reinforcement learning is an area of Machine Learning. It is about taking suitable action to maximize reward in a particular situation. It is employed by various software and machines to find the best possible behavior or path it should take in a specific situation. Reinforcement learning differs from supervised learning in a way that in supervised learning the training data has the answer key with it so the model is trained with the correct answer itself whereas in reinforcement learning, there is no answer, but the reinforcement agent decides what to do to perform the given task. In the absence of a training dataset, it is bound to learn from its experience.
What can AI do?
AI can help you solve problems.
AI can help you make better decisions.
AI can help you make better products.
AI can help you make better services.
AI can also be used to create experiences that are more engaging and engaging in a way that humans just don’t do well yet (like, say, human-computer interaction).