Looking forward to when Europe and China also launch their own satellite internet constellations
WalnutLum
joined 9 months ago
The key is to get one where you can widen the spray and squeegee everything off.
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.
I like using it like a rubber ducky. I even have it respond almost entirely in quacks.
Note: it's a local model running for free. Don't pay anyone for this slop.
“When asked about buggy AI, a common refrain is ‘it is not my code,’ meaning they feel less accountable because they didn’t write it.”
That's... That's so fucking cool...
He's mad because SpaceX got caught falsifying EPA documents and the FAA can't keep letting them launch rockets with a wink and a nudge.
The FAA's blatant favoritism has gotten so bad the EPA had to sue the FAA just to force them to admit they fucked up.
Shit's wild.
Main issue is drivers. One of the best places to take advantage of rust's memory safety is in hardware drivers, and those would be hard to share between separate kernels.
That entire talk, and the complaint that Ts'o responded to was that to continue with rust, there needs to be some responsibility from the guys working on the underlying C bindings to not break downstream dependencies if they refactor code.
The answer from some of the Kernel developers, and vocally by Ts'o was: lol no fuck you and your toy language.
You said open source. Open source is a type of licensure.
The entire point of licensure is legal pedantry.
And as far as your metaphor is concerned, pre-trained models are closer to pre-compiled binaries, which are expressly not considered Open Source according to the OSD.
From the approach section:
A Transformer sequence-to-sequence model is trained on various speech processing tasks, including multilingual speech recognition, speech translation, spoken language identification, and voice activity detection. These tasks are jointly represented as a sequence of tokens to be predicted by the decoder, allowing a single model to replace many stages of a traditional speech-processing pipeline. The multitask training format uses a set of special tokens that serve as task specifiers or classification targets.
This is not sufficient data information to recreate the model.
From the training data section:
The models are trained on 680,000 hours of audio and the corresponding transcripts collected from the internet. 65% of this data (or 438,000 hours) represents English-language audio and matched English transcripts, roughly 18% (or 126,000 hours) represents non-English audio and English transcripts, while the final 17% (or 117,000 hours) represents non-English audio and the corresponding transcript. This non-English data represents 98 different languages. As discussed in the accompanying paper, we see that performance on transcription in a given language is directly correlated with the amount of training data we employ in that language.
This is also insufficient data information and links to the paper itself for that data information.
Additionally, model cards =/= data cards. It's an important distinction in AI training.
There are guides on how to Finetune the model yourself: https://huggingface.co/blog/fine-tune-whisper
Fine-tuning is not re-creating the model. This is an important distinction.
The OSAID has a pretty simple checklist for the OSAID definition: https://opensource.org/deepdive/drafts/the-open-source-ai-definition-checklist-draft-v-0-0-9
To go through the list of materials required to fit the OSAID:
Datasets Available under OSD-compliant license
Whisper does not provide the datasets.
Research paper Available under OSD-compliant license
The research paper is available, but does not fit an OSD-compliant license.
Technical report Available under OSD-compliant license
Whisper does not provide the technical report.
Data card Available under OSD-compliant license
Whisper provides the model card, but not the data card.
Oh and for the OSAID part, the only issue stopping Whisper from being considered open source as per the OSAID is that the information on the training data is published through arxiv, so using the data as written could present licensing issues.
The problem with just shipping AI model weights is that they run up against the issue of point 2 of the OSD:
The program must include source code, and must allow distribution in source code as well as compiled form. Where some form of a product is not distributed with source code, there must be a well-publicized means of obtaining the source code for no more than a reasonable reproduction cost, preferably downloading via the Internet without charge. The source code must be the preferred form in which a programmer would modify the program. Deliberately obfuscated source code is not allowed. Intermediate forms such as the output of a preprocessor or translator are not allowed.
AI models can't be distributed purely as source because they are pre-trained. It's the same as distributing pre-compiled binaries.
It's the entire reason the OSAID exists:
- The OSD doesn't fit because it requires you distribute the source code in a non-preprocessed manner.
- AIs can't necessarily distribute the training data alongside the code that trains the model, so in order to help bridge the gap the OSI made the OSAID - as long as you fully document the way you trained the model so that somebody that has access to the training data you used can make a mostly similar set of weights, you fall within the OSAID
Edit: also the information about the training data has to be published in an OSD-equivalent license (such as creative Commons) so that using it doesn't cause licensing issues with research paper print companies (like arxiv)
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I don't know if thinking that training data isn't going to be more and more poisoned by unsupervised training data from this point on counts as "in practice"