Podcasts tend to be relatively terrible, accuracy wise. If the alternative is learning from ChatGPT, your odds of getting correct information is substantially higher.
Podcasts are entertaining! But not where I would go to learn anything.
At one point I came across this series of "are CJK languages related" questions in Quora with cached ChatGPT responses[1], all grammatically correct and very natural, largely turboencabulators, sometimes contradicting even within a single response.
Podcasters? They're not _this_ inconsistent.
Even worse, I think they actually prime it with answers already posted on the thread, or even just related threads. For example, one of the answers to the first question mentions the same Altaic root as ChatGPTs answer, and I've found multiple people that are seeing their own rephrased answers in the response.
If you preprompt ChatGPT with questionable data, then the answer quality will be massively degraded. I've noticed many times now that Bing will rephrase incorrect information or construct a very shallow summary out of unrelated articles when internet searches are allowed, but is able to generate a cohesive and detailed summary when they're disabled.
Throwing random answers - some contradicting each other and some talking about subtly different aspects of the topic - into a session without further guidance just isn't a great idea.
My problem is not that GPTs are too often wrong, it's that they always prioritize syntax over facts since they are _language_ models.
The sentence "Colorless green ideas" always make more sense to LLM than "Water is wet", simply because the latter is syntactically invalid, and that would be problematic for many use cases including Podcast replacement. Sometimes us humans want AI to say "water is definitively wet", and that has been attempted by forcing LLM to accept that factoids are more syntactically correct, but that isn't a solution and it's still an architectural problem for these pseudo-AGI apps.
There are podcasts for almost every topic where experts are present. Journalists, Scientists, Activists, Researchers etc. can be heard in podcasts, I don't really see why it's generally a mistake to listen to a podcast to learn important information.
During the pandemic my partner was attending university from home and listening to their professors via MS Teams, these classes were also recorded so that they could listen to them at a later point. In some ways that's just a professional podcast.
And depending on the class and the institution, I may still trust ChatGPT more than what gets taught.
There are tons of podcasts involving experts talking about their field of expertise, how can it be a mistake to listen to such podcasts to gather information?
There is no “sort by accuracy” button in any podcasting app, nor are they peer reviewed.
Furthermore, podcasts are not a review of the body of knowledge on a subject; they’re often a complete layperson interviewing a single member of a given field, at best. Almost never do the views of any individual actually represent any field as a whole.
So once we’ve thrown out the concept of accuracy and completeness, ChatGPT fares exceedingly well in comparison. You’d do much worse than ChatGPT for idle conversation level accuracy.
Yes, they have.
Setting aside the many individuals who currently lead their fields, history is filled with groundbreaking heretics.
https://informationisbeautiful.net/visualizations/mavericks-...
You, most importantly, are complete garbage at telling the difference between a crackpot and an innovator in a field you know nothing about.
Trying to drink unpasteurized knowledge will infect you a lot more quickly than it will enlighten you.
It's not censorship, propaganda and official disinformation, it's "Pasteurized Knowledge®"
That's what flat-eartherism is, that's what jewish space lasers are. The argument you're giving is a tacit endorsement of that kind of "inquiry", which for reasonable people is unconscionable.
In the beginning people were skeptical but over time, as Wikipedia matured, the answer has become (I think): Don't blindly trust what you read on Wikipedia but in most cases it's sufficiently accurate as a starting point for further investigation. In fact, I would argue people do trust Wikipedia to a rather high degree these days, sometimes without questioning. Or at least I know I do, whether I want to or not, because I'm so used to Wikipedia being correct.
I'm wondering what this means for the future of LLMs: Will we also start trusting them more and more?
This argument is so dishonest its infuriating.
The main thing I’m getting from this discussion is that a lot more very smart people seem to have deluded themselves into thinking knowledge is objective or “locked in” than I had initially realized. The desire for certainty is an extremely human thing, but it’s a dead end, intellectually.