Search is primarily a portal - you know a particular resource exists, you just don't know its exact URL.
You hear about this new programming language called "Frob", and you assume it must have a website. So you google "Frob language". You hear that there was a plane crash in DC, and assume (CNN/AP/your_favorite_news_site) has almost certainly written an article about it. You google "DC plane crash."
LLMs aren't ever going to replace search for that use case, simply because they're never going to be as convenient.
Where LLMs will take over from search is when it comes to open-ended research - where you don't know in advance where you're going or what you're going to find. I don't really have frequent use cases of this sort, but depending on your occupation it might revolutionize your daily work.
IMO an example of a good use case for an LLM, which would be otherwise very hard to search for, is clarifying vague technical concepts.
Just yesterday I was trying to remember the name of a vague concept I’d forgotten, with my overall question being:
“Is there a technical term in biology for the equilibrium that occurs between plant species producing defensive toxins, and toxin resistance in the insect species that feed on those plants, whereby the plant species never has enough evolutionary pressure to increase it’s toxin load enough to kill off the insect that is adapting to it”
After fruitless searching around because I didn’t have the right things to look for, putting the above in ChatGPT gave an instant reply of exactly what I was looking for:
“Yes, the phenomenon you're describing is often referred to as evolutionary arms race or coevolutionary arms race.”
While I do like LLMs for these tasks, unfortunately this one failed you but was a near enough miss that you couldn't see it. What you were really looking for is the Red Queen problem/hypothesis/race, named after a quote from Through the Looking Glass, with the Queen explaining to Alice: "Now, here, you see, it takes all the running you can do, to keep in the same place." In particular, the Red Queen term is specifically the equilibrium you inquired about, where relative fitness is unchanging, rather than the more general concept of an evolutionary arms race in which there can be winners and losers. The terms 'evolutionary equilibrium' and 'evolutionary steady state' are also used to capture the idea of the equilibrium, rather than just of competition.
Evolutionary arms race is somewhat tautological; an arms race is the description of the selective pressure applied by other species on evolution of the species in question. (There are other, abiotic sources of selective pressures, e.g. climate change on evolutionary timescales, so while 'evolution' at least carries a broader meaning, 'arms race' adds nothing that wasn't already there.)
That said, using your exact query on deepseek r1 and claude sonnet 3.7 both did include red queen in their answers, along with other related concepts like tit for tat escalation.
This is an incorrect response.
Firstly, "Evolutionary Arms Race" is not tautological, it is a specific term of art in evolutionary biology.
Secondly, "evolutionary arms race" is a correct answer, it is the general case of which the Red Queen hypothesis is a special case. I do agree with you that OP described a Red Queen case, though I would hesitate to say it was because of "equilibrium"; many species in Red Queen situations have in fact gone extinct.
I disagree that evolutionary arms race is a specific term of art; we have many specific terms of art but 'arms race' is a broad generalization popularized by Dawkins as a pop science writer addressing a lay audience. Actual terms of art in this area would include Red Queen, the many individually termed coevolutions (antagonistic, mosaic, host-parasite, plant-herbivore, predator-prey etc), coadaptation, coextinction, the escalation hypothesis, frequency-dependent selection, reciprocal selection, asymmetric selection, the evolutionary lag, evolutionary cycling, character displacement, Fisherian runaway, evolutionary mismatch/trap, (phylogenetic) niche conservatism, fitness landscape, Grinnellian vs Eltonian niches, the competitive exclusion principle, and on and on. All of these actual terms of art fit under the broad, general umbrella of an 'arms race' with other species, which is really nothing more than a restatement of Spencer's unfortunate phrase. The latter is so widely 'known' that it is to the point that I and many of my peers try not to utter it, in an effort to reduce the work refuting the same tired misunderstandings that arise from that verbiage.
At any rate, almost NONE of these actual terms of art are about the sort of equilibrium that was the exact heart of the OP's query to the LLM, and thus nearly none of the broader umbrella 'arms race' is about why the plant doesn't have the evolutionary pressure to actually drive the parasite extinct. An arms race doesn't have to be in equilibrium. Armor vs weapons were in an arms race and indeed at equilibrium for millenia, but then bullets come along and armor goes exinct almost overnight and doesn't reappear for 5 centuries. Bullets win the arms race. Arms races have nothing to do, inherently, with equilibrium.
