Token & cost optimization
2 min · Hacker News
Can Large Language Models Outperform Classical Hyperparameter Optimization Algorithms?
A new benchmark compares LLMs to Bayesian Optimization and random search for tuning machine learning models. Surprisingly, LLMs leverage prior knowledge of typical dataset structures to converge faster on optimal hyperparameter configurations.
Why it matters. You can now use LLM-driven search spaces to optimize code, prompt structures, and ML hyperparameters with fewer trial runs.