Unverified50% confidenceFactExact time
Modern large neural networks (such as GPT-4-level models) have hundreds of billions to trillions of parameters, and it is nearly impossible for humans to trace their internal decision-making processes step by step.
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9/2/2026
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UnverifiedGPT系列、LLaMA等大语言模型参数量级已达数千亿，内部决策路径几乎无法用人类可理解的语言完整描述73% similarUnverifiedGPT-4-level large language models have hundreds of billions of parameters and require billions of floating-point operations on high-end GPUs (such as NVIDIA A100/H100) for each response.72% similarUnverifiedEach inference requires loading model weights into GPU memory and generating responses token by token; GPT-4-level model parameter counts are typically on the order of hundreds of billions.72% similarUnverifiedGPT-3拥有1750亿参数，用进化策略进行有效采样所需的函数评估次数随参数维度呈指数级增长（维度灾难）70% similarVerifiedGPT-4采用混合专家（MoE）架构，估计总参数量达1.8万亿，每次推理实际激活参数约为总量的1/869% similar
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