11 ms·

AI is impressive because we've failed at personal computing

206 points by ambigious7777 1y ago

thanhdotr 1y ago
is it unreasonable to expect some kind of good enough baseline guided by the prior of these llm to be the standard ? Should google's priors (or their training dataset and recipe) be allowed to guide societal's prior? same problem, different era ?
open_ 1y ago
A pretty reductionist and a poor take. "Standing on the shoulders of giants, it is clear that the giants failed to reach the heights we have reached."
ubercow13 1y ago
"AI is impressive because it solves problems better than the previous solutions"? Yes?
Kapura 1y ago
I have often thought about how computers are significantly faster than they were in the early 2000s, but they are significantly harder to use. Using Linux for the first time in college was a revelation, because it gave me the tools to tell the computer "rename all of the files in this directory, keeping only the important parts of the name." But instead of iterating on better interfaces to effectively utilize the N thousands of operations per second a computer is capable of, the powers that be behind the industry have decided to invest billions of dollars in GPUs to get a program that seems like it understands language, but is incapable of counting the number of B's in "blueberry."
- SV_BubbleTime 1y ago
  IDK, I think there is something adorable about taking a system that over trillions of iterations always performs the same operation with the same result, reliability unmatched in all of the universe… And making it more of “IDK what it answered the way it did, but it might be right!!”
  - codr7 1y ago
    Humans like games :)
- xandrius 1y ago
  Is counting the number of B's vital? Also, I'm pretty sure you can get an LLM to parse text the way you want it, it just doesn't see your text as you do, so that simple operation is not straightforward. Similarly, are you worthless because you seem like you understand language but are incapable of counting the number of octects in "blueberry"?
  - tekno45 1y ago
    if i have to talk to it a specific way, why not just use programming. The specific way we talk to computers effectively...
  - squigz 1y ago
    > Similarly, are you worthless because you seem like you understand language but are incapable of counting the number of octects in "blueberry"? Well, I would say that if GP advertised themselves as being able to do so, and confidently gave an incorrect answer, their function as someone who is able to serve their advertised purpose is practically useless.
    - xandrius 1y ago
      So ChatGPT was advertised as a letter counter? Also, no matter what hype or marketing says: GPT is a statistical word bag with a mostly invisible middleman to give it a bias. A car is a private transportation vehicle but companies still try to sell it as a lifestyle choice. It's still a car.
      - rini17 1y ago
        It is (maybe not directly but very insistently) advertised as taking many jobs soon. And counting stuff you have in front of yourself is basic skill required everywhere. Counting letters in a word is just a representative task for counting boxes with goods, or money, or kids in a group, or rows on a list on some document, it comes up in all kinds of situations. Of course people insist that AI must do this right. The word bag perhaps can't do it but it can call some better tool, in this case literally one line of python. And that is actually the topic the article touches on.
- svachalek 1y ago
  Prompt: "Spell blueberry and count the letter b". They're not claiming AGI yet, so human intelligence is required to operate an LLM optimally. It's well known that LLMs process tokens rather than characters s, so without space for "reasoning" there's no representation of the letter b in the prompt. Telling it to spell or think about it gives it room to spell it out, and from there it can "see" the letters and it's trivial to count.
  - Kapura 1y ago
    if you're going to need to learn how to use a tool, why not learn to use the efficient and precise one?
    - ubercow13 1y ago
      Because there aren't more efficient and precise tools capable of the same things?
  - cestith 1y ago
    perl -e 'print scalar grep {/b/} split //, "blueberry”' echo blueberry | grep -o 'b' | wc -l echo blueberry | perl -ne 'print scalar (() = m/(b)/g)’ echo blueberry | tr -d '\n' | tr b '\n' | wc -l echo -n blueberry | tr b '\n' | wc -l So long as I’m teaching the user how to speak to the computer for a specific edge case, which of these burn nearly as much power as your prompt? Maybe we should consider that certain problems are suitable to LLMs and certain ones should be handled differently, even if that means getting the LLM to recognize its own edge cases and run canned routines to produce answers.
throwmeaway222 1y ago
> because we've failed at personal computing ? If you really want to, you know have this super generic indexing thing, why don't you go organize the web with hypercard and semantic web crap and tell us how it worked out for you
foundart 1y ago
Expresses a longing for the semantic web. > Remember Semantic Web? The web was supposed to evolve into semantically structured, linked, machine-readable data that would enable amazing opportunities. That never happened. I think the lesson to be learned is in answering the question "Why didn't the semantic web happen?"
- neilalexander 1y ago
  > "Why didn't the semantic web happen?" Advertising.
  - throwaway346434 1y ago
    To a degree re ads on pages, but why didn't big business end up publishing all of their products in JSON-LD or similar? A lot did, to get aggregated, but not all.
- Workaccount2 1y ago
  >"Why didn't the semantic web happen?" Because web content is generated by humans, not engineers.
  - abeppu 1y ago
    But also because companies that produce web content wanted it to be seen by humans who would look at ads, not consumed by bots and synthesized with other info into a product owned by some other firm.
    - dreamcompiler 1y ago
      And yet today most websites are being scraped by LLM bots which don't look at ads and which synthesize with other info into a product owned by some other firm.
      - 1gn15 1y ago
        Optimistically, the semantic web is going to happen. Just that instead of the original plan of website owners willingly making data machine-readable, LLMs will be the ones turning non-machine-readable data machine-readable (which can then be processed by user agents), even if the website owner prefers you looked at the ads instead.
walterbell 1y ago
> If all knowledge were stored in a structured way with rich semantic linking, then very primitive natural language processing algorithms could parse question like the example at the beginning of the article, and could find the answer using orders of magnitude fewer computational resources. In vertical markets, can LLMs generate a "semantic web of linked data" knowledge graph to be parsed with efficient NLP algorithms? https://news.ycombinator.com/item?id=43914227#43926169 https://news.ycombinator.com/item?id=43914227#43926169 leveraging LLMs to build the special markup so that it can be applied towards other uses.. some type of semantic web format, like JSON-LD or OWL, or some database that can process SPARQL queries.. Palantir is using ontologies as guardrails to prevent LLM hallucinations
- nrjames 1y ago
  Palantir was 90% about ontology creation back when I first used it in 2009. They knew at that point that without some level of structure that mapped to the specific business problem that the data input into the graph was difficult to contextualize.
captainclam 1y ago
My read is that the author is saying it would have been really nice if there had been a really good protocol for storing data in a rich semantically structured way and everyone had been really really good at adhering to that standard. Is that the main thrust of it?
gsmt 1y ago
We weren't given enough time
deleted 1y ago
[deleted]
jddj 1y ago
I think every field has its own version of this thought, where if we could just manage to categorise and tag things properly we could achieve anything. Our lack of a valid overarching ontology is what is holding us back from greatness. It might be short lived, who knows, but it's interesting that the recent progress came from capturing/consuming rather than systematically eliminating the nuance in language.
- octoberfranklin 1y ago
  Every field including library science? ;)
butterisgood 1y ago
I'm pretty sure AI _is_ "personal computing". One can speak in their native language to a computer now and it mostly understands what is meant and can retrieve information or even throw together a scaffold of a project somewhat reliably. It's not particularly good at writing software, however. Still feels like a human is needed to make sure it doesn't generate nonsense or apparently pretty insecure code. So I'm not sure the author got the point across that they wished, but aren't vector databases basically a semantic storage/retrieval technology?
- ralfd 1y ago
  Yes, I rolled my eyes about the sneering of the author. By the way: His blog getting a few dozen hn comments is only impressive, because he failed to write a better blog.
octoberfranklin 1y ago
dang, please fix the title, "semantic web" somehow got deleted. if it's a space issue, "semantic web" is far more relevant to the article than "personal computing".
headcanon 1y ago
I feel like I see this attitude a lot amongst devs: "If everyone just built it correctly, we wouldn't need these bandaids" To me, it feels similar to "If everyone just cooperated perfectly and helped each other out, we wouldn't need laws/money/government/religion/etc." Yes, you're probably right, but no that won't happen the way you want to, because we are part of a complex system, and everyone has their very different incentives. Semantic web was a standard suggested by Google, but unless every browser got on board to break web pages that didn't conform to that standard, then people aren't going to fully follow it. Instead, browsers (correctly in my view) decided to be as flexible as possible to render pages in a best-effort way, because everyone had a slightly different way to build web pages. I feel like people get too stuck on the "correct" way to do things, but the reality of computers, as is the reality of everything, is that there are lots of different ways to do things, and we need to have systems that are comfortable with handling that.
- ajkjk 1y ago
