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Generative AI represents a significant advancement in deeplearning and AI development, with some suggesting it’s a move towards developing “ strong AI.” This data is fed into generational models, and there are a few to choose from, each developed to excel at a specific task.
This has led to substantial environmental implications for training and using AI models. OpenAI researchers note that : since 2012, the computing power required to train advanced AI models has doubled every 3.4 Trainium is specifically designed to enhance AI model training and is set to be incorporated into EC2 UltraClusters.
From an operational standpoint, you can embrace foundation model ops (FMOps) and largelanguagemodel ops (LLMOps) to make sure your sustainability efforts are data-driven and scalable. This involves documenting data lineage, data versioning, automating data processing, and monitoring data management costs.
Training complex AI models, particularly deeplearningmodels, requires significant computational power. For instance, training a largelanguagemodel like GPT-4 involves processing vast amounts of data through multiple layers of neural networks.
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