Ok, but I would say that these concerns are all small potatoes compared to the potential for the general public gaining the ability to query a system with synthesized expert knowledge obtained from scraping all academically relevant documents. If you’re wondering about something and don’t know what you don’t know, or have any idea where to start looking to learn what you want to know, a LLM is an incredible resource even with caveats and limitations.
Of course, it would be better if it could also directly reference and provide the copyrighted/paywalled sources it draws its information from at runtime, in the interest of verifiably accurate information. Fortunately, local models are becoming increasingly powerful and lower barrier of entry to work with, so the legal barriers to such a thing existing might not be able to stop it for long in practice.
The phrase “synthesised expert knowledge” is the problem here, because apparently you don’t understand that this machine has no meaningful ability to synthesise anything. It has zero fidelity.
You’re not exposing people to expert knowledge, you’re exposing them to expert-sounding words that cannot be made accurate. Sometimes they’re right by accident, but that is not the same thing as accuracy.
The fact you confused what the LLM is doing for synthesis is something loads of people will do, and this will just lend more undue credibility to its bullshit.
People developing local models generally have to know what they’re doing on some level, and I’d hope they understand what their model is and isn’t appropriate for by the time they have it up and running.
Don’t get me wrong, I think LLMs can be useful in some scenarios, and can be a worthwhile jumping off point for someone who doesn’t know where to start. My concern is with the cultural issues and expectations/hype surrounding “AI”. With how the tech is marketed, it’s pretty clear that the end goal is for someone to use the product as a virtual assistant endpoint for as much information (and interaction) as it’s possible to shoehorn through.
Addendum: local models can help with this issue, as they’re on one’s own hardware, but still need to be deployed and used with reasonable expectations: that it is a fallible aggregation tool, not to be taken as an authority in any way, shape, or form.
Ok, but I would say that these concerns are all small potatoes compared to the potential for the general public gaining the ability to query a system with synthesized expert knowledge obtained from scraping all academically relevant documents. If you’re wondering about something and don’t know what you don’t know, or have any idea where to start looking to learn what you want to know, a LLM is an incredible resource even with caveats and limitations.
Of course, it would be better if it could also directly reference and provide the copyrighted/paywalled sources it draws its information from at runtime, in the interest of verifiably accurate information. Fortunately, local models are becoming increasingly powerful and lower barrier of entry to work with, so the legal barriers to such a thing existing might not be able to stop it for long in practice.
The phrase “synthesised expert knowledge” is the problem here, because apparently you don’t understand that this machine has no meaningful ability to synthesise anything. It has zero fidelity.
You’re not exposing people to expert knowledge, you’re exposing them to expert-sounding words that cannot be made accurate. Sometimes they’re right by accident, but that is not the same thing as accuracy.
The fact you confused what the LLM is doing for synthesis is something loads of people will do, and this will just lend more undue credibility to its bullshit.
People developing local models generally have to know what they’re doing on some level, and I’d hope they understand what their model is and isn’t appropriate for by the time they have it up and running.
Don’t get me wrong, I think LLMs can be useful in some scenarios, and can be a worthwhile jumping off point for someone who doesn’t know where to start. My concern is with the cultural issues and expectations/hype surrounding “AI”. With how the tech is marketed, it’s pretty clear that the end goal is for someone to use the product as a virtual assistant endpoint for as much information (and interaction) as it’s possible to shoehorn through.
Addendum: local models can help with this issue, as they’re on one’s own hardware, but still need to be deployed and used with reasonable expectations: that it is a fallible aggregation tool, not to be taken as an authority in any way, shape, or form.