You seem to have misunderstood the nature of the equilibrium in a Red Queen scenario, which is the fundamental effect that the hypothesis is directly named for. That species that are in Red Queen relationships can go extinct is in no way a counterargument to the idea that two (or more) species tend to coevolve in such a way that the relative fitness of each (and of the system as a whole) stays constant. See, for example, the end of the first paragraph on the origin of Van Valen's term at your own wiki link.
Evolutionary steady-state is a synonymous term without the baggage of the literary reference and also avoids the incorrect connotation suggested by arms race that leads people to forget the abiotic factors that are often a dominant mechanism in extinctions as the realized niche vs the fundamental niche differ. Instead, Van Valen was specifically proposing the Red Queen hypothesis as an explanation of why extinction appears to be a half-life, i.e. of a constant probability, rather than a rate that depends on the lifetime of the taxa. This mechanism has good explanatory power for the strong and consistent evidence that speciation rate (usually considered as the log of the number of genera, depending on definition, see Stanley's Rule) has a direct and linear relation with the extinction rate. If Red Queened species didn't go exinct, Van Valen wouldn't have needed to coin the term to explain this correlation.
Or were you deliberately invoking Cunningham's Law?
> this one failed you but was a near enough miss that you couldn't see it. What you were really looking for is the Red Queen
GP was looking for a specific term that they had heard before. It was co-/evolutionary arms race, and ChatGPT guessed it correctly.
Also GPT-4o elaborated the answer (for me at least) with things like:
> However, the specific kind of equilibrium you're referring to—where neither side ever fully "wins", and both are locked in a continuous cycle of adaptation and counter-adaptation—is also captured in the idea of a “Red Queen dynamic”. > You could refer to this as: * Red Queen dynamics in plant-insect coevolution * A coevolutionary arms race reaching a dynamic equilibrium * Or even evolutionary stable strategies (ESS) applied to plant-herbivore interactions, though ESS is more game-theory focused.I tested that prompt with multiple chatGPT models, Claude Sonnet 3.7 and Deepseek and all mentioned the red queen. Just saying.
I just want to say that this thread / the responses to your question are better than either search engines or LLMs can ever come up with, and shows the truth of Cunningham's Law: "The best way to get the right answer on the internet is not to ask a question; it's to post the wrong answer"
Or updated for the LLM age, "the best way to get the right answer from an LLM is not to ask it a question and use its answer; it's to post its response on a site of well-educated and easily nerdsniped people"
The responses to GP's comment are surprisingly entertaining to read. I'm entirely engaged in this nerdy semantics war on a topic I know nothing about and loving it.
Time to pop some popcorn and hit refresh.
Same. This is one of the few uses for LLMs that I actually find useful and that I trust.
They’re very helpful for helping me ask more refined questions by getting the terminology correct.
That's the truth behind finding answers; it's not about finding the answer, it's about asking the right question.
Agreed. I'm increasingly using ChatGPT to research topics. In that way, I can refine my question, drill down, ask for alternatives, supply my own supplementary information, etc.
I think of AI as an intelligent search engine / assistant and, outside of simple questions with one very specific answer, it just crushes search engines.
I don't see it as crushing the search engines.
I use the LLMs to find the right search terms, and that combination makes search engines much more useful.
LLM by themselves give me very superficial explanations that don't answer what I want, but they are also a great starting point that will eventually guide me to the answers.
Likely because I'm asking specific Python development questions, I'm getting specific answers (and typically 2-3 variations) that I can drill down into. That response is likely different than for a more general question with a wider array of possible answers.
it's especially great in voice mode. I love to take a long walk or jog with earbuds in and use it to learn a new topic. I don't well through indoctrination, I learn much better by asking it to give a very big picture overview, start to build an intuitive understanding, and then start asking pointed questions to fill in the blanks and iterate towards a deeper understanding. I find ChatGPT's voice mode to be very engaging in that use case—far more so than Gemini's actually—and I've used it to learn a bunch of new technologies. It's like having a never-bored professor friend you can call and ask endless questions and keep getting answers without annoying it!
