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For example, organizations can use generative AI to: Quickly turn mountains of unstructured text into specific and usable document summaries, paving the way for more informed decision-making. Automate tedious, repetitive tasks. Imagine training a generative AImodel on a dataset of only romance novels.
Set the right data foundations As a CEO aiming to use generative AI to achieve sustainability goals, remember that data is your differentiator. From an operational standpoint, you can embrace foundation model ops (FMOps) and large language model ops (LLMOps) to make sure your sustainability efforts are data-driven and scalable.
Generative AI Overview According to McKinsey , Generative AI is “a type of AI that can create new data (text, code, images, video) using patterns it has learned by training on extensive (public) data with machine learning (ML) techniques.” It can automate, enhance, and expedite a wide range of tasks across various functions.
A report in the Japan Times said the nation is expected to face an 11 million shortage of workers by 2040. Industrial and physical AI-based systems are today becoming accelerated by a three computer solution that enables robot AImodel training, testing, and simulation and deployment.
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