  eh I feel this but it's a lot simpler than that. Not "if everyone built everything correctly" but "if everyone's work was even slightly better than complete garbage". I do not see many examples of companies building things that are not complete embarrassing shit. I worked at some companies and the things we built was complete embarrassing shit. The reasons are obvious: nobody cares internally to do it, and nobody externally has any standards, and the money still flows if you do a bad job so why do better? What happens in practice is that the culture exterminates the drive for improvement: not only are things bad, but people look at you if you're crazy if you think things should be better. Like in 2025 people defend C, people defend Javascript, people write software without types, people write scripts in shell languages; debugging sometimes involves looking at actual bytes with your eyes; UIs are written in non-cross-platform ways; the same stupid software gets written over and over at a million companies, sending a large file to another person is still actually pretty hard; leaving comments on it is functionally impossible ... these are software problems, everything is shit, everything can be improved on, nothing should be hard anymore but everything still is; we are still missing a million abstractions that are necessary to make the world simple. Good lord, yesterday I spent two hours trying to resize a PDF. We truly live in the stone age; the only progress we've made is that there are now ads on every rock. I really wish it was a a much more ruthlessly competitive landscape. One in which if your software is bad, slow, hard to debug, hard to extend, not open source, not modernized, not built on the right abstractions, hard to migrate on or off of, not receptive to feedback, covered in ads... you'd be brutally murdered by the competition in short order. Not like today where you can just lie on your marketing materials and nobody can really do anything because the competition is just as weak. People would do a much better job if they had to to survive.
MarkusQ 1y ago
Fresh plums right off the tree taste significantly better than the ones you can get in the produce isle, which are in turn better than canned, which are themselves still better than re-hydrated prunes. In scaling out computation to the masses, we went from locally grown plums that took a lot of work and were only available to a small number of people that had a plum tree or knew someone that had one, to building near magical prune-cornucopia devices that everyone could carry around in their pockets, giving them an effectively unlimited supply of prunes. LLMs re-hydrate these for us, making them significantly more palatable; if you're used to gnawing dried fruit, they seem amazing. But there's still a lot of work to be done.
- selimthegrim 1y ago
  But can it beat William Carlos Williams?
  - MarkusQ 1y ago
    they were delicious so sweet and so cold :)
- random3 1y ago
  Perhaps, but we still failed and not at personal computing, nor just semantic web, but computing and programming in general. The failure is between the original intent (computing was originally more or less AI) along with theory and actual result with every software project turning into unsustainable infinite regress. Things likely broke around ALGOL. Also LLMs are failing too, for different reasons, but IMO unlikely AI in general will— it will correct a 60 years or so failure in industrial computer science.
  - heresie-dabord 1y ago
    > we still failed [at] semantic web The most reprehensible knowledge-search-and-communication failure of all. We gave people monetisation of drek instead. Then asked them to use it for education. Then trained bot systems on it. Then said that even those answers must be made to confirm to transient propagandists.
khazhoux 1y ago
I always appreciate our weekly Crankypants Take on LLMs. > AI is not a triumph of elegant design, but a brute-force workaround You can read and understand Attention Is All You Need in one hour, and then (after just scaling out by a few billion) a computer talks to you like a human. Pretty elegant, if you ask me. > The web was supposed to evolve into semantically structured, linked, machine-readable data that would enable amazing opportunities. I missed that memo. The web was, and forever shall be, a giant, unstructured, beautiful mess. In fact, LLMs show just how hopeless the semantic web approach was. Yes, it's useful to attach metadata to objects, but you will still need massive layering and recursion to derive higher-order, non-trivial information. This entire article is someone unable to let go of an old idea that Did Not Work.
- codr7 1y ago
  Except it's all just smoke and mirrors.
  - khazhoux 1y ago
    Explain? The algorithms are surprisingly easy to understand. There is no trickery.
    - codr7 1y ago
      And the conclusions are delusional, especially given how easy it is for anyone to see there is nothing in there even resembling intelligence.
- mrweasel 1y ago
  > AI is not a triumph of elegant design, but a brute-force workaround I think the author is on to something here, but does not realize it, or applies the think to the wrong problem. The issue isn't the web, search was good enough and it's a pretty big problem to solve. We need to go smaller. Applying AI to customer service, internal processes and bureaucracy, among other things, is an inelegant brute-force approach to not just fixing your shit. The majority of customer service could be fixed by having better self-service, designing better UIs, writing better manuals, having better monitoring, better processes, better trained staff, not insisting on pumping stock numbers and actually caring about your product. AI will never fix the issues your customers are having, they'll just make customer service cheaper and worse because just like real humans the content and levers they need aren't available. Same for much of the bureaucracy in companies and governments. Rather than having AI attempt to fill out forms or judge if someone is entitled to a pension, insurance pay out or what have you. Take the time to fix your damn processes and built self-service portals that actually works (some of those may have some sort of AI on the backend for things like scanning documents). Forget the semantic web thing, it never worked, to much data, and AI generated content certainly isn't making the problem easier. Let's work on that at some other time. Still the author is correct, LLMs are a brute-force workaround, regardless of how elegant the design may be. They are applied to a host of problem that should just be eliminated, not hidden and stupefied by a prediction engine.
nicemountain 1y ago
Alan Kay has also written about his disappointment with what personal computing delivered. I think he'd agree with this. Most people can't use the power of the computers they have effectively. Maintaining the data in Excel spreadsheets for most people is like manual labour.
blurbleblurble 1y ago
Another angle: we're super over provisioned in compute resources because of reasonable limitations in how quickly we can collectively absorb and learn how to use computers. "AI" is simply a new paradigm in our understanding of how to program computers. This isn't a failure, it's just an evolution.
bkummel 1y ago
Yeah dream on. I’m an engineer and know what structured data is. And yet I miserably fail to store my private files in a way that I can find them back without relying on search tools. So how on earth are we ever going to organize all the world’s data and knowledge? Thank god we found this sub-optimal “band aid” called LLMs!
- ctoth 1y ago
  Precisely this. This article might seem reasonable to anybody who has never tried to organize something as simple as a local music collection.
  - pjm331 1y ago
    Made me think about John Wilkins' "philosophical language" which I first heard about in Neal Stephenson's book Quicksilver https://en.wikipedia.org/wiki/An_Essay_Towards_a_Real_Character,_and_a_Philosophical_Language https://en.wikipedia.org/wiki/An_Essay_Towards_a_Real_Charac... I'm sure there have been countless similar attempts at categorizing knowledge one of the more successful ones being the dewey decimal system I have my doubts about whether the thing the OP alleges we have "failed" at is even possible at all
  - whartung 1y ago
    Well, this runs straight into one of the massive, concrete pillars of computing: naming things. Because that’s what a lot of this falls into. Overwhelming amount of stuff with no names. No categories, no nothing. With extended file attributes we could hang all sorts of meta bits off of arbitrary files. But that’s very fragile. So we ask the systems to make up names for data based on their content, which turns out to not necessarily work as well as we might like.
    - jandrese 1y ago
      No names is not the biggest problem. You just have to come up with a name. The problem is when things have multiple names, or even worse when people disagree on what names are appropriate for something. The world rarely allows you to neatly categorize large datasets. There are always outliers. For example, you have a set of balls and you want to sort them by color. Where does orange stop and red begin? What about striped balls or ones with logos printed on them? What if it is a hypercolor ball that changes based on heat? It gets messy very fast.
AlienRobot 1y ago
Personal computing failed because desktop operating systems started trying to work for mobile. Everything that is bad in UI is a direct consequence of that. 1. No tooltips, right click, middle click behavior because touch doesn't have that. No ctrl+click either. 2. Large click areas wasting screen space with padding and margins. 3. Low density UI so it can shape-shift into mobile version. 4. Why type on a phone when you can talk? Make everything a search box. 5. Everything must be flat instead of skeumorphic because it's easier to resize for other screen sizes. 6. Everything needs a swipe animation and views instead of dialogs because smartphones can't have windows.
smusamashah 1y ago
How do LLMs help Google, an ad company, generate more ad revenue. LLMs drive the traffic away from websites, give you answer directly without needing bother with ads. How does it benefit Google's ad business?
- add-sub-mul-div 1y ago
  Ad clicks are a trifle compared to the possibility of winning the game of displacing vast amounts of labor and delivering ads and narratives undisclosed through conversational AI output. At that point you've won the economy, period.
  - thewebguyd 1y ago
    > winning the game of displacing vast amounts of labor and delivering ads and narratives undisclosed through conversational AI output. At that point you've won the economy, period. In a functional democracy, all you should win by doing that is harsh antitrust action.
    - add-sub-mul-div 1y ago
      Yes that's why my opposition to LLMs is contextual. If it had been invented 30 years ago I'd have been optimistic about it.
SoftTalker 1y ago
What a terrible question in the opening example. Are we playing Jeopardy?
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yen223 1y ago
How will user-generated content work in a semantic web world?
jvreeland 1y ago
