DeepSeek's recent launch of the R1 model, which combines performance with low costs, has excited the tech community. This model is part of a trend towards distillation in AI training, where smaller, faster models learn from larger ones. Meanwhile, researchers from Stanford and the University of Washington successfully developed the s1 model on a limited budget, highlighting the viability of creating competitive AI systems. They utilized strategic data curation and a compact dataset to fine-tune the model, significantly enhancing its performance in math problem-solving without incurring high costs.
DeepSeek's R1 model showcases the potential of distillation, creating efficient AI with high intelligence while emphasizing the challenges of protecting intellectual property in AI training.
The budget-friendly s1 model developed by researchers outperforms existing competitors by leveraging a compact dataset, achieving remarkable results at a fraction of typical costs.
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