We wanted a scenario where, say, 5 well-placed border points could efficiently represent an area with 5,000 internal points and 10,000 road edges. This would reduce those 10,000 edges to just 5*4/2 = 10 shortcuts for routing through that cluster at a high level – an incredible 1:1000 point ratio and a 30x reduction in edges to consider for the high-level path!
Not allowing the agent to access the Internet, nor any other compiler source code, was certainly the right call. Less understandable is the almost-zero steering principle, but this is coherent with a certain kind of experiment, if the goal was showcasing the completely autonomous writing of a large project. Yet, we all know how this is not how coding agents are used in practice, most of the time. Who uses coding agents extensively knows very well how, even never touching the code, a few hits here and there completely changes the quality of the result.
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Nano Banana Pro could already generate images so realistic, it’s almost impossible to tell that they were AI-generated. Google even had to limit its use due to high demand. Whether Nano Banana 2 can generate images that are markedly better than what Pro could create — and whether we could still tell if an image was made by AI — remains to be seen. The new model will replace Nano Banana Pro in the Gemini app, but Google AI Pro and Ultra subscribers will retain access to Nano Banana Pro for specialized tasks. It will also be the default model in Search for AI Mode and Lens, as well as in Google’s Flow AI creative studio.。业内人士推荐下载安装 谷歌浏览器 开启极速安全的 上网之旅。作为进阶阅读
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