I think I broadly agree with this. I am super frustrated that everythign always wants me to search for things. As an example Finders default search while looking at a folder is the whole machine instead of a filter in the directory you are viewing in seems totally insane to me. It's almost like they don't want me to know where my files are. I can understand that it's a result, to a degree of cloud services and peoples primary mode swapping to opening and app and opening recents or searching instead of opening a file to open an app but it does mean that you're at the mercy of what I experience as some pretty crap search algorithms that don't seem to want you to find the information you're looking for. I keep encountering searches that rank fuzzy matches over exact matches or aren't stable as you continue to complete the same word and I just don't understand how that's acceptable after being pointed out if search is what I'm supposed to be using.
- autoexec 1y ago
  > It's almost like they don't want me to know where my files are. I think this might actually be true in some cases. Especially where companies want your files on their cloud servers. It's better for them if you don't think about what's stored locally or remotely. It's better for them if you don't think at all and just ask them for whatever you want and let them decide what to show you or keep hidden from you. It's easier for them to get metrics on what you're doing if you type it out explicitly in a search box than it is for them to track you as you browse through a hierarchy you designed to get to what you want. You're supposed to feel increasingly helpless and dependent on them.
rglullis 1y ago
Uh, the author got so close to make the same realization I had while working on a project [0] for the Wikimedia Foundation: we wouldn't need search engines if we had better tooling to query semantic databases like wikidata. However, the thing that the author might be missing is that the semantic web exists. [1] The problem is that the tools that we can use to access it are not being developed by Big Tech. Remember Freebase? Remember that Google could have easily kept it around but decided to fold it and shoved it into the structured query results? That's because Google is not interested in "organizing the world's information and make it universally accessible" unless it is done in a way that it can justify itself into being the data broker. I'm completely out of time or energy for any side project at the moment, but if someone wants to steal my idea: please take a llm model and fine tune so that it can take any question and turn it into a SparQL query for Wikidata. Also, make a web crawler that reads the page and turns into a set of RDF triples or QuickStatements for any new facts that are presented. This would effectively be the "ultimate information organizer" and could potentially replace Wikidata as most people's entry page of the internet. [0]: https://meta.wikimedia.org/wiki/QuickStatements_3.0 https://meta.wikimedia.org/wiki/QuickStatements_3.0 [1] https://guides.library.ucla.edu/semantic-web/datasets https://guides.library.ucla.edu/semantic-web/datasets
- throwaway346434 1y ago
  ChatGPT etc does an OK job at SPARQL generation. Try something like "generate a list of all supermarkets, including websites, country, description" and you get usable queries out. In a much, much more limited way, this is what I was dabbling with with alltheprices - queries to pull data from wikidata, crawling sites to pull out the schema.org Product and offers, and publish the aggregate.
- ethan_smith 1y ago
  DBpedia Spotlight and entity-fishing already do something similar to your idea - they extract structured data from text and link to knowledge bases. Combining these with LLM-based query translation to SPARQL could indeed bridge the gap between semantic web's structure and natural language interfaces.
atrettel 1y ago
I find traditional web search and LLM search to be complementary technologies, and this is a good example of that. Both have their uses and if you get the information you need using one or the other, we are all happy. I think the example query here actually shows a problem with the query languages used in web search rather than an intrinsic inability of web search. It contains what amounts to a natural language subquery starting with "in the same year". In other words, to evaluate this query properly, we need to first evaluate this subquery and then use that information to evaluate the overall query. Google Search and almost all other traditional web search engines use intentionally oversimplified query languages that disallow nested queries let alone subqueries, so this example really is just revealing a problem with the query language rather than a problem with web search overall. With a better query language, we might get better results.
nullorempty 1y ago
Neither chat-gpt nor gemini got the same answer as the article for me ` What animal is featured on a flag of a country where the first small British colony was established in the same year that Sweden's King Gustav IV Adolf declared war on France? ` chatgpt: Final answer: Lion gemini: A lion is featured on the flag of Sri Lanka.
- autoexec 1y ago
  > Neither chat-gpt nor gemini got the same answer as the article for me getting wildly different and unpredictable answers from the same input is one of the features AI offers
- vrwarp 1y ago
  Gemini (2.5 pro) stands firm on its answer even when told that ChatGPT said it is a parrot. It does provide additional reasoning: https://g.co/gemini/share/45232dcc7278 https://g.co/gemini/share/45232dcc7278
gorfian_robot 1y ago
"pile of divs" is so accurate
antithesizer 1y ago
The essential meaning of technological progress is the utter inadequacy of humanity. We build cars that we never figure out how to safely drive, but being to arrogant to admit defeat and reconstruct society around trams like a sensible animal would do, we wait a century for cars that can drive themselves while the bodies pile up on the freeways in the meantime. Yes it's true, we can't make a UI. Or a personal computer, or anything else that isn't deeply opaque to its intended users. But it's so much worse than that. We humans can't do hardly anything successfully besides build technology and beat each other in an ever expanding array of ridiculous pissing contests we call society.
tempfile 1y ago
This take is very naive and should anticipate the obvious criticism: people did try, very very hard, to create structured information systems. They simply did not work. The sort of systems people tend to build are well-scoped for a particular problem, but fall apart completely when moving out of that domain. It is very easy to imagine an information system that results in correct answering of flag questions. It is a wide open problem to come up with a way of tagging information that works well for flag questions and for questions about memes, or art. It's not like Google didn't try!
seydor 1y ago
Chatgpt does not build semantic maps. we know it has some attention maps, but really fuzzy how it uses them
fouc 1y ago
I would argue that LLM is ultimately making true Semantic Web available, or irrelevant. It can basically figure out all the semantic knowledge graphs automatically for us, and it's multi-modal to boot. That means it can infer the relationships between any node across text, audio, images, videos, and even across different languages.
- jacobgkau 1y ago
  The question is whether humans specifying the relationships between nodes is more or less reliable than LLMs inferring those relationships.
  - svachalek 1y ago
    So we need to compare the reliability of something hypothetical to something real? I'll take the real every time.
    - jacobgkau 1y ago
      What? No. With traditional tech stacks, humans are responsible for tagging and structuring data as they input it. With AI, the argument is that the AI system can do that instead (via inference), meaning humans can input it unstructured. They're both "real." If you were trying to make a witty comment about AI's purported capabilities not existing/working well, then I personally agree that humans doing it would be smarter and more efficient.
reriufj 1y ago
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mwkaufma 1y ago
> They scan the unstructured web and build ephemeral semantic maps across everything. It's not knowledge in the classic sense.. or perhaps it is exactly what knowledge is? Betteridge's law
jkaptur 1y ago
"... if all knowledge were stored in a structured way with rich semantic linking..." this sounds a lot like Google's "Knowledge Graph". https://developers.google.com/knowledge-graph https://developers.google.com/knowledge-graph. (Disclosure: I work at Google.) If you ask an LLM where you can find a structured database of knowledge with structured semantic links, they'll point you to this and other knowledge graphs. TIL about Diffbot! In my experience, it's a lot more fun to imagine the perfect database like this than it is to work with the actual ones people have built.
throwanem 1y ago
People have said this since Vannevar Bush theorized the Memex. The unanswered question, the problem unsolved, remains: Who does all the categorization work? How come they're never part of "we," such that the plaint is never "if only we had done the work..."?
seanmcdirmid 1y ago
At Engelbart's mother of all demos in 1968, which basically birthed what we call personal computing today, most computer scientists were convinced that AGI was right around the corner and "personal computing" wasn't worth it. Now, back then AGI wasn't right around, and personal computing was really really necessary, but how did we forget the viewpoint that personal computing was seen as a competing way to use computing power vs AI?
- tempodox 1y ago
  Economic interests, walled gardens, lock-in effects. Providers learned to make it (initially) convenient for us to forget. Of course, once we’re hooked, enshittification ensues: https://news.ycombinator.com/item?id=44837367 https://news.ycombinator.com/item?id=44837367
seanwilson 1y ago
> What animal is featured on a flag of a country where the first small British colony was established in the same year that Sweden's King Gustav IV Adolf declared war on France? ... My point is that if all knowledge were stored in a structured way with rich semantic linking, then very primitive natural language processing algorithms could parse question like the example at the beginning of the article, and could find the answer using orders of magnitude fewer computational resources. So as well as people writing posts in English, they would need to provide semantic markup for all the information like dates, flags, animals, people, and countries? It's difficult enough to get people to use basic HTML tags and accessible markup properly, so what was the plan for how this would scale, specifically to non-techy people creating content?
- TZubiri 1y ago
  So wikipedia and wikidata? This actually happened already and it's part of why llms are so smart, I haven't tested this but I venture a guess that without wikipedia and wikidata and wikipedia clones and stolen articles, LLMs would be quite a lot dumber. You can only get so far with reddit articles and embedded knowledge of basic info on higher order articles. My guess is when fine tuning and modifying weights, the lowest hanging fruit is to overweigh wikipedia sources and reduce the weight of sources like reddit.
