Like it or not, this is exactly what normies have always wanted out of search engines - a little guy in their computer they can talk to for answers, advice and reassurance. They've always been trying to use Google Search this way and have been confused and annoyed that it doesn't work. And now it does! It's a massive quality of life improvement for the average user and a huge product win for Google.
Its also why Google Search "went to shit years ago"
Technically adept people would search using ordered keywords and phrases, which would have excellent results with Google 2006:
Dario Turkey NBA "never coming over"
But regular people agonized over this because to them a search was
What were some of the memes about Dario staying in turkey
Google put immense effort into calibrating search for regular people instead of engineers.
Christ, thank you! I’ve been saying this for years and no one I’ve spoken to, even engineers, could acknowledge the level of “chunking” that’s been engrained in them over the years for turning inquiries into keyword/phrase shorthand, and that this is NOT something most people want to do, and is the killer app of Google AI. This time around, you CAN type in an input box what you would say to a human in everyday conversation, AND expect a reasonable response. That’s invaluable to a casual user.
> this is NOT something most people want to do
I've always felt that "proper" and responsible LLM use for search [0] would be two boxes: You can describe what you want in the first, and it'll propose search terms in the second, and then those get executed normally.
Yes, the "average user" [1] might not usually care about the second box... Until they need to because the query/results are wrong.
Showing them in tandem means:
1. Users are at least capable of learning through exposure.
2. Users may realize a key term can be added which the model could never have guessed.
3. Users may recognize a term in there that doesn't make sense, allowing them to detect a translation error.
4. If good search-terms leads to a bad outcome, it is possible for someone to report and diagnose it, rather than a fully black-box mystery.
_____
[0] Not just for websites, but also things like internal business software, or SQL queries.
[1] The average that might not exist. ( https://www.thestar.com/news/insight/when-u-s-air-force-disc... ) There are some features that everybody needs, just at different times.
Your described thinking pattern does not apply to 95%+ users, and might add confusion leading to retention loss (e.g. 2 text boxes? Wtf, two boxes? What do i type in the second one? Whatever i’ll switch to the usual). Every project with at least 100K non-tech users I’ve worked on, has shown that sort of thinking just doesn’t translate.
And regarding “average doesn’t exist” - that’s true. But no company does a/b testing to land on average. I’d assume a good 85%-kinda pass rate for these type of experiments.
If you are a fast typer, maybe the longer query might just come out naturally.
If you are properly lazy, you must expect or at least attempt to get results for the shorter query. Especially on a phone.
It's not about shorter vs longer.
Many people who learned to search the Internet in early 2000s learned "boolean search queries" (terms connected with AND or OR). They're talking about the difference between boolean search queries and natural language search queries.
I'm not sure about this. I know complete normies that lament how bad Google is now and how often the search is useless. I think many people just want search to search.
Like, today, or the pre-chatgpt age where all the common questions have been spammed to death by SEO farms?
Google's search has been frustratingly awful for quite some time now, long before AI.
Today I googled "emacs" to get the download link.
Top of the search result page: "Did you mean: vim"
Felt like I was being trolled.
That's an Easter egg. It goes the other way too (vim -> did you mean emacs).
Back in the day, more people might have seen something like that as a clever easter egg.
These days, we default to
"Day 3,449: google's still broken. what was i thinking?"
It's an Easter egg. HN discussion: https://news.ycombinator.com/item?id=25371017
Every complaint about Google is evidence of someone who still uses Google.
Googles quality issue seem to be, in part, a market driven choice. Services like Kagi use a large part of the Google data base but with all their additional capital extraction sorting on top.
Google can do it, but they must appease the share holders.
I fail to see how driving users to competitors and crippling the search experience appeases the shareholders. Can you elaborate?
So if enough 737's crash into the water Boeing will start making submarines? Product managers deserve a special express queue when in line for the Warm Place.
>So if enough 737's crash into the water Boeing will start making submarines?
Maybe?
https://en.wikipedia.org/wiki/Post-it_note
>In 1968, Spencer Silver, a scientist at 3M in the United States, attempted to develop a super-strong adhesive. [...]
>Post-its were launched across the United States in 1980.[20][21] The following year, they were launched in Canada and Europe.[22] Post-it Notes as we know them were patented by Fry in 1993 as a "repositionable pressure-sensitive adhesive sheet material".[23]
Another one that to me is equally impressive: instant glues
https://en.wikipedia.org/wiki/Cyanoacrylate
The first thorough research went into them when looking for new clear plastics, and this route of making them was ruled out because it would rather stick to everything than ease the production of objects with nice optical properties. The story goes, it was so annoying to work with that it was initially shelved, and only years after being considered again and ruled out again for a different project, the utility of its reliable and fast bonding was fully appreciated.
No, we did not want it to offer weirdly irrelevant fake sympathy. We just wanted to talk in plain English and get relevant answers back in plain English, without us having to reel it it from going down some emotionally schizophrenic rabbit hole (like in TFA).
In TFA the chatbot got confused, and the author never decided to correct it with "no I'm trying to find an old tweet about NBA Dario" which a normie would do, and be satisfied with the result.
always the same response: "you're holding it wrong"
I think they are really pulling a "no true Scotsman".
"No true normie would be dissatisfied with this unhelpful response, really it's exactly what a true normie wants"
I was always taken aback when I’d see people type fully formed sentences into an old Google search, when a couple keywords would have done just fine.
