开发者用 Jev 构想机器人实时反应层
AgentRuntime 作者把 Jev 视为「人工神经系统」中的快速反应层：大模型负责推理规划，Jev 负责急停、闪避等毫秒级决策。
Jev from TypeSafe AI caught my attention for a different reason than most of the examples I’ve seen. Classification, routing and scoring are useful, but the bigger idea is what a fast decision model could mean for systems that need to react in real time. While building AgentRuntime, we’ve already been thinking in this direction. I don’t think the path to AGI is simply making the LLM bigger and letting it control everything. Imagine a robot. The large model can understand the goal, reason about the environment and change the plan. But if something suddenly moves into its path, it needs a much faster layer to decide: stop, dodge, turn, continue. Then below that, you still need deterministic control and safety. So instead of one model doing everything, you get something closer to an artificial nervous system: fast reactions + slower reasoning + hard safety That is why Jev is interesting to me. Not just as a classifier, but as an example of a different kind of intelligence designed for a different job. And that aligns strongly with how we think about AgentRuntime: different models, rules, tools and humans working together at different layers, instead of one LLM owning the whole system. Jev is still early, and TypeSafe hasn’t positioned it as an edge robotics model today. But the direction is very interesting. Made a short visual of what I mean below. #AI #Jev #EdgeAI #Robotics #AgenticAI #AgentRuntime
这条是引用着另一条写的：「ChatGPT 联合发明人发布新模型 Jev」