There is a lot of energy right now around sandboxing untrusted code. AI agents generating and executing code, multi-tenant platforms running customer scripts, RL training pipelines evaluating model outputs—basically, you have code you did not write, and you need to run it without letting it compromise the host, other tenants, or itself in unexpected ways.
9月10日——罗永浩吐槽西贝预制菜事件，推荐阅读WPS下载最新地址获取更多信息
The camera modules are the same as last year, but Samsung is aiming to supercharge them with upgrades elsewhere, such as ProScaler image upscaling and an MDNIe chip that's said to greatly improve color precision. There's also a video stabilization feature that tries to keep the horizon level while you're following a moving person or pet, which sounds useful for action shots. The new Object Aware Engine is said to better render skin tones and hair textures to make your selfies look better. Samsung has reworked some AI features too, such as making Now Brief and Auto Eraser compatible with more apps.，详情可参考爱思助手下载最新版本
Around this time, my coworkers were pushing GitHub Copilot within Visual Studio Code as a coding aid, particularly around then-new Claude Sonnet 4.5. For my data science work, Sonnet 4.5 in Copilot was not helpful and tended to create overly verbose Jupyter Notebooks so I was not impressed. However, in November, Google then released Nano Banana Pro which necessitated an immediate update to gemimg for compatibility with the model. After experimenting with Nano Banana Pro, I discovered that the model can create images with arbitrary grids (e.g. 2x2, 3x2) as an extremely practical workflow, so I quickly wrote a spec to implement support and also slice each subimage out of it to save individually. I knew this workflow is relatively simple-but-tedious to implement using Pillow shenanigans, so I felt safe enough to ask Copilot to Create a grid.py file that implements the Grid class as described in issue #15, and it did just that although with some errors in areas not mentioned in the spec (e.g. mixing row/column order) but they were easily fixed with more specific prompting. Even accounting for handling errors, that’s enough of a material productivity gain to be more optimistic of agent capabilities, but not nearly enough to become an AI hypester.。关于这个话题，同城约会提供了深入分析