Yeah, I find setting it in voice mode and then directing it to a specific site that I'm interested in discussing is super useful, so I start off in ChatGPT*, then I switch windows to what I'm interested in looking at. For instance, I want to go over a GitHub repo. I can ask it to verbally ask it to go there and then chat with it as I read through the README file, and it provides great a soundboarding experience. No pun intended. Heck, I'm even dictating this response through Wispr Flow, which I have found to be more useful than I had anticipated.
* Gemini lets you do this by actually streaming your screen through and verbally chatting about whatever is on screen. While interesting, I find the responses to be a little less thorough. YMMV.
It is extremely dangerous to believe that anything said by an AI assistant is correct.
Even with supposedly authoritative peer-reviewed research papers it is extremely frequent to find errors whenever the authors claim to quote earlier work, because the reality is that most of them do not bother to read carefully their claimed bibliography.
When you get an answer from an AI, the chances greatly increase that the answer regurgitates some errors present in the publications used for training. At least when you get the answer from a real book or research paper, it lists its sources and you can search them to find whether they have been reproduced rightly or wrongly. With an AI-generated answer it becomes much more difficult to check it for truthfulness.
I will give an example of what I mean, on which I happened to stumble today. I have read a chemistry article published in 2022 in a Springer journal. While the article also contained various useful information, it happened to contain a claim that seemed suspicious.
In 1782, the French chemist Guyton de Morveau has invented the word "alumine" (French) = "alumina" (Latin and English), to name what is now called oxide of aluminum, which was called earth of alum at that time ("terra aluminis" in Latin).
The article from 2022 claimed that the word "alumina" had already been used earlier with the same sense, by Andreas Libavius in 1597, who has been thus the creator of this word.
I have found this hard to believe, because the necessity for such a word has appeared only during the 18th century, when the European chemists, starting with the Swedish chemists, have finally gone beyond the level of chemical classification inherited from the Arabs and they have begun to classify all known chemical substances as combinations of a restricted set of primitive substances.
Fortunately, the 2022 article had a detailed bibliography, and using it I was able to find the original work from 1597 and the exact paragraph in it that was referred to. The claim of the 2022 article was entirely false. While the paragraph contained a word "alumina", that was not a singular feminine adjective (i.e. agreeing with "terra") referring to the "earth of alum". Instead of this, it was not a new word, but just the plural of the neuter word "alumen" (= English alum), in the sentence "alums or salts or other similar sour substances can be mixed in", where "alums" meant "various kinds of alum", like "salts" meant "various kinds of salt". Nowhere in the work of Libavius there was any mention of an earth that is a component of alum and that could be extracted from alum (in older chemistry, "earth" was the term for any non-metallic solid substance that neither dissolves in water nor burns in air).
I have given in detail this example, in order to illustrate the kinds of errors that I very frequently encounter whenever some authors claim to quote other works. While this was an ancient quotation, lots of similar errors appear when quoting more recent publications, e.g. when quoting Einstein, Dirac or the like.
I am pretty sure that if I would ask an AI assistant something, the number of errors in the answers will not be less than when reading publications written by humans, but the answers will be more difficult to verify.
Whoever thinks that they can get a quick answer to any important question in a few seconds and be done with it, are naive because the answer to any serious question must be verified thoroughly, otherwise there are great chances that those who trust such answers will just spread more disinformation, like the sources on which the AI has been trained.
Appreciate your perspective. To be clear, I'm using it to become a better small game developer and not relying on it to answer anything I would classify as an "important question". Moreover, I don't take everything AI tells me to be 100% accurate (and I never copy/paste the response). Rather, I use it as an assistant with which I can have a back and forth "conversation" to acquire other perspectives.
