To be fair Google's results have been shite since the SEO arms race in about 2014.
this post was submitted on 22 Sep 2026
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Yeah, I use other search engines.; they might not be that much better but at least they don't start off with scams and "suggested" websites.
Ditching Google is good, but not for AI. We should take the ditching part and redirect the young people to use other search engines.
Ditching Google is good, but not for AI.
LLMs and their precursors were always how search engines compiled and ranked their search results. Google has been using some form of AI to build up its base of information for decades.
The absurd turn of the last decade was Google C-level pivot from engagement through useful results to engagement through bad results that force you to click around on the site longer. "How do we get more ad interaction?" became the question that dominated the development of their technology.
That's what enahittified their website. Not "AI".
given that by LLMs, people generally refer to the transformer architecture, it definitely wasn't how google always did search. they famously started out by using pagerank. now, back then this was definitely seen as AI, but what gets called ai by the general public has changed over the last couple of decades. now people use it almost exclusively to refer to deep learning models or even just llms.
so yes, in a strict sense google has always used ai for search. but when the general public says AI now, they usually mean llms specifically and using that to replace actually going to the source websites is new
they famously started out by using pagerank
Pagerank was built on the Markov Model, which became the core of modern LLM graph design.
It was a precursor technology, not an independent system, which used Hyperlinks rather than word tokens to form associations.
they usually mean llms specifically and using that to replace actually going to the source websites is new
So much of the complaint around AI isn't even the LLM part. It's the weighting and censorship of certain sources and data, convinced with the masking of results behind natural language output templates.
You had the first problem under Pagerank already (Google Bombing and "shadow banning" of sources the company didn't find reliable). The second is entirely a product of the interface and has nothing to do with the heuristics of the program.
sure both pagerank and llms can modelled as marlov chains, but the working and output of these models is very different. it's disingenuous to state that google used llms and their precursors since the beginning. their precursors maybe but they are very different beasts.
as for the complaints, for me a big problem of their use in search engines is that they often hide the sources of the summary they provide and disincentivize people from clicking through to the source sites. This is very much a new problem that didn't exist before google included output from generative models
Search is probably one of the few "ok" uses for LLMs if you find a way to reduce the carbon footprint and train on ethical material
Which, up until maybe eight or nine years ago, Google was pretty good at.
But then we went into this insane build-out cycle, where you were seemingly incentivized to be extra sloppy with every aspect of the business.
I think we need more solutions like Kagi, but less expensive.
Since you're the customer, no ads are served to you, and the search results are in your best interest and can be fully customized.
Since you’re the customer, no ads
I remember the streaming services making this claim when they first took off.
Oof :(
Yeah. It's almost impossible to create a system grounded in ethics in a hyper-capitalist architecture. Misinformation is by its very nature more entertaining and easier to make, so the unavoidable market incentive is to eventually shift the revenue base away from a broad, but low capitalization user base toward the handful of high capitalization snake-oil mongers. It's a direct product of market concentration that's allowed a handful of talented liars to accumulate more wealth than the majority of the rest of humanity.
I thought Kagi was expensive until I used it for a year. Worth every penny.
I'm Canadian and their prices aren't adjusted per market, so it's pretty expensive for us. It's about the price of YouTube Premium for a base plan. (I'll go double check)
Edit: nope, YT Premium is a wild $27 CAD now, far from the $14 CAD for the cheapest unlimited search Kagi plan lol
$5 a month is really not expensive, though. That's less than the price of a AAA game for a full year. Google is only free because they make their money selling user data. How cheap does a good search engine need to be?
I'm not considering the 300 searches plan, I bust that basically instantly. The minimum plan I can use is the $10 USD, which is about $14 CAD.
That's wild to me; I feel like I search a lot, and I only go over the 300 searches rarely. Those few times I do, it's painless to just start the cycle a few days early.
I'm not who you replied to, but in the same boat as him. I burn through 300 in a week, let alone a month. In my kagi settings I can see I make around 1100 searches each month. That 300 limit is just not possible for me
Interesting! I guess I must search a lot less than I feel like I do. I do some things like type in URLs rather than searching for a known URL, and going to Wikipedia directly and then searching there; maybe that stuff helps more than I'd think? Or maybe we just use the Internet differently, which is fine too.
ah, yeah, I am not sure I have ever seen a website have decent search of its own so I use Kagi for basically every search lol. I just enter my query then add "site:site.com" to the end to limit it to results from that site
You also probably don't use it for spell check when a random system doesn't have it built in. I mean, I totally don't do that.... 🤣
Haha if I did I'd just go to wkitionary.com and search there or something
I mean that would make more sense...
More? I dunno, only if you're trying to minmax searches, which I apparently do. Just different. 😎
No I mean you're doing something that makes sense and I feel silly for not thinking of it lol
I mean Google made its own bed here. Their chronic enshitification because they thought they were invulnerable really means the digital landscape doesn't have a solid accessible alternative and "Web 2.0" capitalization of network effects to concentrate attention means viable competition is always going to be niche.
This is mostly the fault of the tech giants, but if we're being honest, we all played a role in letting it get this bad. Kids are just following the path of least resistance.
Google has been just good enough for it not to start a mass exodus to alternatives. Even if those alternatives are just google/bing front-ends themselves with no real indexing of their own.
But Google is pushing its own AI at the top of its searches. As if search is going to "soon be deprecated".
I think the SEO blogspam was already contributing to brain rot but not to the extent that 5 years of AI generated blogspam ingested to the models, fed to people without critical thinking abilities.
Test it on topics you’re going to dig into already (to minimize work), and you’ll quickly find how horrifying this practice is.
My favorite is when the bot “infers an answer based on what information is available”, in other words, makes shit up, instead of saying “I don’t know.”
It won’t tell you it’s doing this unless you demand source material. Spoiler: what is linked below the answers as source material can be completely unrelated to the response. Like cited sources in an Ann Coulter book.
And even when you do, it may not accurately respond with it. Companies are conflating complicated word-relationship math with "information", and there's no means by which these systems can actually verify that something that came out is accurate or not, since language models just don't work that way. They can straight up point at sources that're real but make the wrong conclusion because the word relationships lean that way in relation to what was quoted, and no "this new model is better!" can really solve that fundamental flaw with Large Language Models in general, or things that operate like they do.
Watson was groundbreaking because of the way it worked as an information match model, designed not to be generative but merely to match one prompt "concept" with a target scored on relations. It was almost like how LLM scoring works but fundamentally still different, with a TON of hand-training done to get there. And I was just thinking about, the other day, how much I think these companies want people to correlated what Watson was doing on Jeopardy with LLMs.
As if Google and other big providers deciding that giving you bad results so you'd have to view ADs for longer wasn't bad enough for the young people's ability to critically think and find information...
Now they're going to AIs that'll outright lie to them with confidence of someone about to say "I told you so".