The problem is an enforced 8KB payload limit. A video frame at 640x360 is 25-40KB. We'd have to chunk every frame into 4-5 separate notifications, reassemble them on the other end, handle ordering, handle dropped chunks — at which point you've built a worse TCP on top of a notification system. Audio frames would mostly fit under 8KB, so we could do a hybrid approach, but splitting the media pipeline across two different transport mechanisms is the kind of complexity I wasn't interested in.
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A bigger problem is that the grid resolution is pretty low, so this is almost going to feel like playing Breakout on an LCD screen, or maybe an RCA Studio II. (Moving objects on a field-sequential system can have some funky color effects, but these blocks will be moving too slowly to enjoy them) To fix that, we’d have to go into HIRES mode.
Enter the GPUs. Acres works with geospatial data—not just spreadsheets, but vector and raster layers that define the points, lines, and polygons behind land ownership and zoning maps. Crunching that kind of imagery and geometry is computationally heavy, and bringing GPUs in‑house lets the team train models and run site‑selection analyses faster and at lower cost, according to Malloy, who declined to comment on how much his utility bills had risen, apart from saying “it uses some power.”，这一点在谷歌中也有详细论述
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