  - seanwilson 1y ago
    Only a relatively small part of Wikipedia has semantic markup though? Like if the article says "_Bob_ was born in _France_ in 1950" where the underlines are Wikpedia links, you'll get some semantic info from the use of links (Bob is a person, France is a country), but you'd be missing the "born" relationship and "1950" date as these are still only raw text. Same with the rest of articles with much more complex relationships that would probably be daunting even for experts to markup in an objective and unambiguous way. I can see how the semantic web might work for products and services like ordering food and booking flights, but not for more complex information like the above, or how semantic markup is going to get added books, research articles, news stories etc. that are always coming out.
taeric 1y ago
Leading in with what feels like a p-hacked question that almost certainly isn't typical kind of hurts the point. Reminds me of seeing clearly rehearsed demos for things that ignore the reason it worked is because it was rehearsed. A lot. Am I wrong in that this was a completely organic question?
ninetyninenine 1y ago
No AI is impressive because we built a machine that finally understands what we are saying and has a concept of what creativity is. It's rudimentary but it's a milestone for humanity. It's social media and the endless barrage of generated AI that's creating the illusion that AI isn't impressive. You're inundated everyday with the same crap and is just making it less and less impressive.
jauntywundrkind 1y ago
I sympathize so much with the failure of personal computing to manifest! > My point is that if all knowledge were stored in a structured way with rich semantic linking, then very primitive natural language processing algorithms could parse question like the example at the beginning of the article, and could find the answer using orders of magnitude fewer computational resources. And most importantly: the knowledge and the connections would remain accessible and comprehensible, not hidden within impenetrable AI models. It's a pocket hope of mine that AI brings us back to the Semantic Web, or something very like it. In many ways these embeddings are giant non-human lexicons already. Distilling this information out seems so possible. Even just making an AI to go markup (or uhh perhaps refine) a page with microdata seems conceptually very doable! More broadly, looking at personal computing: my personal belief is that failure is hugely because of apps. Instead of a broader personal computing that aggregates, that allows constructivism, that enables personal growth & development (barefoot developers & home-cooked software style), computing has been defined by massificstion, by big tech software. The dominant computing paradigm has been mainframe pattern: we the user have an app that acts as a terminal to some far off cloud-y data center. Whatever agency we get is hewn out for us apriori by product teams, and any behavior not explicitly built in is a "Felony Contempt of Business Model" (an oh so accurate Doctorow-ism)! https://maggieappleton.com/home-cooked-software https://maggieappleton.com/home-cooked-software https://news.ycombinator.com/item?id=40633029 https://news.ycombinator.com/item?id=40633029 https://pluralistic.net/2022/10/20/benevolent-dictators/#felony-contempt-of-business-model https://pluralistic.net/2022/10/20/benevolent-dictators/#fel... https://news.ycombinator.com/item?id=33279274 https://news.ycombinator.com/item?id=33279274 It is so so sad to see computing squandered so! The good news is AI is changing this relationship with software. I'm sure we will have no end of AI models built in to our software, that companies will maintain the strict control (tyrant's grip) over software as long as they can! But for AI to flourish, it's going to need to work across systems. And that means tearing down some of the walls, walls that have forcibly kept computing (ardently) anti-personal. I can go look at https://github.com/punkpeye/awesome-mcp-servers https://github.com/punkpeye/awesome-mcp-servers and take such great hope from it. Hundreds of ways that we have eeked out a way to talk interface with systems that, before, people had no say and no control over.
- cdoctorow 1y ago
dawnofdusk 1y ago
Basically the same as decrying why we should have to learn foreign languages instead of everyone speaking Esperanto.
- kbelder 1y ago
  Which I still decry!
grumbel 1y ago
Cyc[0] tried for 40 years to make handwritten semantic rules a thing, but still don't have much to show for. Humans just aren't good or fast at writing down the rather fuzzy semantics of the real world into a computer readable format. With RDF specially, there was also the issue of "WTF is this good for?". Semantic Web sounds lofty in theory, but was there ever even a clear plan on how the UI would look like? How would I explore all that semantic data if it ever came into existence? How would it deal with link rot? And much like with RSS, I think a big failure of RDF is that it's some weird thing outside the Web, instead of just some addition HTML tags to enrich existing documents. If there is a failure, it's that. Even today, a lot of basic semantic tags are missing from HTML, we finally got <date> in 2011, but we still have nothing for names, cities, units, books[1], movie, gps coordinates and a lot of other stuff we use daily. Another big failure is that HTML has become a read-only format, the idea that one uses HTML as a source format to publish documents seems to have been completely abandoned. HTML is just a UI language for Web apps nowadays, Markdown, LaTeX or whatever is what one uses to write content. 0. https://en.wikipedia.org/wiki/Cyc https://en.wikipedia.org/wiki/Cyc 1. <a href="urn:isbn:..."> exists, but browsers don't support it natively
camgunz 1y ago
Isn't this what Reddit is for
pavel_lishin 1y ago
> AI is impressive Ok, but Google's result summary got the answer wrong. So did Gemini, when I tried it (Lion, Sierra Leone). And so did ChatGPT when I tried it (Lion, Sri Lanka). So... it's impressive, sure, because the author is correct that a search engine can't answer that question in a single query. But it's also wildly wrong. I also vaguely agree with the author that Google Drive sucks, but I wish they'd mentioned that the solution to their problem - using search! - also fucking sucks in Google Drive.
- cgh 1y ago
  I saw a quote somewhere to the effect of “LLMs are lossy compression of the internet” and it seemed about right.
  - pavel_lishin 1y ago
    Yep, Ted Chiang wrote that for the New Yorker: https://www.newyorker.com/tech/annals-of-technology/chatgpt-is-a-blurry-jpeg-of-the-web https://www.newyorker.com/tech/annals-of-technology/chatgpt-...
yongjik 1y ago
This is a clickbait article one could've written when Google was new and people were getting used to the idea of "You can just search for things on the internet." It's just dressed up with mentions of AI for better "engagement."
d-mz 1y ago
The funny thing to me is that now more than ever structured data is important so that AI has a known good data set to train from, and so that search engines have contextual and semantically rich data to search. AI isn't a solution to this; on the contrary, whatever insufficiency exists in the original data set will only be amplified, as compression artifacts can be amplified in audio. We also can't trust any data that's created recently, because an LLM can be trained to provide correct-looking structured data that may or may not accurately model semantic structure. The best source of structured, tagged, contextually-rich data suitable for training or searching in the future will be from people who currently AREN'T using generative AI.
wagwang 1y ago
Building the semantic associations that LLMs can do is just building an LLM.
pradn 1y ago
Just complaining that the world is bad is a good way to waste your energy and end up being a cynic. So why is not all information organized in structured, open formats? Because there's not enough of an incentive to label/structure your documents/data that way. That's if you even want to open your data to the public - paywalls fund business models. There have been some smaller successes with semantic web, however. While a recipe site might not want to make it easy for everyone to scrape their recipes, people do want Twitter to generate a useful link preview from their sites' metadata. They do that with special tags Twitter recognizes, and other sites can use as well. The good news is that LLMs can generate structured data from unstructured documents. It's not perfect, but has two advantages: it's cheaper than humans doing it manually, and you don't have to ask the author to do anything. The structuring can happen on the read side, not the write side - that's powerful. This means we could generate large corpuses of open data from previously-inaccessible opaque documents. This massive conversion of unstructured to structured data has already been happening in private, with efforts like Google's internal Knowledge Graph. That project has probably seen billions in cumultative investment over the years. What we need is open data orgs like Wikipedia pick up this mantle. They already have Wikidata, whose facts you can query with a graph querying language. The flag example in the article could be decomposed into motifs by an LLM and added to the flag's entry. And then you could use SPARQL to do the structured query. (And that structured query can be generated from LLMs, too!) LLMs and structured data are friends.
rob_c 1y ago
Personal computing, best now it's flav djour we get to slam on cloud based approaches to everything being what they always were. Wasteful, slow and privacy invasive... But still can't just plainly say cloud has been mostly bad.
p3rls 1y ago
The last ten years of consumer web tech was dedicated to SEO slop and crypto. Google has destroyed everything else with its endless promotion of hindustantimes .com listicles.
mikewarot 1y ago
The root cause of this is that HTML is not a language for the markup of hypertext. Because everything has to be copied and/or compressed into a single layer document along with its markup, you almost never see actual markup in the web, just a lot of formatting and layout. Because you can't have multiple markup of a given source material, adding multiple hierarchies doesn't happen. Any given information structure is necessarily oversimplified and thus only fit for limited use. It's almost as if someone read Vannevar Bush's description of the memex and decided to actively prevent its reification. He said the organization of knowledge was the largest challenge facing mankind post war. Clearly he was right, and we've failed miserably. The thing LLMs provide is an impedance match between the data we do have, and the actual needs of mankind.

