# Can We Drastically Reduce AI Training Costs?
## Main Takeaways:
– Training Large Language Models (LLMs) involves pre-training on extensive datasets and fine-tuning for specific tasks.
– Pre-training demands significant computational resources, while fine-tuning is more compressible as it adds comparatively less new information to the model.
– This pretrain-finetune paradigm has significantly advanced machine learning, enabling LLMs to excel in various tasks and adapt to specific needs.
### Author’s Take:
The collaboration between MIT, Princeton, and Together AI has brought forth BitDelta, showcasing groundbreaking efficiency in machine learning by reducing AI training costs. This innovative approach holds promise in revolutionizing the realm of artificial intelligence, making advanced models more accessible and cost-effective for diverse applications.
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