Remove 2040 Remove Automation Remove Prompt Engineering
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Generative AI use cases for the enterprise

IBM Journey to AI blog

Automate tedious, repetitive tasks. The quality of outputs depends heavily on training data, adjusting the model’s parameters and prompt engineering, so responsible data sourcing and bias mitigation are crucial. The result will be unusable if a user prompts the model to write a factual news article.

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The executive’s guide to generative AI for sustainability

AWS Machine Learning Blog

This involves documenting data lineage, data versioning, automating data processing, and monitoring data management costs. Figure 5 offers an overview on generative AI modalities and optimization strategies, including prompt engineering , Retrieval Augmented Generation , and fine-tuning or continued pre-training.

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