Despite a lot of effort, I'm just not a highly skilled developer and I don't have any friends / colleagues I can turn to for assistance (I don't know a single software developer or even another person who enjoys video games). While resources like StackOverflow are certainly useful, having answers tailored to my specific situation really accelerates progress.
I'm not trying to cure cancer here and much of what would be considered the "best approach" for a small game architecture is unique to the developer. As such, AI is an incredible resource to lean on and get information tailored to my unique use case (here is my code...how does {topic} apply to my situation?")
And yes, I find errors from time to time, but that is good. It keeps me on my toes and forces me to really understand the response / perspective.
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Present day...
Google 55% as GPT is not a local search engine
GPT 45% but use it for more intelligent learning/conversations/knowledgebase.
If I had a GPT phone ... sorta like H.E.R. the movie I would rarely leave my phone's lockscreen. My AI device / super AI human friend would do everything for me including get me to the best lighting to take the best selfies...
Synthesizing what would be multiple searches into one prompt is where they can be really useful.
For example: Take the ingredient list of a cosmetic or other product that could be 30-40 different molecules and ask ChatGPT to list out what each of them is and if any have potential issues.
You can then verify what it returns via search.
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that sounds like a really great example of..... searching through vector embedding. I don't think the LLM part was technically necessary.
Okay, so how does the average person search through vector embedding? I would like to try this out.
I didn't say the average person should use it, I was thinking the search functionality could be implemented that way and save on burning up the planet to tame Moloc.
If it could be implemented that way and would be helpful where Google fails, then why has nobody done this? I’d love to try this out if you can point to a product that does this.
You can criticize LLMs all you want, but the fact is that they provide value to people in ways that alternatives simply don’t. The energy consumption is a concern, but don’t pretend there are viable alternatives when there aren’t.
I don't have insight on what goes on inside Google - they may well be doing this at some level, but their business isn't finding stuff, it's selling ads, so getting the search right is a very low priority.
The LLM people are heavily invested in ever bigger models to keep the research money flowing in, it wouldn't make sense to release a service that undercuts that.
that leaves independent actors - presumably building and maintaining an up to date database is difficult, so only the big search engines do.
I don't think this is _literally_ a search through vector embeddings.
LLMs store embeddings of individual tokens (usually parts of words), so a result of an actual search will be top-k embeddings and the corresponding tokens, similar to the output of a Google search. You could extract the initial matrix of embeddings from some open-weights model and find tokens closest to your query. However, it's not clear why do this. OP got coherent text, so that's not search.
It's _similar_, though, because attention in LLMs basically looks for most similar tokens. So to answer the question about the term, the LLM had to create a stream of tokens that's semantically closest to the given description. Well, this is somewhat like a search, but it's not exactly the same.
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And the LLM won't be necessary either for the common search case of "dc plane crash" or whatever, but increasingly that will be asked of general assistance agent, and it will dispatch an internet search of some kind, and return the result. Even if it provides 0 additional benefit over google, switching the default search location might still occur, especially if it does provide some benefits (such as summarization)
It's all about the UI/UX. Same as in Dropbox/rsync
No one who extensively uses dropbox uses their UI. It's mostly either the API or rclone. It's inefficient and a complete waste of time to use any UI at all
I'd go further, and say I use search when I'm pretty confident I know the right search terms. If I don't, I'll type some wordy long explanation of what I want into an LLM and hope for the best.
The reason is pretty simple. If the result you want is in the first few search hits, it's always better. Your query is shorter so there is less typing, the search engine is always faster, the results are far better because you side step the LLM hallucinating as it regurgitates the results it remembers on the page your would have read if you searched.
If you aren't confident of the search times, it can take 1/2 an hour of dicking around with different terms, clicking though a couple of pages of search results for each set of term, until you finally figure out the lingo to use. Figuring out what you are really after from that wordy description is the inner magic of LLM's.
If the result you want is in the first few search hits, it's always better. Your query is shorter so there is less typing, the search engine is always faster, the results are far better because you side step the LLM hallucinating as it regurgitates the results it remembers on the page your would have read if you searched
Most often not true in the kind of searches I do. Say, I search for how to do something in the Linux terminal (not just the command, but the specific options to achieve a certain thing). Google will often take me to pages that do have the answer, but are full of ads and fluff, and I have to browse through several options until I find the ones I want. ChatGPT just gives me the answer.
