As this phenomenon is so common, do we have enough science about it to make it a base for laws, so future generations could avoid this state of collective psychosis it seems to lead to?
I think it is widely accepted that power corrupts. It is the basis of democracy, and why we would defend it so jealously. Democracy was fought for and won, and we should never forget the alternatives are much worse. This requires peaceful debate, free speech, and free and fair elections.
Probably these pelicans are just some kind of a sarcastic reaction to the AI situation, however I just would like to motivate the author to step up to a much more important question: are the models outputs reliable?
That means are they trustworthy, or simply said true.
There is a science behind getting computers to produce reliable and correct results.
Current AI products still do not conform to that goal and therefore are not usable.
Instead of making this tech usable behind closed doors, they are selling unfinished products that produce errors and people are already dying from it!
It seems to be of more importance to test the product presented on this issue instead of drawing pictures.
Please use your professional skills for something useful, thank you very much!
Just imagine we could buy one piece of hardware where we could run all our software on, wouldn’t that be awesome? We could call it a „Personal Computer“ and it could start a revolutionary new way of doing business independent of gatekeepers! Freedom for free people!
Spoken as someone who has never seen a weather forecast. Computers have long produced results that were, if interpreted naively, incorrect. These systems require humans to take into account the conditional, probabilistic nature of the output and the inherent limitations of the model the computer was executing, when they interpret the output. LLM's are no different. They give you next token prediction probabilities. That is all. There is no particular reason to think that comes (or even could come) with a promise that those tokens will express truths about the world and only truths. The fact that greed-driven hype, and our human inclination to anthropomorphize the token generator inclines us to imagine things should be different doesn't make it so. No model output is truth. Never has been.
For (C) -- I think it could additional create jobs funded by government, philanthropic and other private institutions. For example, a government funded museum may already be participating in Wikimedia GLAM projects (e.g. uploading historical images to Wikimedia Commons with complete metadata). Perhaps this type of open source contribution may increase if organisations realise their mission can be better accomplished by contributing this same open data into LLMs, in addition to Wikimedia Commons. If the museum's mission is to educate the public on the history of life in ACMEville, having LLMs be able to provide historical information and images to a prompt of "What is the history of ACMEville?" may be a good pursuit.
I'm sceptical though whether use of LLMs would encourage creation of data that doesn't already exist. For example, if you ask an LLM "What are the top 100 most prevalent flora endemic to ACME National Park", this data may not currently exist _at all_, and to collect, would require paying botanists to do an extensive field survey. If no one has done this work yet--why? Is it relevant to the scientific community, to making government decisions, etc, or just an obscure academic curiosity. There are certainly some journal articles on _other_ national parks describing some of their common endemic flora, but perhaps there was a reason for this. Such as a scientist funded by a one-off government program trying to determine how to preserve or even create habitat for a specific endangered species.
Consider for the prompt of: "What are the top 100 most prevalent flora endemic to ACME National Park"
An LLM may reply: "I couldn't find any journal article or other prior work that may answer this question. Typically such survey field work may cost $X to complete, require expert botanists, and take 6-12 months to complete. Let me know if you want further information on how to find and select a company to conduct such a botanical field survey."
Would this type of LLM response grow the industry of botanical field surveys, or do nothing, perhaps because anyone likely to fund botanical field surveys is already doing so regardless of whatever is happening with AI.
I think all of these can be addressed by being able to understand which machines contributed what to the model. I know that's messy, but if I can state "this information has come from Alice and the consensus is that it's good and right as it aligns with other information from Bob and others, meanwhile this information came from Mallory and stands out as being incongruent with the rest of the information I have in the model", we can identify malicious violations. If we're then able to state either Alice or Bob is one of the copyright holders, and one of them gets paid a little more, the other a little less as the confirmation agent, well, the economics of all of this changes a little.
At the moment we have Annas Archive being paid by frontier labs and rare/second hand books being destroyed in order to support the training regime. If instead we could just pay the publishers and they could distribute royalties to authors...
Yes, very much so. It is basically a standard across the western world for politicians, journalists, whatsapp refugees... Of course there are many alternatives but most of them have most of their users here, on HN.
MacOS, iOS, Windows, Linux, Android are all made in the US and are also virtually universally used. This idea that people avoid American products is super niche.
linux us made in the US? An open source OS, with collaborators from all over the world initially started by a finnish student and still actively the main orchestrator of it, linux torvalds. Not to mention the thousand distros derived from it.
Country of origin doesn't tell you much on its own. Linux is American too, and few question its trustworthiness. What matters is the code being open source and auditable, not where the maintainers live.
"Linux" doesn't keep centralized records that the government can get their hands on. The fact is that the government in the US can (and does) march into US companies and demand access to their data. The government will install their devices on the company's network and even take over entire parts of their offices. What your data sits, who has access to it, and what kind of record the local government has of abuses of their authority are very important things to consider. Much more important than if the code is open source.
How do you handle the potential errors that might be hidden in parts of the code you don’t understand anymore?
Or do you have 100% understanding of the generated code?
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