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Generative AI use cases for the enterprise

IBM Journey to AI blog

Tools such as Midjourney and ChatGPT are gaining attention for their capabilities in generating realistic images, video and sophisticated, human-like text, extending the limits of AI’s creative potential. Imagine training a generative AI model on a dataset of only romance novels.

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Harnessing Silicon: How In-House Chips Are Shaping the Future of AI

Unite.AI

Why In-house AI Chip Development? Making AI Computing Energy-efficient and Sustainable The current generation of AI chips, which are designed for heavy computational tasks, tend to consume a lot of power , and generate significant heat. This has led to substantial environmental implications for training and using AI models.

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AI’s Growing Power Needs: Tech Industry’s Move Towards Nuclear Power

Unite.AI

AI's Power Consumption Trends and Challenges AI's rapid advancement has led to an exponential increase in computational demands. Training complex AI models, particularly deep learning models, requires significant computational power.

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The executive’s guide to generative AI for sustainability

AWS Machine Learning Blog

Set the right data foundations As a CEO aiming to use generative AI to achieve sustainability goals, remember that data is your differentiator. Purpose-built to handle deep learning models at scale, Inf2 instances are indispensable for deploying ultra-large models while meeting sustainability goals through improved energy efficiency.

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