FOPLP也正凭借规模化优势快速崛起，被视为CoWoS的潜在继任者。FOWLP基于圆形晶圆进行封装，由于晶圆形状为圆盘状，边缘区域难以充分利用，导致芯片放置面积较小。尺寸与利用率优势是FOPLP的核心竞争力。FOPLP采用方形大尺寸面板作为载板，而非8英寸或12英寸晶圆。
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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.
They will be in glass bottles, but for the foreseeable future at least, they won't be returnable. "We are slowly picking up distributors and growing the brand," says Hartwig.