> While there are 54 recognized countries in Africa, none of them begin with the letter "K". The closest is Kenya, which starts with a "K" sound, but is actually spelled with a "K" sound. It's always interesting to learn new trivia facts like this.
https://www.google.co.uk/search?q=which+africa+countries+beg...
- Micro-fees for the web are a good idea. Because "If you don't pay you are the product", etc.
- BUT, they HAVE to be micro-fees. Because of the fact that, EVERYONE uses the internet now. Literally almost all of humanity. To charge 30$ per Month (like ChatGPT does) for such a basic service, would bring an Incomprehensible amount of money in the hands of a few providers, which would make them even more dominant than they already are, I'm afraid. Technologically, we have now 0 problems to implement a solid micro-fee system.
- "But"- you say- "The point of making people pay is to bring back competition, right? If a lot of people pay, more companies will compete to offer the same services and prices will go down". Well, I don't know about this. To me, it seems like the Internet is Intrinsically a monopolistic affair... VEry few companies have the know-how and resources to operate at Google Scale. Networks effects are a thing too (think reviews on Google Maps, etc), and so on...
So I think, in the end, like many of the other basic utilities, prices will have to be controlled by regulation...
It's worth pointing out that facebook makes on average $16 per month per US user, simply by selling ads to show them. And it makes $3 per month per global user.
TL;DR ChatGPT can "lie" and its bad extrapolations are hard to debunk.
I think this is a bad comparison. The issues OP described are not limited to tainted training data. Being critical of Wikipedia and critical of science is not equal to treating text as a black box looking for the most fitting continuation.
LLMs are not fact machines.
When you equate this kind of error with the scientific replication crisis or generally a crtique of scientific methods and political influence (what about commercial?), I don't think this demonstrates critical thinking.
> [...] especially on Wikipedia. Of course, transformer models have the same issues
I agree that one should be critical of all sources, including Wikipedia. I don't agree that GPT is an information source comparable to Wikipedia or scientific studies. Both can be wrong, biased or incorrect though.
In other words, I would never consider the usage of any LLM worth to cross-check information found elsewhere, as opposed to e.g. Wikipedia.
Which does not mean that I consider the info compiled on Wikipedia always as trsutworthy. Then again, I wouldn't use an LLM to cross-check Wikipedia.
They're not equals.
Sorry if I misunderstood anything in your comment.
I'm not arguing that Wikipedia is a good primary source, I still think it is very suitable as a point of entry if you want to cross-check information from other sources.
A user-editable encyclopedia is not perfect, but it is not comparable to automatically generated text that has no regard for correctness, that only tries to fit its training data and prompt.
For example, I wouldn't trust GPT when asking for the height of some building in my city. I would consider it likely though that it confidently gives ke a wrong number.
Without all the RLHF training to refuse "best guess" answers, situation would be even more bleak.
But im sure there's some hybrid in the works that will be very helpful soon.
Just tried it, so good and fast.