dailyai.report

A theoretical framework posits that perfect data compression is equivalent to perfect prediction. This link suggests that LLMs function as compressors by minimizing entropy during training. Researchers argue that scaling laws emerge from this mathematical relationship. Practitioners can use these insights to optimize tokenization and reduce inference costs in large-scale model deployments.