2 posts tagged with "safety"

今日焦点：Musk v. Altman 诉讼案第一周庭审爆出惊人细节——Musk 亲自承认 xAI 使用 OpenAI 模型进行知识蒸馏。与此同时，学术界揭示了一个令人警觉的现象：足够强大的 LLM 可以学会"策略性探索"来抵抗 RL 训练，这对 RLHF 的可靠性提出了根本性质疑。

In the early days of the Generative AI explosion, the industry was obsessed with the "Brain"—the Large Language Model (LLM) itself. We measured success by parameter counts, context window sizes, and benchmark scores like MMLU or HumanEval. However, as we cross into 2026, the narrative has shifted fundamentally. We have realized a hard truth: The model is not the product.

A raw model, no matter how intelligent, is like a powerful engine without a chassis, steering wheel, or brakes. In a production environment, an engine alone is a liability. The "Product" is the entire system that ensures the engine moves the vehicle safely to its destination. This realization has given birth to the discipline of Harness Engineering—the orchestration, safety, and orchestration layer that transforms a probabilistic model into a deterministic agentic system.