And, more importantly, you should use images that are an appropriate resolution for the size they will be displayed. Even if you switch to PNG, using a 2000x2000 image for a icon displayed 20x20 is a waste.

More likely for Axon to acquire flock than the other way around.

[1] https://www.home-assistant.io/

[2] Although frankly to have a fast-enough and good-enough LLM you might need to use a service

There's so much going on in that sentence! What a thing of pure PR beauty.

What does "owned" mean in this sentence? Probably fairly little.

What data does it even refer to? Just the actual video footage? Does the statement include derived data like license plate reads or ML models?

And surely if data is flagged as relevant to an investigation it is not deleted, so is there an implicit "*unless retained"?

1. The translation system would still have to implement the underlying ideas. For example, your spec might explain "key frames are made by doing a wavelet transform ABC, dropping frequency XYZ, applying Heuristic Alpha and then doing LZ encoding on the result" or something like that. You still need implementations of those specific operations. Having to explain all that stuff in the spec would mean each english language doc would be book length tretsie on encoding. As a result, you don't really gain much by doing this kind of meta-explaination.

2. Video encoding/decoding is something where optimization is extremely important. Writing code that is specific to a single purpose is generally going to be faster than generic code that could be applied to any theoretical format. For example, by knowing the exact size of a transformation matrix, you can decide whether to build a lookup table or calculate on the fly - you can use hardware level features that require knowing exact sizes at build-time etc.

Because the author of the piece is worried about the CO2 levels in their home, not about global warming. (well maybe they are worried about global warming too, but that's not what this is about)