用 Jev 设想游戏与交易中的高频决策

Hao Kang @Mlsys_HaoKang原推发布于 2026.09.20

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A year ago, when I tried using small Qwen models to play games like Street Fighter, I realized that efficiency was a major bottleneck. Most interactions were actually prefill-bound: you don’t need much CoT or long decoding, but you do need fast decisions. Now Jev makes me think this direction has real potential. LLMs, or what I personally think of as LAMs (Language Action Models), could eventually power much higher-frequency decision making in gaming, trading, and even robotics. Here is an example of Qwen model one year ago.

这条是引用着另一条写的：「ChatGPT 联合发明人发布新模型 Jev」