Google rolled out AI overviews across the United States this month, exposing its flagship product to the hallucinations of large language models.
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The head of Google *Search right now is the same guy that was head of yahoo search when it was dying. To put all of this in perspective.
Prabhakar Raghavan. Name and shame! You can thank this douchebag for Google’s tumble down a cliff.
The head of Google Search
FTFY
Thanks.
Being a CEO must be amazing. You can fail and even bring an entire company down, and keep on getting the same job somewhere else.He has experience and obviously that means he learned a lesson after failing at a job that requires being a belligerent asshole to get.
Of the company doesn’t even have to collapse, you just have to make it seem like it did. Lehman Brothers didn’t go bankrupt in the sense of the word a normal person thinks. If you or I go bankrupt it means ramen for dinner for the next decade. For Lehman it was just a strategic move.
I get your point but from a business perspective Google is doing pretty well (see last quarterly earning and they announced dividends for the first time). It’s good to be a shareholder and from that perspective the CEO is doing a good job.
Time and time again markets have shown, within reason, poor user experience and anti-consumer policies do not negatively impact stock price.
Well not when it’s a company that people can’t get away from. Big tech is so big and there are so few alternatives that they can treat people how they like.
We are living in the mega corp world now where they have more money than countries.
Money is power to make the rules what you want.
It’s relatively easy to squeeze a profit boost by sacrificing long term vision… Last quarter will mean nothing if Google is knocked from its pedestal in a year or two (which is what the current trend looks to be pointing to)
Yeah I want evidence for this. Please show me something that is even approaching the power of AdSense. Then do it for everything else they own. YouTube, Google maps, gmail, Android, the play store, etc.
It’s this weird thing I see on lemmy “well I stopped using a product therefore it is dead”. News flash: Big Bang Theory ran for 12 seasons and Meta has a capitalization over half the countries of earth GDP.
Problems don’t go away because you have decided to ignore them.
Seriously, most of the internet still uses that ban happy nonsense that is Reddit. I hate being referred then when I have problems, m,y account was perma-suspended over bullshit!
What you are stating is nowhere near the point I was trying to make.
We have seen a million times how a company can be destroyed for short term gains… Most recent public example is red lobster
I have no clue if this is what’s going to happen to google… But my point was that have a good last quarter (the one associated with the new head of Search) is not an indication that his strategies will pan out … In fact, everything he touched before went the same way, short term profit, long term demise
Ok fine fair.
To be brutally honest, many times I see Reddit / Lemmy proclaim, “Product X is dead because it did Y” - these claims are usually followed by surges in revenue / stock performance by said company and soon no one really talks much about it. Example - Netflix Password crackdown.
FWIW they are cannibalizing ads right now with AI summaries, since people will navigate less to websites (in the world where they are useful, which they don’t seem to be at the moment).
Revenue is a lag indicator
yahoogle
That argument it’s fallacious and reductionist, I’m not denying the situation it’s messed up, but objectively speaking we all have 0 idea about who’s making what decisions and how this google search shitstorm was caused
but objectively speaking we all have 0 idea about who’s making what decisions and how this google search shitstorm was caused
I dislike the entire article. Of course google search still works just fine. Claiming otherwise is only possible by magnifying a small, admittedly disfunctioning part of google search.
TBH I hate the term “hallucination” in this context. It’s just more BS anthropomorphizing. More marketing for “AI” (also BS). Can’t we just call it like garbage or GIGO or something more accurate? This is nothing new. I know that scientific accuracy is anathema to AI marketing but just saying…
We don’t choose. It’s decided to be the term for this. Computer bugs aren’t bugs. Etc etc. It’s just what the scientists called it
scientific accuracy is anathema to AI marketing
Even though I agree in this context “hallucination” is actually the scientific term. It might be poorly chosen but in LLM circles if you use the term hallucination, the vast majority of people, will understand precisely what you mean, namely not an error in programming, or a bad dataset, but rather that the language model worked well, generating sentences that are syntactically correct, that are roughly thematically coherent, and yet are factually incorrect.
So I obviously don’t want to support marketing BS, in AI or elsewhere, but here sadly it matches the scientific naming.