And with any halfway decent model, hallucination only seems to be a problem in difficult or very specialized questions. Which I agree shouldn't be asked to LLMs (or not without verifying sources, at least). But over 90% of what I search aren't difficult or specialized questions, they're just things I have forgotten, or things that are easy but I don't know just because they're not in my area of expertise. For example as a learner of Chinese, I often ask it to explain sentences to me (translate the sentence, the individual words, and explain what a given word is doing in the sentence) and for that kind of thing it's basically flawless, there's no reason why it would hallucinate as such questions are trivial for a model having tons of Chinese text in its training set.
It depends. Sometimes webpages are useful, but at the same time navigating the amount of fluff on webpages nowadays takes longer than asking a LLM.
I asked Claude to give me a recipe that uses mushrooms and freezes well and it give me a decent looking soup recipe. It might not be the best soup ever, but it's soup, kinda hard to mess up. The alternative would be to get a recipe from the web with a couple dozen paragraphs about how this is the bestest soup ever and it comes from their grandma and reminds them of summer and whatnot.
> I asked Claude to give me a recipe that uses mushrooms and freezes well and it give me a decent looking soup recipe.
It didn't suggest adding glue? I imagine it would freeze real well if you did that. /s
> I'll type some wordy long explanation of what I want into an LLM and hope for the best.
Interesting, I just random words. LLM not care sentence.
We’re currently in the golden age of LLMs as search engines. Eventually they’ll subtly push products and recommendations in their output to steer you toward specific things.
You mean like the golden age of speech recognition a couple of years ago when they claimed 80% of computer interfacing will be voice only?
Golden age as in, "this is as good as it gets", rather than "it will be better in the future".
Or it could be more like the golden age of search engines. It's hard to tell which way it will go because LLMs are a new technology. Some people see only its strengths. Some focus upon its weaknesses. What matters though is the long run, when we get over our initial reactions.
More like as in the Golden Age of Google search, where the product optimized for returning the best, most relevant, most reputable results. As in, pre enshitification.
Its already stained. And it was never golden so why care?
I assume you didn't try Google in the late 90s?
I did and calling it a golden age is not wrong compared to what we have now. I was referrimg to the golden age of „voice only“ here
by "eventually" they mean "at this rate, mid-next year, if not already"
No - they are all competing for eyeballs right now. They need to solidify their positions in terms of user habits and behaviors before they start pissing people off.
Voice interfaces have become ingrained in some people's lives thanks to either their on-device thing (siri) or there being a permanent listener in their house (alexa); I suspect the same thing will happen with LLMs when they get integrated like that, which is already happening with Copilot in every editor, Gemini in every Google product, and soon enough (if not already) Apple Intelligence and co in phones.
have you tried chatgpt search? you can do "DC plane crash" or "Frob" it will come up with links to the story, but it will quickly give you a summary with links to its sources. Best thing is you can follow up with questions.
Yes, I have. If I want something to read the page for me, then that's where LLMs come in.
But what I'm talking about is when I want to read the page for myself. Waste of time to have to wait for an LLM to chew on it.
hah i use llms for that now too - "option-space 'link to <foo> lang'" and chat returns faster than the whole endeavor of opening google or putting stuff into the nav bar.
That’s my experience too. I don’t find Google or even Kagi faster for retrieving a link. All of the major LLMs can pull search results faster than I can through search websites, and then I’ve got a conversation where I can dive deeper if I want.
Agreed. I think of these as two different types of searches - “page searches” where you know a page exists and want to get to it, and “content searches” where you have a more open-ended question.
Really, for many “page searches”, a good search engine should just be able to take you immediately to the page. When I search “Tom Hanks IMDB”, there’s no need to see a list of links - there’s obviously one specific page I want to visit.
> Really, for many “page searches”, a good search engine should just be able to take you immediately to the page.
Are you feeling lucky?
