I was lucky to get in in the early days when posting Mastodon handles on Twitter was common so was able to easily migrate. But this is a problem with ActivityPub right now I feel like. Discovery algorithms can be awful in the timeline, but so useful for finding people/communities to follow.
Yep just saw that too after I researched it a bit more. What is strange is I don't remember Eve Energy having a firmware update since then. Makes me wonder if they had it ready to go in previous firmware versions based on internal specs they saw? Or maybe I just forgot about a firmware update I did.
but as the Matter standard doesn't yet support energy monitoring, users are limited to basic features like on and off and scheduling
- from this link
Granted the article is almost a year old. But I just didn't realize that Matter now supports energy monitoring. Somehow I just missed that news.
I'm not aware of any official Ubiquiti certifications. Maybe it was a 3rd party certification? Someone else might know more than I do tho.
I know I'm not necessarily the target audience for this. But it feels too expensive. 6x the price of Cloudflare R2, almost 13x the price of Wasabi. Even iCloud storage is $0.99 for 50 GB with a 5 GB free tier. But again, I know I'm not necessarily the target audience as I have a lot of technical skills that maybe average users don't have.
If you ever get around to building an API, and are interested in partnerships, let me know. Maybe there is a possibility for integration into !echo@eventfrontier.com 😉.
This worked!!! However it now looks like I have to pass in 32 (batch size) comments in order to run a prediction in Core ML now? Kinda strange when I could pass in a single string to TensorFlow to run a prediction on.
Also it seems to be much slower than my Create ML model I was playing with. Went from 0.05 ms on average for the Create ML model to 0.47 ms on average for this TensorFlow model. Looks like this TensorFlow model also is running 100% on the CPU (not taking advantage of GPU or Neural Engine).
Obviously there are some major advantages to using TensorFlow (ie. I can run on a server environment, I can better control stopping training early based on that val_accuracy metric, etc). But Create ML seems to really win in other areas like being able to pass in a simple string (and not having to worry about tokenization), not having to pass in 32 strings in a single prediction, and the performance.
Maybe I should lower my batch_size? I've heard there are pros and cons to lowering & increasing batch_size. Haven't played around with it too much yet.
Am I just missing something in this analysis?
I really appreciate your help and advice!
Interesting! I'll try this tonight and see how it goes. Really appreciate your reply tho. I'll let you know the outcome.
Got it. Thanks for the reply! So is Keras just a dependency used in TensorFlow?
From what I've seen TensorFlow is still more popular. But that might be starting to change. Maybe we need to make a PyTorch community as well 🤔
I wish it worked on more webpages. But totally agree.
What? I'm not following. Steam isn't federating with anyone. This is about having a link to an external site. Nothing more. Has nothing to do with federation directly.
It’s not really any different than hosting any other service.