206 points by ambigious7777 1y ago

is it unreasonable to expect some kind of good enough baseline guided by the prior of these llm to be the standard ? Should google's priors (or their training dataset and recipe) be allowed to guide societal's prior? same problem, different era ?

open_ 1y ago

A pretty reductionist and a poor take. "Standing on the shoulders of giants, it is clear that the giants failed to reach the heights we have reached."

ubercow13 1y ago

"AI is impressive because it solves problems better than the previous solutions"? Yes?

Kapura 1y ago

I have often thought about how computers are significantly faster than they were in the early 2000s, but they are significantly harder to use. Using Linux for the first time in college was a revelation, because it gave me the tools to tell the computer "rename all of the files in this directory, keeping only the important parts of the name." But instead of iterating on better interfaces to effectively utilize the N thousands of operations per second a computer is capable of, the powers that be behind the industry have decided to invest billions of dollars in GPUs to get a program that seems like it understands language, but is incapable of counting the number of B's in "blueberry."

SV_BubbleTime 1y ago
IDK, I think there is something adorable about taking a system that over trillions of iterations always performs the same operation with the same result, reliability unmatched in all of the universe… And making it more of “IDK what it answered the way it did, but it might be right!!”
- codr7 1y ago
  Humans like games :)
xandrius 1y ago
Is counting the number of B's vital? Also, I'm pretty sure you can get an LLM to parse text the way you want it, it just doesn't see your text as you do, so that simple operation is not straightforward. Similarly, are you worthless because you seem like you understand language but are incapable of counting the number of octects in "blueberry"?
- tekno45 1y ago
  if i have to talk to it a specific way, why not just use programming. The specific way we talk to computers effectively...
- squigz 1y ago
  > Similarly, are you worthless because you seem like you understand language but are incapable of counting the number of octects in "blueberry"? Well, I would say that if GP advertised themselves as being able to do so, and confidently gave an incorrect answer, their function as someone who is able to serve their advertised purpose is practically useless.
  - xandrius 1y ago
    So ChatGPT was advertised as a letter counter? Also, no matter what hype or marketing says: GPT is a statistical word bag with a mostly invisible middleman to give it a bias. A car is a private transportation vehicle but companies still try to sell it as a lifestyle choice. It's still a car.
    - rini17 1y ago
      It is (maybe not directly but very insistently) advertised as taking many jobs soon. And counting stuff you have in front of yourself is basic skill required everywhere. Counting letters in a word is just a representative task for counting boxes with goods, or money, or kids in a group, or rows on a list on some document, it comes up in all kinds of situations. Of course people insist that AI must do this right. The word bag perhaps can't do it but it can call some better tool, in this case literally one line of python. And that is actually the topic the article touches on.
svachalek 1y ago
Prompt: "Spell blueberry and count the letter b". They're not claiming AGI yet, so human intelligence is required to operate an LLM optimally. It's well known that LLMs process tokens rather than characters s, so without space for "reasoning" there's no representation of the letter b in the prompt. Telling it to spell or think about it gives it room to spell it out, and from there it can "see" the letters and it's trivial to count.
- Kapura 1y ago
  if you're going to need to learn how to use a tool, why not learn to use the efficient and precise one?
  - ubercow13 1y ago
    Because there aren't more efficient and precise tools capable of the same things?
- cestith 1y ago
  perl -e 'print scalar grep {/b/} split //, "blueberry”' echo blueberry | grep -o 'b' | wc -l echo blueberry | perl -ne 'print scalar (() = m/(b)/g)’ echo blueberry | tr -d '\n' | tr b '\n' | wc -l echo -n blueberry | tr b '\n' | wc -l So long as I’m teaching the user how to speak to the computer for a specific edge case, which of these burn nearly as much power as your prompt? Maybe we should consider that certain problems are suitable to LLMs and certain ones should be handled differently, even if that means getting the LLM to recognize its own edge cases and run canned routines to produce answers.

