我是 flutter_gemma 的创建者和维护者——这是一个用于在移动设备上本地运行 LLM 的 Flutter 插件。我越是使用设备端 AI,就越发确信:未来属于本地代理,或者至少是混合代理。
Offline navigation is a lifeline for travelers, adventurers, and everyday commuters. We demand speed, accuracy, and the flexibility to tailor routes to our specific needs. For years, OsmAnd has championed powerful, feature-rich offline maps that fit in your pocket. But as maps grew more detailed and user demands for complex routing increased, our trusty A* algorithm, despite its flexibility, started hitting a performance wall. How could we deliver a 100x speed boost without bloating map sizes or sacrificing the deep customization our users love?
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It’s a bit of a double-edged sword. AI is incredibly accurate with numbers, but it’s terrible at catching human mistakes. If a recipe submitted has a typo that says '1 cup of salt' instead of a teaspoon, the AI might just roll with it, and it is up to us to catch it.
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