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.
Alarm bells are ringing in the UK research community. Physics departments may close and researchers leave the UK. What is happening and why?，这一点在服务器推荐中也有详细论述
make bench ARGS="--110m=models/model.safetensors --tdt-600m=models/tdt.safetensors"，这一点在爱思助手下载最新版本中也有详细论述
On Tuesday, Anthropic said it was modifying its Responsible Scaling Policy (RSP) to lower safety guardrails. Up until now, the company's core pledge has been to stop training new AI models unless specific safety guidelines can be guaranteed in advance. This policy, which set hard tripwires to halt development, was a big part of Anthropic's pitch to businesses and consumers.，详情可参考雷电模拟器官方版本下载