throwmeaway222 1y ago

> because we've failed at personal computing ? If you really want to, you know have this super generic indexing thing, why don't you go organize the web with hypercard and semantic web crap and tell us how it worked out for you

foundart 1y ago

Expresses a longing for the semantic web. > Remember Semantic Web? The web was supposed to evolve into semantically structured, linked, machine-readable data that would enable amazing opportunities. That never happened. I think the lesson to be learned is in answering the question "Why didn't the semantic web happen?"

neilalexander 1y ago
> "Why didn't the semantic web happen?" Advertising.
- throwaway346434 1y ago
  To a degree re ads on pages, but why didn't big business end up publishing all of their products in JSON-LD or similar? A lot did, to get aggregated, but not all.
Workaccount2 1y ago
>"Why didn't the semantic web happen?" Because web content is generated by humans, not engineers.
- abeppu 1y ago
  But also because companies that produce web content wanted it to be seen by humans who would look at ads, not consumed by bots and synthesized with other info into a product owned by some other firm.
  - dreamcompiler 1y ago
    And yet today most websites are being scraped by LLM bots which don't look at ads and which synthesize with other info into a product owned by some other firm.
    - 1gn15 1y ago
      Optimistically, the semantic web is going to happen. Just that instead of the original plan of website owners willingly making data machine-readable, LLMs will be the ones turning non-machine-readable data machine-readable (which can then be processed by user agents), even if the website owner prefers you looked at the ads instead.

walterbell 1y ago

> If all knowledge were stored in a structured way with rich semantic linking, then very primitive natural language processing algorithms could parse question like the example at the beginning of the article, and could find the answer using orders of magnitude fewer computational resources. In vertical markets, can LLMs generate a "semantic web of linked data" knowledge graph to be parsed with efficient NLP algorithms? https://news.ycombinator.com/item?id=43914227#43926169 https://news.ycombinator.com/item?id=43914227#43926169 leveraging LLMs to build the special markup so that it can be applied towards other uses.. some type of semantic web format, like JSON-LD or OWL, or some database that can process SPARQL queries.. Palantir is using ontologies as guardrails to prevent LLM hallucinations

nrjames 1y ago
Palantir was 90% about ontology creation back when I first used it in 2009. They knew at that point that without some level of structure that mapped to the specific business problem that the data input into the graph was difficult to contextualize.

captainclam 1y ago

My read is that the author is saying it would have been really nice if there had been a really good protocol for storing data in a rich semantically structured way and everyone had been really really good at adhering to that standard. Is that the main thrust of it?

gsmt 1y ago

We weren't given enough time

deleted 1y ago

[deleted]

jddj 1y ago

I think every field has its own version of this thought, where if we could just manage to categorise and tag things properly we could achieve anything. Our lack of a valid overarching ontology is what is holding us back from greatness. It might be short lived, who knows, but it's interesting that the recent progress came from capturing/consuming rather than systematically eliminating the nuance in language.

octoberfranklin 1y ago
Every field including library science? ;)

butterisgood 1y ago

I'm pretty sure AI _is_ "personal computing". One can speak in their native language to a computer now and it mostly understands what is meant and can retrieve information or even throw together a scaffold of a project somewhat reliably. It's not particularly good at writing software, however. Still feels like a human is needed to make sure it doesn't generate nonsense or apparently pretty insecure code. So I'm not sure the author got the point across that they wished, but aren't vector databases basically a semantic storage/retrieval technology?

ralfd 1y ago
Yes, I rolled my eyes about the sneering of the author. By the way: His blog getting a few dozen hn comments is only impressive, because he failed to write a better blog.

octoberfranklin 1y ago

dang, please fix the title, "semantic web" somehow got deleted. if it's a space issue, "semantic web" is far more relevant to the article than "personal computing".

headcanon 1y ago

I feel like I see this attitude a lot amongst devs: "If everyone just built it correctly, we wouldn't need these bandaids" To me, it feels similar to "If everyone just cooperated perfectly and helped each other out, we wouldn't need laws/money/government/religion/etc." Yes, you're probably right, but no that won't happen the way you want to, because we are part of a complex system, and everyone has their very different incentives. Semantic web was a standard suggested by Google, but unless every browser got on board to break web pages that didn't conform to that standard, then people aren't going to fully follow it. Instead, browsers (correctly in my view) decided to be as flexible as possible to render pages in a best-effort way, because everyone had a slightly different way to build web pages. I feel like people get too stuck on the "correct" way to do things, but the reality of computers, as is the reality of everything, is that there are lots of different ways to do things, and we need to have systems that are comfortable with handling that.

ajkjk 1y ago
eh I feel this but it's a lot simpler than that. Not "if everyone built everything correctly" but "if everyone's work was even slightly better than complete garbage". I do not see many examples of companies building things that are not complete embarrassing shit. I worked at some companies and the things we built was complete embarrassing shit. The reasons are obvious: nobody cares internally to do it, and nobody externally has any standards, and the money still flows if you do a bad job so why do better? What happens in practice is that the culture exterminates the drive for improvement: not only are things bad, but people look at you if you're crazy if you think things should be better. Like in 2025 people defend C, people defend Javascript, people write software without types, people write scripts in shell languages; debugging sometimes involves looking at actual bytes with your eyes; UIs are written in non-cross-platform ways; the same stupid software gets written over and over at a million companies, sending a large file to another person is still actually pretty hard; leaving comments on it is functionally impossible ... these are software problems, everything is shit, everything can be improved on, nothing should be hard anymore but everything still is; we are still missing a million abstractions that are necessary to make the world simple. Good lord, yesterday I spent two hours trying to resize a PDF. We truly live in the stone age; the only progress we've made is that there are now ads on every rock. I really wish it was a a much more ruthlessly competitive landscape. One in which if your software is bad, slow, hard to debug, hard to extend, not open source, not modernized, not built on the right abstractions, hard to migrate on or off of, not receptive to feedback, covered in ads... you'd be brutally murdered by the competition in short order. Not like today where you can just lie on your marketing materials and nobody can really do anything because the competition is just as weak. People would do a much better job if they had to to survive.

MarkusQ 1y ago

Fresh plums right off the tree taste significantly better than the ones you can get in the produce isle, which are in turn better than canned, which are themselves still better than re-hydrated prunes. In scaling out computation to the masses, we went from locally grown plums that took a lot of work and were only available to a small number of people that had a plum tree or knew someone that had one, to building near magical prune-cornucopia devices that everyone could carry around in their pockets, giving them an effectively unlimited supply of prunes. LLMs re-hydrate these for us, making them significantly more palatable; if you're used to gnawing dried fruit, they seem amazing. But there's still a lot of work to be done.

selimthegrim 1y ago
But can it beat William Carlos Williams?
- MarkusQ 1y ago
  they were delicious so sweet and so cold :)
random3 1y ago
Perhaps, but we still failed and not at personal computing, nor just semantic web, but computing and programming in general. The failure is between the original intent (computing was originally more or less AI) along with theory and actual result with every software project turning into unsustainable infinite regress. Things likely broke around ALGOL. Also LLMs are failing too, for different reasons, but IMO unlikely AI in general will— it will correct a 60 years or so failure in industrial computer science.
- heresie-dabord 1y ago
  > we still failed [at] semantic web The most reprehensible knowledge-search-and-communication failure of all. We gave people monetisation of drek instead. Then asked them to use it for education. Then trained bot systems on it. Then said that even those answers must be made to confirm to transient propagandists.

khazhoux 1y ago

I always appreciate our weekly Crankypants Take on LLMs. > AI is not a triumph of elegant design, but a brute-force workaround You can read and understand Attention Is All You Need in one hour, and then (after just scaling out by a few billion) a computer talks to you like a human. Pretty elegant, if you ask me. > The web was supposed to evolve into semantically structured, linked, machine-readable data that would enable amazing opportunities. I missed that memo. The web was, and forever shall be, a giant, unstructured, beautiful mess. In fact, LLMs show just how hopeless the semantic web approach was. Yes, it's useful to attach metadata to objects, but you will still need massive layering and recursion to derive higher-order, non-trivial information. This entire article is someone unable to let go of an old idea that Did Not Work.

