IBM Watsonx

Watsonx is IBM's commercial generative AI and scientific data platform based on cloud. It offers a studio, data store, and governance toolkit. It supports multiple large language models (LLMs) including IBM Granite.

watsonx

Developer(s)	IBM
Initial release	May 9, 2023 (2023-05-09)
Written in	Python
Engine	Multiple large language models (LLMs)
Platform	Cloud computing platforms
Type	Chatbot AI fine-tuning of large language models Generative pre-trained transformer (GPT)
License	Proprietary
Website	www.ibm.com/watsonx

Machine learning and data mining
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Problems Classification Generative model Regression Clustering dimension reduction density estimation Anomaly detection Data Cleaning AutoML Association rules Semantic analysis Structured prediction Feature engineering Feature learning Learning to rank Grammar induction Ontology learning Multimodal learning
Supervised learning (classification • regression) Apprenticeship learning Decision trees Ensembles Bagging Boosting Random forest k-NN Linear regression Naive Bayes Artificial neural networks Logistic regression Perceptron Relevance vector machine (RVM) Support vector machine (SVM)
Clustering BIRCH CURE Hierarchical k-means Fuzzy Expectation–maximization (EM) DBSCAN OPTICS Mean shift
Dimensionality reduction Factor analysis CCA ICA LDA NMF PCA PGD t-SNE SDL
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Reinforcement learning Q-learning SARSA Temporal difference (TD) Multi-agent Self-play
Learning with humans Active learning Crowdsourcing Human-in-the-loop
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Mathematical foundations Kernel machines Bias–variance tradeoff Computational learning theory Empirical risk minimization Occam learning PAC learning Statistical learning VC theory
Machine-learning venues ECML PKDD NeurIPS ICML ICLR IJCAI ML JMLR
Related articles Glossary of artificial intelligence List of datasets for machine-learning research List of datasets in computer vision and image processing Outline of machine learning

The platform is described as an AI tool tailed to companies and a one which can be customized for customers' needs and trained on their confidential data, as client data is said to be not collected by IBM for further training of their models. It is also capable of fine-tuning, an approach which makes training pre-trained models on the newly introduced data possible.

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