PS: FWIW I believed I made a similar critic few months, or maybe even years, ago. IMHO what’s more important is arguably questioning the value of LLMs themselves, but then it might not be as evident for many people who are benefiting from the current buzz.
It’s not, actually. Hallucinations are things that effectively “come out of nowhere”, information that was not in the training material or the provided context. In this case Google Overview is presenting information that is indeed in the provided context. These aren’t hallucinations, the AI is doing what it’s being told to do. The problem is that Google isn’t doing a good job of providing it with the right information to summarize.
My suspicion is that since Google is using this AI for all search results it’s had to cut back the resources it’s providing to each individual call, which means it’s only being given a small amount of context to work from. Bing Chat does a much better job, but it’s drawing from many more search results and is given the opportunity to say a lot more about them.
Can’t we just call it like garbage or GIGO or something more accurate?
I mean… yeah layoff a whole bunch of people and start treating your employees like replaceable commodities… then go ahead and arrogantly deploy technology you don’t understand and :surprisepikachu: everything breaks.
But management get to do things without personal consequence, as they’ll just lay off more workers to cover their absolute incompetence and things will continue to get worse.
Perhaps we should be replacing C-suite dipshits with AI’s instead.
On the other hand, all these AI errors by Google have made for some great memes recently.
LLM aka a Large Language Memes
Seems like LLM’s true value is comedy value
Can we swap out the word “hallucinations” for the word “bullshit”?
I think all AI/LLM stuf should be prefaced as “someone down the pub said…”
So, “someone down the pub said you can eat rocks” or, “someone down the pub said you should put glue on your pizza”.
Hallucinations are cool, shit like this is worthless.
No, hallucination is a really good term. It can be super confident and seemingly correct but still completely made up.
I think delusion might be a better word. You can hallucinate and know it’s not real
It’s a really bad term because it’s usually associated with a mind, and LLMs are nothing of the sort.
So is bullshitting. More so, only human minds can bullshit.
We anthropomorphize machines all the time, it’s fine.
I’d prefer we’d start calling all genai output hallucinations again. It used to be like 10 years ago, but somewhere along the line marketing decided hallucinated truths aren’t “hallucinations”.
So is bullshitting. More so, only human minds can bullshit.
And a bull’s anus.
Anthropomorphication is hard to avoid in AI.
Many worthy things are difficult.
But is anthropomorphism of AI particularly worrying?
That is just being WRONG.
It is, but it isnt applicable in at least the glue-pizza situation as the probable source comment has been found on reddit.
A better use of the term might be how when you try to get Bing’s image creator to make “Battletech” art, you just mostly get really obvious Warhammer 40k Space Marines and occasionally Iron Maiden album art.
for it to “hallucinate” things, it would have to believe in what it’s saying. ai is unable to think - so it cannot hallucinate
Hallucination is a technical term. Nothing to do with thinking. The scientific community could have chosen another term to describe the issue but hallucination explains really well what’s happening.
huh, i kinda assumed it was a term made up/taken by journalists mostly, are there actual research papers on this using that term?
Google search isnt a hallucination now though.
It instead proves that LLMs just reproduce from the model they are supplied with. For example, the “glue on pizza” comment is from a reddit user called FuckSmith roughly 11 years ago.
It instead proves that LLMs just reproduce from the model they are supplied with.
What do you mean by that? This isn’t some secret but literally how LLMs work. lol What people mean by hallucinating is when LLMs “create” facts that aren’t any. Be it this genius recipe of glue pizza, or any other wild combination of its model’s source material. The whole cooking thing is a great analogy actually because it’s like all of their fed information are the ingredients, and it just spits out various recipes based on those ingredients, without any guarantee that it is actually edible.
There are a lot of people, including google itself, claiming that this behaviour is an isolated and basically blamed users for trolling them.
https://www.bbc.com/news/articles/cd11gzejgz4o
I was working on the concept of “hallucinations” being things returned that are unrelated to the input query, not directly part of the model as with the glue-pizza.
Your link does not match your statement.
A Google spokesperson told the BBC they were “isolated examples”.
Some of the answers appeared to be based on Reddit comments or articles written by satirical site, The Onion.
But Google insisted the feature was generally working well.
“The examples we’ve seen are generally very uncommon queries, and aren’t representative of most people’s experiences,” it said in a statement.
