I don't know if we're guaranteed to see the same level of support for Android based devices, and if Google decides they're not marketable enough, they could drop support as soon as before they even launch as they have with previous hardware initiatives.
Right - I wasn't suggesting that it would fix the notification issue, just that it might give the previous commenter the Android environment they're looking for.
They're certainly losing interest in maintaining core Android, which is closer to what I meant. Everything you've described is within their Play Services environment.
Some of what you've said is incorrect as well - I have a third party gallery that works just fine on my stock Pixel 8 Pro. Its access is just managed by a separate permission.
I feel like it's been downhill since Jelly Bean.
It's just a different use case to create a single-file large language model engine that automatically chooses the "best" parameters to run under. It uses llama.cpp under the hood.
The intent is to make it as easy as double clicking a binary to get up and running.
A minor complaint, but I hope they remove the yellow highlights throughout Wear OS. It's just unnecessary.
Of course!
You can tinker in the image in a variety of ways, but make sure to preserve your state outside the container in some way:
- Extend the image you want to use with a custom Dockerfile
- Execute an interactive shell session, for example
docker exec -it containerName /bin/bash - Replace or expose filesystem resources using host or volume mounts.
Yes, you can set a variety of resources constraints, including but not limited to processor and memory utilization.
There's no reason to "freeze" a container, but if your state is in a host or volume mount, destroy the container, migrate your data, and resume it with a run command or docker-compose file. Different terminology and concept, but same result.
It may be worth it if you want to free up overhead used by virtual machines on your host, store your state more centrally, and/or represent your infrastructure as a docker-compose file or set of docker-compose files.
What is obscene is subjective.
I'll take a forehead over a notch.
Mine has also been very reliable.
xcjs
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Deepseek R1 and OpenThinker are two more examples. There's also SmolLM, which I believe also open sources its training data and ensures proper licensing for it.