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  2. Artificial intelligence - Wikipedia

    en.wikipedia.org/wiki/Artificial_intelligence

    Artificial intelligence (AI), in its broadest sense, is intelligence exhibited by machines, particularly computer systems.It is a field of research in computer science that develops and studies methods and software that enable machines to perceive their environment and use learning and intelligence to take actions that maximize their chances of achieving defined goals. [1]

  3. Machine learning - Wikipedia

    en.wikipedia.org/wiki/Machine_learning

    t. e. Machine learning ( ML) is a field of study in artificial intelligence concerned with the development and study of statistical algorithms that can learn from data and generalize to unseen data and thus perform tasks without explicit instructions. [ 1] Recently, artificial neural networks have been able to surpass many previous approaches ...

  4. Neural network (machine learning) - Wikipedia

    en.wikipedia.org/wiki/Neural_network_(machine...

    An artificial neural network is an interconnected group of nodes, inspired by a simplification of neuronsin a brain. Here, each circular node represents an artificial neuronand an arrow represents a connection from the output of one artificial neuron to the input of another. Part of a series on. Machine learning.

  5. Age of AI: Everything you need to know about artificial ...

    techcrunch.com/2023/08/04/age-of-ai-everything...

    Artificial intelligence, also called machine learning, is a kind of software system based on neural networks, a technique that was actually pioneered decades ago but very recently has blossomed ...

  6. Wednesday, OpenAI CEO Sam Altman spoke with the WSJ, saying OpenAI has not started training GPT-5.Altman also noted that the company has long given priority to safety in development and spent more ...

  7. Training, validation, and test data sets - Wikipedia

    en.wikipedia.org/wiki/Training,_validation,_and...

    In particular, three data sets are commonly used in different stages of the creation of the model: training, validation, and test sets. The model is initially fit on a training data set, [ 3] which is a set of examples used to fit the parameters (e.g. weights of connections between neurons in artificial neural networks) of the model. [ 4]

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