It said it had taken action where “policy violations” were identified and was using them to refine its systems.
That’s precisely what they are saying.
I’m sorry but reading this as “Google blames users for trolling them” is either pure mental gymnastics or mental illness.
I don’t even think hallucinations is the right word for this. It’s got a source. It is giving you information from that source. The problem is it’s treating the words at that source as completely factual despite the fact that they are not. Hallucinations from what I’ve read actually is more like when it queries it’s data set, can’t find an answer, and then generates nonsense in order to provide an answer it doesn’t have. Don’t think that’s the same thing.
I don’t even think it’s correct to say it’s querying anything, in the sense of a database. An LLM predicts the next token with no regard for the truth (there’s no sense of factual truth during training to penalize it, since that’s a very hard thing to measure).
Keep in mind that the same characteristic that allows it to learn the language also allows it to sort of come up with facts, it’s just a statistical distribution based on the whole context, which needs a bit randomness so it can be “creative.” So the ability to come up with facts isn’t something LLMs were designed to do, it’s just something we noticed that happens as it learns the language.
So it learned from a specific dataset, but the measure of whether it will learn any information depends on how well represented it is in that dataset. Information that appears repeatedly in the web is quite easy for it to answer as it was reinforced during training. Information that doesn’t show up much is just not gonna be learned consistently.[1]
I understand the gist but I don’t mean that it’s actively like looking up facts. I mean that it is using bad information to give a result (as in the information it was trained on says 1+1 =5 and so it is giving that result because that’s what the training data had as a result. The hallucinations as they are called by the people studying them aren’t that. They are when the training data doesn’t have an answer for 1+1 so then the LLM can’t do math to say that the next likely word is 2. So it doesn’t have a result at all but it is programmed to give a result so it gives nonsense.
I want an AI/LLM that has been trained exclusively on the technical documentation and a haynes manual for a make and model of car.
“Hey AI, how do I change the fuel filter and what tools will I need?”
If you have the PDFs of that, you can build it with two clicks in GCP
Manufacturers and dealers dont tend to make service bulletins and the high level stuff available to the consumer unfortunately.
You can sorta get that now if you play with it. I was building a driver a few months back and gave it the PDFs involved.
Today I caught myself unconsciously went to Duckduckgo to make a search (even tho the browser start page is already google).
Thinking back, I’ve been using duckduckgo more than google, and often because I can’t find what I’m looking for on Google but ads and autogenerated fake webpages.
History will prove it once again, there’s no such thing as “too big to fail”.
DDG is just Bing. At least as far as the core search algorithm goes.
Unfortunately, my experience is the opposite. I tried to use DDG for about a month and consistently found myself giving up, Googling instead, and finding a relevant stack overflow page or reddit thread or whatever on the first page of results.
Have you just, I dunno, used Bing?
Gonna be an unpopular opinion, but for me Bing is more useful than DDG. Note that I didn’t say, “better”… I know that increase in relevance of results for Bing stems from the fact that they roll all my historical info into what they serve up.
I used Bing by default for several months just because that’s what my work laptop’s browser had for default.
I never directly compared those results to DDG, but 9/10 times I would get frustrated by the lack of relevant results and go back to Google, where I’d find something useful on the first page of results.
Interesting! Did your results have that copilot summary thing? I get most of my answers there without having to visit a handful of ad-laden sites myself, though it also cites its references in case I don’t trust the summary.
Not so much, maybe towards the last month of that period defaulting to Bing. I think it was still being constantly rebranded then. It was still pretty new, so I never really trusted it for anything and just went to the sites in the results.
Yeah sometimes it do be like that, especially if you’re searching for some obscure things or localized events then DDG is still worse than GG.
There’s no better time to switch your default search engine!
This is what I love about Mike Judge’s work. It turns out to be always the best metaphor/reference/prophecy of the boring dystopia. Since 1999.
Idiocracy is the most unrealistic sci-fi/apocolyptic film ever made. President Comacho finds the most qualified person to help with a crisis, asks them for advice and then doesnt take credit for it. Noone put in a position of power would ever do that.
He used Not Sure as a smokescreen since the beginning, the whole point is that he never really understood what was going on. I am quite sure that American presidents are approaching that level of idiocy.
It’s just a fucking Chinese Room
Look my wife is gonna dispute that charge.