Exactly :-)
Unfortunately you can’t really show ads if you take someone directly to the destination without any interstitial content like a list of links…
wrong - that's how YouTube works. 30s advert before a video on CPR.
I'd rather have a list of links with text ads I can ignore...
This is one of my favorite duckduckgo features - adding a single exclamation point after a search (“Tom Hanks IMDB !”) does exactly this
It's been pretty cool to realize that Grok 3 actually prioritizes up-to-date information: I have actually used it for both kinds of your examples, and it worked.
Still use Google for quick generic lookups, spell-checks/definitions, shopping stuff, products, or things I know will return a good result.
Grok is great for finding details and background info about recent news, and of course it's great for deep-diving on general knowledge topics.
I also use Grok for quick coding help. I prefer to use AI for help with isolated coding aspects such as functions and methods, as a conversational reference manual. I'm not ready to sit there pretending to be the "pilot" while AI takes over my code!
For the record, I do not like Google's AI generated results it spams at me when I search for things. I want AI when I choose to use AI, not when I don't choose it. Google needs a way to switch that off on the web (without being logged in).
Agree 100% I tried perplexity to "search" My use case was similar to one described above.
I know what I'm looking for. I just need exact URL.
Perplexity miserably fails at this.
Yes they will. Why do you think they won’t? They certainly can. You just use RAG to look up the latest news based on the keywords you are using. You can use search on the back end and never surface a list of results unless the LLM decides that is a good idea. It curates that the reusits for you. Or gives you the singular site you need with context. That is better for most searches.
I am going to cite you in a decade. Already today ChatGPT is _far_ better than Google. Instead of finding a keyword optimized page for "frob language", I can get the objectively best sources for frob language and even find the best communities related to it. Zero frob ads, zero frob-optimized pages that are designed to trick google, etc.
Traditional search is dead, semantic search through AI is alive and well.
I can't yet count once AI misunderstood the meaning of my search while Google loves to make assumptions, rewrite my search query, and deliver the results that pay it the best which have the best ads (in my opinion as a lifetime user).
Lets not even mention how they willingly accept misleading ads atop the results which trick the majority of common users into downloading malware and adware on the regular.
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LLMs already replaced that news example for me. Especially grok is really good at summarizing the state of reporting for current events like plane crashes
Yea 'needle in a haystack' style search is something that LLM based search is simply not as good at.
The reason Google is still seeing growth (in revenue etc.) is that for a lot 'commercial' search still ends with this kind of action.
Take purchasing a power drill for example, you might use an LLM for some research on what drills are best, but when you're actually looking to purchase you probably just want to find the product on Home Depot/Lowe's etc.
Except when search engines bury the thing you're obviously looking for under an entire page of sponsored ads, then that convenience argument starts to not hold up as well...
If LLMs aren't already doing this, they certainly will soon. And it'll be even more insidious and "invisible" than sponsored search results.
This is the biggest argument in favor of subscription-based funding models for search I've heard. (Kagi et al.)
Ad-sponsored models are going to be dead as soon as people realize they can't trust output.
And because the entire benefit to LLM search is the convenience of removing a human-in-the-loop step (scanning the search results), there won't be a clear insertion/distinction point for ads without poisoning the entire output.
You'd hope so, but it's still an uphill battle to get people to only work with financial advisors who have a fiduciary duty to their client, rather than working with advisors who get kickbacks.
Granted, most markets are bifurcated.
Those who can afford, buy unbiased.
Those who cannot, accept biased free services.
I suppose that's Google's hope for how future search turns out.
There is no exclusive-or between business models, there is an inclusive-or.
Over time subscription models will converge to subscription with advertisements. Like newspapers did.
And streaming services. People really thought streaming would be the end of TV commercials. Ha!
It absolutely has been for me. It'll be a cold day in Hell before I pay money for something that's ad-supported. It's why I won't touch Hulu with a 10-foot pole, it's one of many reasons why I will always pirate Windows, and it's why I laugh at cable Internet salesmen when they sing their praises for bundling in TV.
Ads xor payment, or else you can fuck all the way off.
