Generative AI
It is the opinion of the Board that Large Language Models (LLMs), herein referred to as Slop Generators, are unsuitable for use as software engineering tools, particularly in the Free and Open Source Software movement.
The use of Slop Generators in any contribution to the Asahi Linux project is expressly forbidden. Their use in any material capacity where code, documentation, engineering decisions, etc. are largely created with the "help" of a Slop Generators will be met with a single warning. Subsequent disregard for this policy will be met with an immediate and permanent ban from the Asahi Linux project and all associated spaces.
Illegal output¶
All of the popular Slop Generators are trained on an incomprehensibly large corpus of text. There is ample evidence across the Web of this training material including copyrighted material, brazenly stolen by the Slop Generator proprietors with impunity. Due to the nature of Slop Generators, they are prone to regurgitating their training corpus almost verbatim. This presents a challenge for FOSS projects in that the use of generated slop is highly likely to violate intellectual property law by way of regurgitating the aforementioned stolen training material. This likelihood is proportional to the specificity of the problem area.
Asahi Linux is a highly specific project, working in esoteric problem spaces on publicly undocumented hardware. Given the techniques used by Slop Generator manufacturers, it is not impossible for them to have confidential or leaked material owned by Apple or its vendor partners in their training corpi. It is therefore likely that Slop Generators will regurgitate this when queried in just the right way. We already forbid the use of illegally acquired or leaked documentation and tooling (e.g. Apple's internal repair diagnostic tools). This also applies to regurgitated slop.
FOSS projects like Asahi Linux cannot afford costly intellectual property lawsuits in US courts. The current political situation in that nation also makes it incredibly unlikely that any FOSS project would win such a suit regardless of the quality of its defence.
Waste of resources¶
Slop Generators consume an unfathomable amount of resources we can scarcely afford to waste. Training, and to a lesser extent inference, require enormous amounts of energy, water, land, and hardware. Manufacturing the hardware itself requires enormous amounts of energy, water and minerals. All parts of the Slop Generator supply chain are environmentally intensive. These resources are better used on quite literally anything else.
LMGTFY¶
An emerging trend we have observed is people copying user questions or posts into a Slop Generator, then replying to the post with the generated slop. This is occurring with increasing frequency, particularly on Reddit. For some people it is tempting to "help" others and answer questions by feeding them to a LLM and then posting the answer as-is, or lightly edited at best. If this is you, please realise that others also have access to the same models as you do, and if they wanted an answer from one, they could have asked it themselves. Doing this is exactly as helpful as posting a LMGTFY link, and everyone else will view your actions as if you did exactly that.
It's just matmul¶
It is very easy to get caught up in the hype that bad actors have built around Slop Generators. The anthropomorphic presentation of Slop Generators as "agents" or "assistants" is a very deliberate attempt to manufacture consent for their integration into workforces at the expense of human interaction. The implication of some higher degree intelligence or sentience is very much deliberate, and it is very much false.
Make no mistake, they cannot think. They cannot reason. They cannot take into account context. They don't "know" things or have a sense of humour or any of the other human-centric qualities bad actors would have you believe of them. Slop Generators are a chain of matrices in a stochastic system. The output of a Slop Generator is nothing more than a statistical calculation, where the next word to be generated is decided by an opaque probabilistic function dependent on previously generated words. This is fundamentally the same mathematics that is used to predict the weather.
A Slop Generator cannot assess the veracity of its claims, nor can it ever tell you that it simply does not know something. Slop Generators are often confidently incorrect as a result, and require brow-beating to admit a mistake. They are therefore highly inappropriate tools in contexts where truth and correctness are of utmost importance, and when the user is not already highly knowledgeable and confident in the problem area. This presents a bit of an issue for Slop Generators; if the user is already highly knowledgeable and confident in the problem area, then why ask the Slop Generator in the first place?