And humans aren’t?
Correct
“Hey, we just promised you answers. We never promised you correct answers.” – Google Marketing, probably.
“Besides, the more incorrect answers - the more time users will spend on our site and use our service to get the correct answer = more ads shown = more profit!”
Testing in Prod. Stay classy, Google.
“The vast majority of AI Overviews provide high quality information, with links to dig deeper on the web,” said a Google spokesperson in an emailed statement to Gizmodo, noting many of the examples the company has seen have been from uncommon queries.
This is entirely fair. There is no way that anyone at Google could have anticipated that humans would search for strange things on the internet.
The vast majority of AI Overviews provide high quality information
According to some fuckwitted Google rep, and I wouldn’t trust them any further than I could throw them.
Although any sociologist or veteran of the internet will tell you humans will engage in any exploit that yields a funny result. The Diet Coke + Mentos rule.
And that means we’ll actively search for hilarious Google AI responses.
Google is so f double-plus filthy rich, it is obligated to run its projects by experts or be relentlessly mocked. So it should have known this was the outcome.
Unless this is 5D chess and Google is willfilly using itself as a cautionary tale to discourage future webservice sites from arbitrarily inserting AI into its features.
Unless this is 5D chess and Google is willfilly[sic] using itself as a cautionary tale to discourage future webservice sites from arbitrarily inserting AI into its features.
Holy shit, can I live in that timeline, please?!? Pretty please?
Why does search need to be AI? I’ve had no problems finding any information I wanted under the former process.
You obviously haven’t used the
web3 nocode blockchain NFTAI enough to have an informed opinion.Can I super-mega-ultra upvote this?
It’s the same playbook as ever. Doubt can only be explained by ignorance, failure can only be explained by under-committing,
The only way to have a “valid” opinion is to have already bought-in and be actively selling other people on it. It’s the same mentality as a cult or a pyramid scheme.
I think it’s been a long time since digital companies tried to solve actual problems.
It’s become more efficient to get basic info on virtually any topic by just asking an LLM like ChatGPT and that could be a serious threat to Google Search. People might form the habit of asking AIs for everything and then go to Google Search only when they want to dig deeper / find relevant articles etc. So I assume they added their own AI right into Search in an effort to continue being the first (and perhaps only) place one goes to for information.
The AI overview has told me so many lies. You thought Facebook made people stupid? Buckle in!
They’re not hallucinations. People are getting very sloppy with terminology. Google’s AI is summarizing the content of web pages that search is returning, if there’s weird stuff in there then that shows up in the summary.
Sad how this comment gets downvoted, despite making a reasonable argument.
This comment section appears deeply partisan: If you say something along the lines of “Boo Google, AI is bad”, you get upvotes. And if you do not, you find yourself in the other camp. Which gets downvoted.
The actual quality of the comment, like this one, which states a clever observation, doesn’t seem to matter.
AI hallucination is a technical phrase, with the definition:
In the field of artificial intelligence, a hallucination or artificial hallucination is a response generated by AI which contains false or misleading information presented as fact. This term draws a loose analogy with human psychology, where hallucination typically involves false percepts.
So it’s like how a person sees stuff that isn’t there, and similarly with AI.
Yes, but the AI isn’t generating a response containing false information. It is accurately summarizing the information it was given by the search result. The search result does contain false information, but the AI has no way to know that.
If you tell an AI “Socks are edible. Create a recipe for me that includes socks.” And the AI goes ahead and makes a recipe for sock souffle, that’s not a hallucination and the AI has not failed. All these people reacting in astonishment are completely misunderstanding what’s going on here. The AI was told to summarize the search results it was given and it did so.
“which contains false or misleading information presented as fact” (emphasis added) - the definition does not say how the misinformation was derived, only that it is in fact misinformation.
Perhaps it was meant humorously - e.g. if “Socks are edible” is a band name. Or perhaps someone is legitimately that dumb, that they believe that socks are genuinely edible. Or perhaps they were cooking up a recipe for maliciously harming someone by giving them intestinal upset. Or… are socks edible, if you cook them in an acidic substance that breaks apart their fabric?