codr7 1y ago
Except it's all just smoke and mirrors.
- khazhoux 1y ago
  Explain? The algorithms are surprisingly easy to understand. There is no trickery.
  - codr7 1y ago
    And the conclusions are delusional, especially given how easy it is for anyone to see there is nothing in there even resembling intelligence.
mrweasel 1y ago
> AI is not a triumph of elegant design, but a brute-force workaround I think the author is on to something here, but does not realize it, or applies the think to the wrong problem. The issue isn't the web, search was good enough and it's a pretty big problem to solve. We need to go smaller. Applying AI to customer service, internal processes and bureaucracy, among other things, is an inelegant brute-force approach to not just fixing your shit. The majority of customer service could be fixed by having better self-service, designing better UIs, writing better manuals, having better monitoring, better processes, better trained staff, not insisting on pumping stock numbers and actually caring about your product. AI will never fix the issues your customers are having, they'll just make customer service cheaper and worse because just like real humans the content and levers they need aren't available. Same for much of the bureaucracy in companies and governments. Rather than having AI attempt to fill out forms or judge if someone is entitled to a pension, insurance pay out or what have you. Take the time to fix your damn processes and built self-service portals that actually works (some of those may have some sort of AI on the backend for things like scanning documents). Forget the semantic web thing, it never worked, to much data, and AI generated content certainly isn't making the problem easier. Let's work on that at some other time. Still the author is correct, LLMs are a brute-force workaround, regardless of how elegant the design may be. They are applied to a host of problem that should just be eliminated, not hidden and stupefied by a prediction engine.

nicemountain 1y ago

Alan Kay has also written about his disappointment with what personal computing delivered. I think he'd agree with this. Most people can't use the power of the computers they have effectively. Maintaining the data in Excel spreadsheets for most people is like manual labour.

blurbleblurble 1y ago

Another angle: we're super over provisioned in compute resources because of reasonable limitations in how quickly we can collectively absorb and learn how to use computers. "AI" is simply a new paradigm in our understanding of how to program computers. This isn't a failure, it's just an evolution.

bkummel 1y ago

Yeah dream on. I’m an engineer and know what structured data is. And yet I miserably fail to store my private files in a way that I can find them back without relying on search tools. So how on earth are we ever going to organize all the world’s data and knowledge? Thank god we found this sub-optimal “band aid” called LLMs!

ctoth 1y ago
Precisely this. This article might seem reasonable to anybody who has never tried to organize something as simple as a local music collection.
- pjm331 1y ago
  Made me think about John Wilkins' "philosophical language" which I first heard about in Neal Stephenson's book Quicksilver https://en.wikipedia.org/wiki/An_Essay_Towards_a_Real_Character,_and_a_Philosophical_Language https://en.wikipedia.org/wiki/An_Essay_Towards_a_Real_Charac... I'm sure there have been countless similar attempts at categorizing knowledge one of the more successful ones being the dewey decimal system I have my doubts about whether the thing the OP alleges we have "failed" at is even possible at all
- whartung 1y ago
  Well, this runs straight into one of the massive, concrete pillars of computing: naming things. Because that’s what a lot of this falls into. Overwhelming amount of stuff with no names. No categories, no nothing. With extended file attributes we could hang all sorts of meta bits off of arbitrary files. But that’s very fragile. So we ask the systems to make up names for data based on their content, which turns out to not necessarily work as well as we might like.
  - jandrese 1y ago
    No names is not the biggest problem. You just have to come up with a name. The problem is when things have multiple names, or even worse when people disagree on what names are appropriate for something. The world rarely allows you to neatly categorize large datasets. There are always outliers. For example, you have a set of balls and you want to sort them by color. Where does orange stop and red begin? What about striped balls or ones with logos printed on them? What if it is a hypercolor ball that changes based on heat? It gets messy very fast.

AlienRobot 1y ago

Personal computing failed because desktop operating systems started trying to work for mobile. Everything that is bad in UI is a direct consequence of that. 1. No tooltips, right click, middle click behavior because touch doesn't have that. No ctrl+click either. 2. Large click areas wasting screen space with padding and margins. 3. Low density UI so it can shape-shift into mobile version. 4. Why type on a phone when you can talk? Make everything a search box. 5. Everything must be flat instead of skeumorphic because it's easier to resize for other screen sizes. 6. Everything needs a swipe animation and views instead of dialogs because smartphones can't have windows.

smusamashah 1y ago

How do LLMs help Google, an ad company, generate more ad revenue. LLMs drive the traffic away from websites, give you answer directly without needing bother with ads. How does it benefit Google's ad business?

add-sub-mul-div 1y ago
Ad clicks are a trifle compared to the possibility of winning the game of displacing vast amounts of labor and delivering ads and narratives undisclosed through conversational AI output. At that point you've won the economy, period.
- thewebguyd 1y ago
  > winning the game of displacing vast amounts of labor and delivering ads and narratives undisclosed through conversational AI output. At that point you've won the economy, period. In a functional democracy, all you should win by doing that is harsh antitrust action.
  - add-sub-mul-div 1y ago
    Yes that's why my opposition to LLMs is contextual. If it had been invented 30 years ago I'd have been optimistic about it.

SoftTalker 1y ago

What a terrible question in the opening example. Are we playing Jeopardy?

deleted 1y ago

[deleted]

yen223 1y ago

How will user-generated content work in a semantic web world?

jvreeland 1y ago

I think I broadly agree with this. I am super frustrated that everythign always wants me to search for things. As an example Finders default search while looking at a folder is the whole machine instead of a filter in the directory you are viewing in seems totally insane to me. It's almost like they don't want me to know where my files are. I can understand that it's a result, to a degree of cloud services and peoples primary mode swapping to opening and app and opening recents or searching instead of opening a file to open an app but it does mean that you're at the mercy of what I experience as some pretty crap search algorithms that don't seem to want you to find the information you're looking for. I keep encountering searches that rank fuzzy matches over exact matches or aren't stable as you continue to complete the same word and I just don't understand how that's acceptable after being pointed out if search is what I'm supposed to be using.

autoexec 1y ago
> It's almost like they don't want me to know where my files are. I think this might actually be true in some cases. Especially where companies want your files on their cloud servers. It's better for them if you don't think about what's stored locally or remotely. It's better for them if you don't think at all and just ask them for whatever you want and let them decide what to show you or keep hidden from you. It's easier for them to get metrics on what you're doing if you type it out explicitly in a search box than it is for them to track you as you browse through a hierarchy you designed to get to what you want. You're supposed to feel increasingly helpless and dependent on them.

rglullis 1y ago

Uh, the author got so close to make the same realization I had while working on a project [0] for the Wikimedia Foundation: we wouldn't need search engines if we had better tooling to query semantic databases like wikidata. However, the thing that the author might be missing is that the semantic web exists. [1] The problem is that the tools that we can use to access it are not being developed by Big Tech. Remember Freebase? Remember that Google could have easily kept it around but decided to fold it and shoved it into the structured query results? That's because Google is not interested in "organizing the world's information and make it universally accessible" unless it is done in a way that it can justify itself into being the data broker. I'm completely out of time or energy for any side project at the moment, but if someone wants to steal my idea: please take a llm model and fine tune so that it can take any question and turn it into a SparQL query for Wikidata. Also, make a web crawler that reads the page and turns into a set of RDF triples or QuickStatements for any new facts that are presented. This would effectively be the "ultimate information organizer" and could potentially replace Wikidata as most people's entry page of the internet. [0]: https://meta.wikimedia.org/wiki/QuickStatements_3.0 https://meta.wikimedia.org/wiki/QuickStatements_3.0 [1] https://guides.library.ucla.edu/semantic-web/datasets https://guides.library.ucla.edu/semantic-web/datasets

throwaway346434 1y ago
ChatGPT etc does an OK job at SPARQL generation. Try something like "generate a list of all supermarkets, including websites, country, description" and you get usable queries out. In a much, much more limited way, this is what I was dabbling with with alltheprices - queries to pull data from wikidata, crawling sites to pull out the schema.org Product and offers, and publish the aggregate.
ethan_smith 1y ago
DBpedia Spotlight and entity-fishing already do something similar to your idea - they extract structured data from text and link to knowledge bases. Combining these with LLM-based query translation to SPARQL could indeed bridge the gap between semantic web's structure and natural language interfaces.

