Comment by tapoxi
3 hours ago
I searched for something, it told me that according to a YouTube video, the entire point of my search was wrong. I asked it for the source, I watched the video, it never made the claims Gemini hallucinated. I asked again and it claimed it scrubbed the video and found the point it made multiple times. I said those timecodes were wrong and it admitted it couldn't actually parse videos and just guessed.
What the fuck?
When it says it can read videos you don’t trust it.
When it says it can’t read videos you think that’s an accurate introspection on its abilities, and not a statistically likely continuation of a conversation where one side seems to be reading videos and the other side says the read is inaccurate?
I don't understand how this isn't considered as active malice. Like purposefully outputting random stuff. Any other sort of computer system would get lot more flak than these are getting.
Throughout my career, I've almost always been close enough to the user that I hear about it quickly when something is wrong. It's a tough problem that so many Google engineers are typically so far removed from end users. Or maybe it's just that a small part of the company has long subsidized the rest of the employees to the point that it doesn't matter how good their work is because they'll get paid anyway.
Ex-Googler.
The engineers are pressured to significantly reduce "dependencies" for projects. Anything that could become risk or create friction is dramatically less appetizing.
Simply because of how many people that *must* agree with your proposal. Getting all the relevant tech leads, some you have never heard of or ever spoken with, to agree on a proposal for your team's project is a nightmare.
So you keep it as simple and agreeable as possible. Given the circumstances, it makes sense as one of the engineers. It's fairly fine advice in general wherever you work, but it just haunts all the work you do at Google in particular. Nothing gets done otherwise.
If you have a dependency that can be dropped from an engineering perspective, that's the route the 9 leads reviewing your design doc will take:
"Let's iterate and start with just the basics (no user testing)", "let's get this working and user test in a later phase", "I think this problem is obvious enough we don't need to consult with users about it."
I worked in Ads Integrity at the time, and for one of my projects I was concerned how it would impact the manual reviewers. Then I learned I couldn't talk with them, only by proxy through another person if we really had to. And that proxy takes time, so...
The scary (or funny) part is people use that for serious questions.
Typical exchange:
Me: "You bastard."
Gemini: "Fair callout. I should have been more up front that [has no idea what the fuck it is talking about]."
I still believe this AI push out of nowhere is due to the current Government in power state side. Making everyone question themselves and each other and being uncertain about facts while being inundated with techbro fake news called hallucinations is a recipe for disaster for older populations that don't 'trust but verify' like most technology inclined people. This is all by design and we'll falling for it.
An interesting conspiracy theory, as long as you're honest about what it is.
The more simple explanation is that the current government in power is over exposed in their AI investment. The normal conservative mainstream media was already doing a great job of propagandizing older populations.
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Yup. I'm most familiar with Jill Lepore and Quinn Slobodian (and others in their respective orbits). They're both historians who've written extensively about Musk and Muskism (et al). Wild stuff.
Apparently the plan is to use AI slop, mediated thru social medias, to defeat the woke mind virus, perpetuated by the Anti-Christ, in order to safe guard humanity's future.
I wish I was making this up.
Same experience with the interaction I described in my comment... after I finally got the correct answer, I asked where it got the faulty information from. It said it had just simply fabricated it. That's actively worse than just saying "I don't know", for something that's sold to us as an easy way to look up information.
These models are incapable of saying they don't know, because they have no concept of knowing. They simply predict the next word which is most likely.
Maybe it's because they are trained on Internet comments, and the most rare thing to find on the Internet is someone admitting they don't know something.
The saddest part is when people take their experience with Google's idiotic AI implementation and assume that's how all LLMs work. Frontier-class models will, in fact, generally admit when they don't know something. That includes the one I run at home on my own graphics cards, but it seems that Google just doesn't GAF.
Your point about "predicting the next word" mostly means that your post was very easy to predict.