Unverified50% confidenceOpinionExact time
The traditional view holds that Bayesian optimization is only suitable for expensive functions and that algorithm speed does not matter, but problem cost is actually a continuum, from cheap to expensive.
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10/22/2026
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UnverifiedEven with optimizations such as quantization, distillation and caching, the marginal cost of inference remains hard to bring close to zero.74% similarUnverifiedWhen the cost of deviating from the algorithm far exceeds the cost of complying with it, human review exists in name only.74% similarUnverifiedMetaheuristic optimization algorithms generally suffer from high computational overhead, and their search processes are stochastic, meaning convergence results may vary across runs.74% similarUnverified优化算法设计中存在收敛速度、稳定性与内存开销之间的持续权衡72% similarVerifiedIf a low-cost model has insufficient reasoning capability, it leads to more retry rounds, and the hidden costs of accumulated failed retries may exceed those of a high-cost, high-efficiency solution (the paradox of "cheap models actually being more expensive").72% similar
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