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2. Machine learning - Wikipedia

   en.wikipedia.org/wiki/Machine_learning

   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]

3. Artificial intelligence - Wikipedia

   en.wikipedia.org/wiki/Artificial_intelligence

   Generative artificial intelligence (generative AI, GenAI, [165] or GAI) is a subset of artificial intelligence that uses generative models to produce text, images, videos, or other forms of data. [ 166 ] [ 167 ] [ 168 ] These models learn the underlying patterns and structures of their training data and use them to produce new data [ 169 ...

4. Applications of artificial intelligence - Wikipedia

   en.wikipedia.org/wiki/Applications_of_artificial...

   Artificial intelligence is used in astronomy to analyze increasing amounts of available data [160] [161] and applications, mainly for "classification, regression, clustering, forecasting, generation, discovery, and the development of new scientific insights" for example for discovering exoplanets, forecasting solar activity, and distinguishing ...

5. List of artificial intelligence projects - Wikipedia

   en.wikipedia.org/wiki/List_of_artificial...

   15.ai, a real-time artificial intelligence text-to-speech tool developed by an anonymous researcher from MIT. [70] Amazon Polly, a speech synthesis software by Amazon. [71] Festival Speech Synthesis System, a general multi-lingual speech synthesis system developed at the Centre for Speech Technology Research (CSTR) at the University of ...

6. Transformer (deep learning architecture) - Wikipedia

   en.wikipedia.org/wiki/Transformer_(deep_learning...

   For many years, sequence modelling and generation was done by using plain recurrent neural networks (RNNs). A well-cited early example was the Elman network (1990). In theory, the information from one token can propagate arbitrarily far down the sequence, but in practice the vanishing-gradient problem leaves the model's state at the end of a long sentence without precise, extractable ...

7. Timeline of machine learning - Wikipedia

   en.wikipedia.org/wiki/Timeline_of_machine_learning

   Generative AI leads to revolutionary models, creating a proliferation of foundation models both proprietary and open source, notably enabling products such as ChatGPT (text-based) and Stable Diffusion (image based). Machine learning and AI enter the wider public consciousness.

8. Active learning (machine learning) - Wikipedia

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

   This type of iterative supervised learning is called active learning. Since the learner chooses the examples, the number of examples to learn a concept can often be much lower than the number required in normal supervised learning. With this approach, there is a risk that the algorithm is overwhelmed by uninformative examples.

9. Feature (machine learning) - Wikipedia

   en.wikipedia.org/wiki/Feature_(machine_learning)

   Examples of categorical features include gender, color, and zip code. Categorical features typically need to be converted to numerical features before they can be used in machine learning algorithms. This can be done using a variety of techniques, such as one-hot encoding, label encoding, and ordinal encoding.