Define ad infinitum
What you don't get with pay TV
Available eyeballs will be sold.Originally for cable, but then you got ads with cable. Then for streaming, but then you got ads with streaming. Physical DVDs? Ads. Paid Roku device? Ads. Paid windows installation? Ads.
What if the advertiser's product or service is objectively (according to either a prompt defined by the user or by the UI operator, transparently provided) the answer to the query?
Then the response will also contain ads for things that are not the answer to the query. This is how search engines currently behave.
Example from my work. Many of our customers will search for our company name in order to find the login page. I've watched them do this over screen share.
When they do that, the top search result is an ad slot. The second search result is our login page.
We buy ads against out own company name so that we can be the ad slot as well as the first result. Otherwise a competitor who buys ads against our company name could be the top slot.
Or a phisher could buy the ad slot or game the search results to publish a fake login page to phish credentials. This is why 2FA is not really optional anymore for anything of value.
I'm actually surprised that llms aren't pushing us towards products yet.
Except when LLM providers bury the thing you're obviously looking for under an entire page of sponsored ads (buy Diet Coke™!), then that convenience argument starts to not hold up as well...
When I search 'dc plane crash' in Google, Bing, and DuckDuckGo I don't get results buried under ads. When I search 'air conditioner for sale' I do get ads at the top of each of those, but that's more okay because I am looking for things to buy. And it's easy to look past the ads to get to sites like home depot or other traditional retailers that come up not just because they purchased ad space.
It helps that decent ad-blockers also tend to be able to block sponsored results.
Paying for ad-free search engines do exist as an alternative, sucks a lot for the ones who cannot afford such a luxury but at some point I noticed that for my life search is quite important, both personally and professionally, so I haven't minded paying for it after the free experience provided by Google, Bing, etc. started worsening.
Do you not use an ad blocker?
install uBlock Origin
And most of the actual results from said search are nothing but LLM generated slop content that provide zero utility to the user and only exist to capture as many clicks and traffic as possible so they can shovel as many ads as possible. The current web is practically unusable.
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>LLMs aren't ever going to replace search for that use case, simply because they're never going to be as convenient.
What? On Planet Earth, this is already a thing.
> Search is primarily a portal - you know a particular resource exists, you just don't know its exact URL.
Kind of like a manual, with an index.
RTFM people.
>LLMs aren't ever going to replace search for that use case, simply because they're never going to be as convenient.
Sounds trivial to integrate an LLM front end with a search engine backend (probably already done), and be able to type "frob language" and it gives you a curated clickable list of the top resources (language website, official tutorial, reference guide, etc) discarding spam and irrelevant search engine results in the process.
That's called a search engine. We've had them for 30 years. Ahhhhhhhhhhhghh. It's blockchain all over again.
>That's called a search engine. We've had them for 30 years
https://news.ycombinator.com/item?id=9224
The LLM could "intelligently" pick from the top several pages of results, discard search engine crap results and spam, summarize each link for you, and so on.
We don't have that now (or for 30 years - I should know, I was there, using Yahoo!, and Altavista, and Lycos and such back in the day).
I think you mean it's SOAP all over again.
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If you wanted to know more about a new programming language named “Frob” or a plane crash that happened today, couldn’t you use an LLM like grok?
Or any other LLM that’s continuously trained on trending news?
How do I know the LLM isn't lying to me? AIs lie all the time, it's impossible for me to trust them. I'd rather just go to the actual source and decide whether to trust it. Odds are pretty good that a programming language's homepage is not lying to me about the language; and I have my trust level for various news sites already calibrated. AIs are garbage-in garbage-out, and a whole boatload of garbage goes into them.
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They could provide verbatim snippets surrounded by explanations of relevance.
Instead of the core of the answer coming from the LLM, it could piece together a few relevant contexts and just provide the glue.
They do this already, but the problem is it takes me more time to verify if what they're saying is correct than to just use a search engine. All the LLMs constantly make stuff up & have extremely low precision & recall of information
I don't understand how that's an improvement over a link to a project homepage or a news article. I also don't trust the "verbatim snippet" to actually be verbatim. These things lie a lot.
