Having an archive of "curated" training data seems like it is going to be important. Otherwise you need "AS" (artificial skepticism) introduced into future models. ("But I read it on the internet!", ha ha.)
Or perhaps there are ways to bucket training data such that the model is aware of which data leans factual (quantifiable) and which data leans opinion (fuzzy, qualifiable?).
(I recently asked Claude about the existence of ball lightning, spontaneous human combustion. I got replies that ultimately did not leave me satisfied. It's probably just as well that I read this article though—I now have an even stronger degree of skepticism with regard to their replies—specifically, I suppose, with topics that are likely to be biased.)
(I'm not quite convinced from the article though that Google is "fighting back". In fact, this feels like another moment where a "player" could try to establish their LLM as more factual. Is that the row Grok is trying to hoe? Or is Grok just trying to be anti-woke?)
the justification for not doing that is probably "prohibitively expensive given the amount of data involved". they'd need a bunch of human reviewers combing through massive troves of data. it's probably cheaper to "sort of fix" it after the fact.
> perhaps there's ways to bucket training data such that the model is aware of which data leans factual (quantifiable) and which data leans opinion (fuzzy, qualifiable)
as a lecturer once said to me about my idea for a masters dissertation project that would classify news sites based on right/left tendencies -- "that sounds dangerously political". especially given the current let's all shout at each other political climate.
aside: someone built this and it was a fully fledged company, which has always annoyed me.
The strength of the sources should be clearly indicated in the answers to help users gauge how trustworthy the info is.
LLMs are very good at this clearly
One blog post ... that's all it takes. i'm actually surprised it's that bad. i would have thought it'd take more effort, but i guess it could depend on some sort of purposeful weighting based on search rank during training?
> If a company or website is caught breaking the rules, it could be removed from or downranked in Google's search results. And if you're not on Google, it's like you don't exist.
> "You can give a company a penalty for their website," he says, "but there's nothing stopping them from paying 20 YouTube influencers to say their product is the best." And now, Google's AI is citing YouTube videos.
This makes me think of the stackoverflow seo spam problem we all had like 5 years ago. which ended up with spammers just constantly spinning up new sites all the time.
... the cat and mouse game is in full swing already.
It was SOOOOO successful with search, right?
file:///Users/GermaTW1/BBC%20Dropbox/Thomas%20Germain/A%20Downloads%20and%20Documents/2026/And%20there's%20evidence%20that%20AI%20tools%20are%20being%20manipulated%20on%20a%20wide%20scale.
63•29m ago
simmerup•20m ago
I only knew that because i saw the movie, but it’s a clear sign that the internet is going to shit for quality information
antonyt•6m ago