Artificial intelligence (AI) is the branch of computer science that builds systems able to perform tasks, such as recognizing patterns, making predictions, or generating text and images, that have traditionally required human intelligence. The Organisation for Economic Co-operation and Development (OECD) defines an AI system more precisely as “a machine-based system that, for explicit or
Artificial intelligence (AI) is the branch of computer science that builds systems able to learn from data and perform tasks requiring human judgment.
Computer vision is the field of artificial intelligence focused on enabling computers to interpret and understand visual information from the world, including photographs, video, and live camera feeds. The goal is to replicate, and in some narrow tasks exceed, the remarkable ease with which human vision identifies objects, judges distances, and makes sense of a
The field of artificial intelligence focused on enabling computers to interpret and understand visual information such as images and video.
Deep learning is a method of machine learning in which computer models with many processing layers learn to represent data at several levels of abstraction. It has improved results in speech recognition, visual object recognition and object detection, as well as in areas such as drug discovery and genomics. History of deep learning Deep learning
A machine learning method that uses neural networks with many layers to learn increasingly abstract representations of data such as images, speech and text.
Generative AI refers to artificial intelligence systems that create new content, including text, images, audio, video, and computer code, rather than simply analyzing or classifying existing data. Where an earlier generation of AI systems excelled mainly at recognizing patterns, such as identifying what object appears in a photo or whether an email is spam, generative
Artificial intelligence systems that create new content, such as text, images, audio, or code, rather than only analyzing existing data.
In simple terms In machine learning, inference is the stage where a finished model is put to work. New data goes in, and a prediction, label or answer comes out. Training is the other half of the story. NIST describes the training stage as the phase in which a model is learned from labeled data,
In machine learning, inference is the stage where a trained model is run on new data to produce a prediction or answer.
In simple terms A large language model is a machine learning system trained on enormous amounts of text. Its core job is narrow: given some text, work out what is most likely to come next. Do that over and over and the model writes sentences, answers questions or drafts code. How it works Text is
A large language model is a system trained on huge amounts of text to predict what text comes next, one token at a time.
In simple terms Machine learning builds computer systems that adapt and learn from data in order to get more accurate. That is close to the definition NIST uses. The contrast is with ordinary software, where a person writes the rules. In machine learning the rules are worked out from examples. How it works Start with
Machine learning is the branch of computing in which systems improve at a task by finding patterns in data instead of following hand-written rules.
Natural language processing, often abbreviated NLP, is the branch of artificial intelligence focused on enabling computers to understand, interpret, and generate human language in both written and spoken form. Human language is full of ambiguity, context-dependence, idioms, and shifting meaning that make it dramatically harder for a computer to process than structured data like numbers
The branch of artificial intelligence focused on enabling computers to understand, interpret, and generate human language.
A neural network is a type of computing system loosely inspired by the structure of the brain, built from layers of simple connected units called neurons that each take in numbers, apply a mathematical transformation, and pass the result along to the next layer. Although the biological comparison is loose, the basic idea carries over
A computing system built from layers of connected units that learn to recognize patterns in data by adjusting connection weights.
A voice assistant is a software program that listens to spoken requests, works out what the user wants and responds by speaking or by carrying out a task such as setting a timer, answering a question or controlling a device. Voice assistants run on smartphones, smart speakers, cars and televisions. They combine speech recognition, language
Software that understands spoken requests and answers by voice or acts on them, such as setting timers, answering questions or controlling devices.