Firefly needs to hurry up and make a human-rated capsule instead of cargo farings.
I have high hopes for a company that can set up a rocket almost from scratch in 24 hours.
Firefly needs to hurry up and make a human-rated capsule instead of cargo farings.
I have high hopes for a company that can set up a rocket almost from scratch in 24 hours.
One of the few practical things AI might be good at:
NewPipe can do peertube as well
Isn’t the emperor’s tower and all the surface guns oriented toward the second option?
Seems like it’s a little of both
I’d say mostly energy savings and CPU usage efficiency
Ah, no not the template files for the individual containers, but the project descriptors are just compose files.
They’re 1-1 compose files.
The app just saves them as compose files and then runs docker compose in the backend.
it is EXTREMELY barebones
There’s also Yacht.
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Flat epistemological statements like this are why I feel like more STEM people need to take Philosophy.
The OSI just published a resultnof some of the discussions around their upcoming Open Source AI Definition. It seems like a good idea to read it and see some of the issues they’re trying to work around…
https://opensource.org/blog/explaining-the-concept-of-data-information
Yes of course, there’s nothing gestalt about model training, fixed inputs result in fixed outputs
I suppose the importance of the openness of the training data depends on your view of what a model is doing.
If you feel like a model is more like a media file that the model loaders are playing back, where the prompt is more of a type of control over how you access this model then yes I suppose from a trustworthiness aspect there’s not much to the model’s training corpus being open
I see models more in terms of how any other text encoder or serializer would work, if you were, say, manually encoding text. While there is a very low chance of any “malicious code” being executed, the importance is in the fact that you can check the expectations about how your inputs are being encoded against what the provider is telling you.
As an example attack vector, much like with something like a malicious replacement technique for anything, if I were to download a pre-trained model from what I thought was a reputable source, but was man-in-the middled and provided with a maliciously trained model, suddenly the system I was relying on that uses that model is compromised in terms of the expected text output. Obviously that exact problem could be fixed with some has checking but I hope you see that in some cases even that wouldn’t be enough. (Such as malicious “official” providence)
As these models become more prevalent, being able to guarantee integrity will become more and more of an issue.
I’ve seen this said multiple times, but I’m not sure where the idea that model training is inherently non-deterministic is coming from. I’ve trained a few very tiny models deterministically before…
I’m not sure where you get that idea. Model training isn’t inherently non-deterministic. Making fully reproducible models is 360ai’s apparent entire modus operandi.
There are VERY FEW fully open LLMs. Most are the equivalent of source-available in licensing and at best, they’re only partially open source because they provide you with the pretrained model.
To be fully open source they need to publish both the model and the training data. The importance is being “fully reproducible” in order to make the model trustworthy.
In that vein there’s at least one project that’s turning out great so far:
Holy crap there are still working nitter instances? God bless
Ahhhh that makes a lot more sense, thanks!
I didn’t realize you could run something like this on your phone
You should play voices of the void then. Game is chock full of random spooks with lots of very quiet and relaxing downtime, so they hit pretty hard when they happen.