> How do I know the LLM isn't lying to me?
How do you know the media isn't lying to you ? It's happened many times before (think pre-war propaganda)
We’re talking about the official website for a programming language, which has to reason to lie.
>Odds are pretty good that a programming language's homepage is not lying to me about the language
Odds are pretty good that, at least for not very popular projects, the homepage's themselves would soon be produced by some LLM, and left at that, warts and all...
None of the LLMs (not even Grok) are "continuously trained" on news. A lot of them can run searches for questions that aren't handled by their training data. Here's Grok's page explaining that: https://help.x.com/en/using-x/about-grok
> In responding to user queries, Grok has a unique feature that allows it to decide whether or not to search X public posts and conduct a real-time web search on the Internet. Grok’s access to real-time public X posts allows Grok to respond to user queries with up-to-date information and insights on a wide range of topics.
i can also use my human brain to read a webpage from the source, as the authors intended. not EVERY question on this planet needs to be answered by a high resource intensive LLM. Energy isn’t free you know. :)
Other considerations:
- Visiting the actual website, you’ll see the programming languages logo. That may be a useful memory aide when learning.
- The real website may have diagrams and other things that may not be available in your LLM tool of choice (grok).
- The ACT of browsing to a different web page may help some learners better “compartmentalize” their new knowledge. The human brain works in funny ways.
- i have 0 concerns of a hallucination when readings docs directly from the author/source. Unless they also jumped on the LLM bandwagon lol.
Just because you have a hammer in your hand doesn’t mean you should start trying to hammer everything around you friend. Every tool has its place.
It's just a different kind of data. Even without LLMs, sometimes I want a tutorial, sometimes I want the raw API specification.
For some cases I absolutely prefer an LLM, like discoverability of certain language features or toolkits. But for the details, I'll just google the documentation site (for the new terms that the LLM just taught me about) and then read the actual docs.
Search is best viewed as a black box to transform {user intention} into {desired information}.
I'm hard pressed to construction an argument where, with widely-accessible LLM/LAM technology, that still looks like:
Summarization and deep-indexing are too powerful and remove the necessity of steps 2-4.1. User types in query 2. Search returns hits 3. User selects a hit 4. User looks for information in hit 5. User has informationF.ex. with the API example, why doesn't your future IDE directly surface the API (from its documentation)? Or your future search directly summarize exactly the part of the API spec you need?
I don't know the exact word for this case, but sometimes you want the surrounding information to what you're looking for. Often I skim documentations, books, articles,... not in search for a specific answer but to get the overview of what it discusses. I don't need a summary of a table of contents. But it's a very good tool for quickly locating some specific information. Something like
orLanguage Implementation Patterns (the book) |> Analyzing Languages (the part) |> Tracking and Identifying Program Symbols (the chapter) |> Resolving Symbols (the section)
orUnit Testing: Principles, Practices,and Patterns (the book) |> Making your tests work for you (the part) |> Mocks and test fragility (the chapter) |> The relationship between mocks and test fragility (the section) |> Intra-system vs. inter-system communicationsPython 3.13.3 Documentation (docs.python.org) |> The Python Standard Library |> Text Processing Services |> stringCould never understand that obsession with summmarization. Sure, it may be be useful for long-form articles or for low-quality content farms, but most of the time you are not reading those.
And if you are reading technical docs, especially good ones, each word is there for a reason. LLM throw some that information away, but they don't have your context to know if the stuff they throw away is useful or not. The text the summary omitted may likely contain an important caveat or detail you really should have known before starting to use that API.
And if you go to a nicely formatted doc page (laravel) or something with diagrams (postgres), it throws all of these away too.
Yes, you can use grok but you could also use a search engine. Their point is that grok would be less convenient than a search engine for the use case of finding Frob's website's homepage.
Perplexity solves this problem perfectly for me. It does the web search, reads the pages, and summarizes the content it found related to my question. Or if it didn't find it, it says that.
I recently configured Chrome to only use google if I prefix my search with a "g ".