It reminds me of the motion controls we now have in video game controllers. In the 80s I remember my parents moving the controller as if that was going to help their Teris block or Mario go a little further than the D-pad alone. We laughed when people did this. Now, the controllers respond to what people had been doing for decades with no effect.
I suppose this is what technology should do, adapt to how people naturally use the thing, rather than trying to rigidly adhere to conventions users are expected to learn… that were only conventions due to the limits of technology when it was first developed.
I understand this is the prevalant narrative coming from the "users just want star trek" google, but I've got to wonder what long-term impacts focusing on users who don't understand software (or even what they're looking for) will be. It's probably fine or positive for short-term revenue, but this is also culture loss: the users who know what they want will move on to more functional software. 100% of the feedback I've seen about recent changes has been frustration that a reliable tool has stopped working. Obviously, this is selection bias but it's still meaningful.
And the impact on discourse has been, frankly, scary. People screenshotting the search output as a source seems to be the norm now, even if it's obviously incoherent or straight-up incorrect.
I'm going to agree and disagree.
I agree that plain language queries is what people wanted. We've been seeing Google shift in that direction for well over a decade. And of course people are looking towards search engines for answers. There may be different expectations for where those answers are coming from, and there are cases where people are simply trying to source information, but those differences are likely just noise as far as Google is concerned.
I don't agree with people expecting advice or reassurance from a search engine. There will be some people who do that. It may even be a sizeable number of people. But using this article as an example that a majority of people want such a thing is silly.
I mean, look at the query. To the author, it was an attempt to source information. Yet the author also realised that the reader would need context to understand why Google's response was weird in their mind. What they failed to do was give context to Google, so the LLM interpreted it as asking for social advice.
New technology requires new approaches. It's as simple as that.
The big selling point of Google used to be that their fuzzy search was significantly better than just about anyone else, and you could do advanced query filters. Now if you do that, because showing the user zero results is unacceptable, you’ll get all sorts of crap that “doesn’t contain” your query - the results say so!
But anthropomorphic interfaces have been around for a while, from Clippy to the Windows 10+ installers that refer to the royal We during setup.
> What they failed to do was give context to Google
The context is: "I'm using the premier web-search engine of the internet to search for things on the internet the same way that zillions of people have searched for things on the internet for 20 years."
It's not missing, Google simply chose to build something new that will ignore it because they're trying to alter the relationship.
I absolutely despise when people cite google as a source, especially now where 90% of the time they're citing the LLM overview. The old answer widget was at least a direct quote from some website.
How on earth did you figure out what the 'average' person wants? 'Average' by the way doesn't exist, its an artificial math concept. What people want is an endless list of things and a bot no longer being objective, as in just addressing the search query, isn't one of those things.
Yeah - exactly this. And yet people still say they've lost the AI race because Gemini 3.5 Pro or whatever has not been released yet... And here we are with fast and decent AI being served to and used by billions of people (most without them probably even realising), making ever-increasing revenue, gaining back market share etc. Who cares if their coding models are not as good as opus 5.5 when they're printing more and more money every quarter.
Gemini is easily the single most popular LLM family used in the world, period.
As in, it probably has 90% of the market share. Possibly even 99%, going by number of prompts made.
This is not a “gotcha” kind of argumentative question, I am genuinely asking curiously: is the AI overview and AI lens thing really making Google lots of money?
I don't think directly, but search as a business category was once a solved domain with a single winner, and suddenly it was up for grabs again with LLMs. If Google ever lost search, they would lose Ads which is their entire core business. Google 'won' in the sense that they successfully integrated AI into search fast enough and well enough that they will (likely) hold their place through this transition, and can still funnel ads to users which is already integrated into their AI overview.
It's true that Google is still very successful, but simply calling their AI a successful product misses the full picture. Their flagship product has always been and continues to be advertising, the AI overview is only there to pull people away from ChatGPT and, similar to ChatGPT itself, is not a product the vast majority of people would be interested in paying for - it exists only as a sort of loss leader to keep people looking at ads, and is not making any sort of profit on its own (quite the contrary, I imagine it's pretty expensive to run every query through an LLM, even if it's a small one.)
AI labs have long since realized that the only real path to direct profitability is coding, and in this, Google have indeed fallen behind.
You can, of course, argue that none of this matters as long as the whole is making a profit, but I think the distinction is important.
When I was in grade 8 and 9 in public school, we'd got a couple random lessons in the library on the computers learning to search online databases and catalogues. For most of us it was our introduction to keyword matching and boolean logic. Sadly, instead of continuing teaching, services have instead phased out those basic operators and here we are. We also learned to make websites using Pagemaker and edit the generated html, that was just fun.
This is also why even lowest-intelligence emoji spamming slop models from ChatGPT are a massive hit
and something like 3% of LLM userbase pays to get access to the higher tier models with actual useful thinking
If it's thinking I want, I can do that myself. Chat bots are occasionally useful search tools, but thinking doesn't really help with that. So why pay?
No it isn't.
The debate doesn't end there yet because what's considered a "scam" is a point on the gradient of user acceptance.
Too many users still reject this for it to not be a scam. The highest acceptance is from boomers and the delusional. Neither group gives a shit if AI actually works because they don't have work to do.