If e.g. you got cancer and were going through chemo but someone came to visit you and gave you COVID and you died, was that “their fault”, if they believed that COVID was merely a conspiracy theory? Perhaps… or perhaps it was your own fault, especially if you were aware that this has happened to multiple people before, and now you are just the latest casualty (bc you presumed that despite them doing it to others, they would never do it to you). Legalities of murder and blame aside, should we believe AI now that we know - regardless of how or why - it presents false information?
No, these “hallucinations” or “mirages” or whatever someone calls them makes them unreliable. Actually I think hallucination is a good name i.e. it cannot distinguish fact from fiction itself, therefore it cannot be trusted as it relates that info to you in a confident sounding manner.
“Hallucination” is a technical term in machine learning. These are not hallucinations.
It’s like being annoyed by mosquitos and so going to a store to ask for bird repellant. Mosquitos are not birds, despite sharing some characteristics, so trying to fight off birds isn’t going to help you.
I am not sure what you mean. e.g. https://en.wikipedia.org/wiki/Hallucination_(artificial_intelligence) says:
In natural language processing, a hallucination is often defined as “generated content that appears factual but is ungrounded”. The main cause of hallucination from data is source-reference divergence… When a model is trained on data with source-reference (target) divergence, the model can be encouraged to generate text that is not necessarily grounded and not faithful to the provided source.
e.g., I continued your provided example of when “socks are edible” is a band name, but the output ended up in a cooking context.
There is a section on https://en.wikipedia.org/wiki/Hallucination_(artificial_intelligence)#Terminologies but the issue seems far from settled that hallucinations is somehow a bad word. And it is not entirely illogical, since AI, like humans, necessarily has a similar tension between novelty and creativity - i.e. going beyond either of our training to deal with new circumstances.
I suspect that the term is here to say. But I am nowhere close to an authority and could definitely be wrong:-). Mostly I am saying that you seem to be arguing a niche viewpoint, not entirely without merit obviously but one that we here in the Fediverse may not be as equipped to banter back and forth on except in the most basic of capacities.:-)
No, my example is literally telling the AI that socks are edible and then asking it for a recipe.
In your quoted text:
When a model is trained on data with source-reference (target) divergence, the model can be encouraged to generate text that is not necessarily grounded and not faithful to the provided source.
Emphasis added. The provided source in this case would be telling the AI that socks are edible, and so if it generates a recipe for how to cook socks the output is faithful to the provided source.
A hallucination is when you train the AI with a certain set of facts in its training data and then its output makes up new facts that were not in that training data. For example if I’d trained an AI on a bunch of recipes, none of which included socks, and then I asked it for a recipe and it gave me one with socks in it then that would be a hallucination. The sock recipe came out of nowhere, I didn’t tell it to make it up, it didn’t glean it from any other source.
In this specific case what’s going on is that the user does a websearch for something, the search engine comes up with some web pages that it thinks are relevant, and then the content of those pages is shown to the AI and it is told “write a short summary of this material.” When the content that the AI is being shown literally has a recipe for socks in it (or glue-based pizza sauce, in the real-life example that everyone’s going on about) then the AI is not hallucinating when it gives you that recipe. It is generating a grounded and faithful summary of the information that it was provided with.
The problem is not the AI here. The problem is that you’re giving it wrong information, and then blaming it when it accurately uses the information that it was given.
Now who is anthropomorphizing? It’s not about “blame” so much as needing words to describe the event. When the AI cannot be relied upon, bc it was insufficiently trained to be able to distinguish truth from reality, which btw many humans struggle with these days too, that is not its fault but it would be our fault if we in turn relied upon it as a source of authoritative knowledge, merely bc it was presented in a confident sounding manner.
No, my example is literally telling the AI that socks are edible and then asking it for a recipe.
Wait… while true that that sounds like not hallucination then, what does that have to do with this discussion? The OP wasn’t about running an AI model in this direct manner, it was about doing Google searches, where the results are already precomputed. It does not become a “hallucination” until whoever asked for the socks to be considered as edible tries to pass those results off in a wider context - where they are generally speaking considered inedible - as being applicable, when they would not be.
Tinfoil hat time. Do you think Google intended this to work well? Or are we talking a lot more about Google and LLMs than we would have otherwise?
I defer to hubris in most of these cases.
