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Anomaly detection in machine learning: Finding outliers for optimization of business functions

IBM Big Data Hub

Supervised learning Supervised learning techniques use real-world input and output data to detect anomalies. These types of anomaly detection systems require a data analyst to label data points as either normal or abnormal to be used as training data.

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Data science vs data analytics: Unpacking the differences

IBM Big Data Hub

Data science is an area of expertise that combines many disciplines such as mathematics, computer science, software engineering and statistics. It focuses on data collection and management of large-scale structured and unstructured data for various academic and business applications.

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The most valuable AI use cases for business

IBM Big Data Hub

But right now, pure AI can be programmed for many tasks that require thought and intelligence , as long as that intelligence can be gathered digitally and used to train an AI system. Generative AI can produce high-quality text, images and other content based on the data used for training.

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Data science vs. machine learning: What’s the difference?

IBM Big Data Hub

Data science use cases Data science is widely used in industry and government, where it helps drive profits, innovate products and services, improve infrastructure and public systems and more. A manufacturer developed powerful, 3D-printed sensors to guide driverless vehicles.

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GUEST ESSAY: Recalibrating critical infrastructure security in the wake of evolving threats

The Last Watchdog

in different industries, including energy, manufacturing, and healthcare. However, security experts are trained to identify these issues and therefore can ensure that the software is vulnerability-free and follows good cybersecurity best practices. Organizations must move from a “trust but verify” mindset to a Zero Trust approach.

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Building AI for business: IBM’s Granite foundation models

IBM Big Data Hub

And just as granite is a strong, multipurpose material with many uses in construction and manufacturing, so we at IBM believe these Granite models will deliver enduring value to your business. The Granite family of models is no different, and so we trained them on a variety of datasets — totaling 7 TB before pre-processing, 2.4

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How foundation models and data stores unlock the business potential of generative AI

IBM Big Data Hub

Foundation models: The driving force behind generative AI Also known as a transformer, a foundation model is an AI algorithm trained on vast amounts of broad data. A specific kind of foundation model known as a large language model (LLM) is trained on vast amounts of text data for NLP tasks. All watsonx.ai