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Digital Twin Use Races Ahead at McLaren Group

CIO Business Intelligence

billion by 2030. and artificial intelligence (AI) and machine learning (ML) technologies. . Predictive analytics can foretell a breakdown before it happens. Modern data analytics spans a range of technologies, from dedicated analytics platforms and databases to deep learning and artificial intelligence (AI).

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The benefits of AI in healthcare

IBM Big Data Hub

According to Statista , the artificial intelligence (AI) healthcare market, valued at $11 billion in 2021, is projected to be worth $187 billion in 2030. One use case example is out of the University of Hawaii, where a research team found that deploying deep learning AI technology can improve breast cancer risk prediction.

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AI in marketing: How to leverage this powerful new technology for your next campaign

IBM Big Data Hub

A recent study by Price Waterhouse Cooper (PwC) estimates that by 2030, artificial intelligence (AI) will generate more than USD 15 trillion for the global economy and boost local economies by as much as 26%. (1) 1) But what about AI’s potential specifically in the field of marketing? What is AI marketing?

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Five machine learning types to know

IBM Big Data Hub

Machine learning (ML) technologies can drive decision-making in virtually all industries, from healthcare to human resources to finance and in myriad use cases, like computer vision , large language models (LLMs), speech recognition, self-driving cars and more. What is machine learning? temperature, salary).

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Conversational AI use cases for enterprises

IBM Big Data Hub

Machine learning (ML) and deep learning (DL) form the foundation of conversational AI development. Predictive analytics integrates with NLP, ML and DL to enhance decision-making capabilities, extract insights, and use historical data to forecast future behavior, preferences and trends. billion by 2030.

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How to choose the best AI platform

IBM Big Data Hub

Artificial intelligence platforms enable individuals to create, evaluate, implement and update machine learning (ML) and deep learning models in a more scalable way. AI platform tools enable knowledge workers to analyze data, formulate predictions and execute tasks with greater speed and precision than they can manually.