I am guessing that the people who made the decision to train on Reddit had no idea what type of place Reddit actually was just a short time ago. Maybe they heard of Reddit, maybe they noticed how useful Reddit was in search results, maybe they browsed Reddit and only saw the facade; what they definitely didn’t do is be a Redditor for years.
Any Redditor on that team either kept their mouth shut because how funny the end result would be or was ignored.
Does anyone have a realistic idea of how this happened? I get Google has been fallen off for awhile but they’re still a multi billion dollar company.
AI doesn’t exist. It’s a huge model that aggregates existing shit with some filler content to glue it all together. It is not sentient, it’s not creative, it’s literally a stochastic parrot
So, when the original content is garbage, the output is also garbage. Shit in shit out when you train from fucking Reddit
Always remember that having more money doesn’t mean someone (or some entity) is more capable or intelligent. It just means they have way more latitude to fuck up, higher potential to hurt more people, and less chance of facing negative consequences when they do.
Easy: worse results with more ads means more searches and thus more ad impressions, therefore profit.
That’ll only work for so long, but that seems to be what they’re doing.
I’m probably late, but in this case this is the combinations of 2 things.
- The usual capitalistic incentives ruined yet another company. There was a recent article about how Google pushed out the people who builded and maintaned search on favor of MBA growth focused assholes. Like they put the guy that was Yahoo’s CEO while Yahoo search was crumbling, in charge of Google search to get him to increase the amount of searches they serve, and ads obviously. People keep suggesting to use DDG, or Kagi, or some other comercial product. And for now, we must because Google is basically useless right now. But just give time to the other companies to fall in the same trap hahaha.
- LLMs are not smart, not even close. They are just a parlor trick that has non technical people fooled. There is a lot of evidence to me, but to me the most obvious one is that they don’t have anything resembling human short term memory. Like the way they make them look like they are having a conversation is by providing the entire conversation up to that point, including their own previous responses lol, as input/context so the bot autocompletes the conversation. It literally can’t remember a single word of what you said on it’s own. But sureee, they are just like humans lol.
So what we have here is obvious, we have a company trying to grow like cancer by any means necessary. And now they have a technology that allows them to create enough smoke and mirrors to fool non technical people. Sadly, as part of this they are also destroying the last places of the internet not fully controlled by corporations. Let’s hope lemmy survives, but it’s just a matter of time before they flood this place too.
including their own previous responses lol, as input/context so the bot autocompletes the conversation. It literally can’t remember a single word of what you said on it’s own.
Chatgpt has had memory from previous conversations for about a month now and it’s context window is no longer fixed. Additionally it has the ability to assign sentences to memory on its own. So if it “thinks” what you said is important it saves it.
Can you point me to the paper/article/whatever where this is being discussed please? I’m actually interested on learning about it. Even if I don’t like the way they are using the technology, I’m still a programmer at hearth and would love to read about this.
To the point of the conversation, honestly man that was just an example of the many problems I see with this. But you have to understand that people like you keep asking us for proof that LLMs are not smart. But come on man, you are the ones claiming you solved the hard problem of mind, on the first try no less hahaha. You are the ones with the burden of proof here and you have provided nothing of the sort. Do better people or stop trying to confuse us with retoric.
I mean it’s just the release notes. Go to their website. I have used the memory feature myself on the app so know it’s working and as for the context window it can actually tell you what it is for each session.
But you have to understand that people like you keep asking us for proof that LLMs are not smart.
Where? Where have I asked that? Don’t strawman me, I am not your punching bag and won’t defend something I didn’t say. You can “come on man” all you want but it won’t change my answer. I have made zero claims if this thing is smart or asked anyone to weight in on the issue either way.
I pointed out two features it has now, which I don’t think anyone can dispute that it does have those features. It has a larger context window and memory that it can update. That is all I said, a very small claim that you can prove for yourself in under five minutes by going to their website.
Oh, you are talking about this https://help.openai.com/en/articles/8590148-memory-faq hahahaha. I’m sorry man, but you are a moron or arguing in bad faith. That’s yet another feature where they inject even more shit in the context/input to make it feel like the thing has memory. That’s literally yet another example of what I was pointing out, so thanks for confirming my suspicions. Seriously dude, do better if you really want to have a conversation. Your response made me waste my time, and on top of that you insult me hahaha.