atrettel 1y ago

I find traditional web search and LLM search to be complementary technologies, and this is a good example of that. Both have their uses and if you get the information you need using one or the other, we are all happy. I think the example query here actually shows a problem with the query languages used in web search rather than an intrinsic inability of web search. It contains what amounts to a natural language subquery starting with "in the same year". In other words, to evaluate this query properly, we need to first evaluate this subquery and then use that information to evaluate the overall query. Google Search and almost all other traditional web search engines use intentionally oversimplified query languages that disallow nested queries let alone subqueries, so this example really is just revealing a problem with the query language rather than a problem with web search overall. With a better query language, we might get better results.

nullorempty 1y ago

Neither chat-gpt nor gemini got the same answer as the article for me ` What animal is featured on a flag of a country where the first small British colony was established in the same year that Sweden's King Gustav IV Adolf declared war on France? ` chatgpt: Final answer: Lion gemini: A lion is featured on the flag of Sri Lanka.

autoexec 1y ago
> Neither chat-gpt nor gemini got the same answer as the article for me getting wildly different and unpredictable answers from the same input is one of the features AI offers
vrwarp 1y ago
Gemini (2.5 pro) stands firm on its answer even when told that ChatGPT said it is a parrot. It does provide additional reasoning: https://g.co/gemini/share/45232dcc7278 https://g.co/gemini/share/45232dcc7278

gorfian_robot 1y ago

"pile of divs" is so accurate

antithesizer 1y ago

The essential meaning of technological progress is the utter inadequacy of humanity. We build cars that we never figure out how to safely drive, but being to arrogant to admit defeat and reconstruct society around trams like a sensible animal would do, we wait a century for cars that can drive themselves while the bodies pile up on the freeways in the meantime. Yes it's true, we can't make a UI. Or a personal computer, or anything else that isn't deeply opaque to its intended users. But it's so much worse than that. We humans can't do hardly anything successfully besides build technology and beat each other in an ever expanding array of ridiculous pissing contests we call society.

tempfile 1y ago

This take is very naive and should anticipate the obvious criticism: people did try, very very hard, to create structured information systems. They simply did not work. The sort of systems people tend to build are well-scoped for a particular problem, but fall apart completely when moving out of that domain. It is very easy to imagine an information system that results in correct answering of flag questions. It is a wide open problem to come up with a way of tagging information that works well for flag questions and for questions about memes, or art. It's not like Google didn't try!

seydor 1y ago

Chatgpt does not build semantic maps. we know it has some attention maps, but really fuzzy how it uses them

fouc 1y ago

I would argue that LLM is ultimately making true Semantic Web available, or irrelevant. It can basically figure out all the semantic knowledge graphs automatically for us, and it's multi-modal to boot. That means it can infer the relationships between any node across text, audio, images, videos, and even across different languages.

jacobgkau 1y ago
The question is whether humans specifying the relationships between nodes is more or less reliable than LLMs inferring those relationships.
- svachalek 1y ago
  So we need to compare the reliability of something hypothetical to something real? I'll take the real every time.
  - jacobgkau 1y ago
    What? No. With traditional tech stacks, humans are responsible for tagging and structuring data as they input it. With AI, the argument is that the AI system can do that instead (via inference), meaning humans can input it unstructured. They're both "real." If you were trying to make a witty comment about AI's purported capabilities not existing/working well, then I personally agree that humans doing it would be smarter and more efficient.

reriufj 1y ago

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deleted 1y ago

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mwkaufma 1y ago

> They scan the unstructured web and build ephemeral semantic maps across everything. It's not knowledge in the classic sense.. or perhaps it is exactly what knowledge is? Betteridge's law

jkaptur 1y ago

"... if all knowledge were stored in a structured way with rich semantic linking..." this sounds a lot like Google's "Knowledge Graph". https://developers.google.com/knowledge-graph https://developers.google.com/knowledge-graph. (Disclosure: I work at Google.) If you ask an LLM where you can find a structured database of knowledge with structured semantic links, they'll point you to this and other knowledge graphs. TIL about Diffbot! In my experience, it's a lot more fun to imagine the perfect database like this than it is to work with the actual ones people have built.

throwanem 1y ago

People have said this since Vannevar Bush theorized the Memex. The unanswered question, the problem unsolved, remains: Who does all the categorization work? How come they're never part of "we," such that the plaint is never "if only we had done the work..."?

seanmcdirmid 1y ago

At Engelbart's mother of all demos in 1968, which basically birthed what we call personal computing today, most computer scientists were convinced that AGI was right around the corner and "personal computing" wasn't worth it. Now, back then AGI wasn't right around, and personal computing was really really necessary, but how did we forget the viewpoint that personal computing was seen as a competing way to use computing power vs AI?

tempodox 1y ago
Economic interests, walled gardens, lock-in effects. Providers learned to make it (initially) convenient for us to forget. Of course, once we’re hooked, enshittification ensues: https://news.ycombinator.com/item?id=44837367 https://news.ycombinator.com/item?id=44837367

seanwilson 1y ago

> What animal is featured on a flag of a country where the first small British colony was established in the same year that Sweden's King Gustav IV Adolf declared war on France? ... My point is that if all knowledge were stored in a structured way with rich semantic linking, then very primitive natural language processing algorithms could parse question like the example at the beginning of the article, and could find the answer using orders of magnitude fewer computational resources. So as well as people writing posts in English, they would need to provide semantic markup for all the information like dates, flags, animals, people, and countries? It's difficult enough to get people to use basic HTML tags and accessible markup properly, so what was the plan for how this would scale, specifically to non-techy people creating content?

TZubiri 1y ago
So wikipedia and wikidata? This actually happened already and it's part of why llms are so smart, I haven't tested this but I venture a guess that without wikipedia and wikidata and wikipedia clones and stolen articles, LLMs would be quite a lot dumber. You can only get so far with reddit articles and embedded knowledge of basic info on higher order articles. My guess is when fine tuning and modifying weights, the lowest hanging fruit is to overweigh wikipedia sources and reduce the weight of sources like reddit.
- seanwilson 1y ago
  Only a relatively small part of Wikipedia has semantic markup though? Like if the article says "_Bob_ was born in _France_ in 1950" where the underlines are Wikpedia links, you'll get some semantic info from the use of links (Bob is a person, France is a country), but you'd be missing the "born" relationship and "1950" date as these are still only raw text. Same with the rest of articles with much more complex relationships that would probably be daunting even for experts to markup in an objective and unambiguous way. I can see how the semantic web might work for products and services like ordering food and booking flights, but not for more complex information like the above, or how semantic markup is going to get added books, research articles, news stories etc. that are always coming out.

taeric 1y ago

Leading in with what feels like a p-hacked question that almost certainly isn't typical kind of hurts the point. Reminds me of seeing clearly rehearsed demos for things that ignore the reason it worked is because it was rehearsed. A lot. Am I wrong in that this was a completely organic question?

ninetyninenine 1y ago

No AI is impressive because we built a machine that finally understands what we are saying and has a concept of what creativity is. It's rudimentary but it's a milestone for humanity. It's social media and the endless barrage of generated AI that's creating the illusion that AI isn't impressive. You're inundated everyday with the same crap and is just making it less and less impressive.

jauntywundrkind 1y ago

I sympathize so much with the failure of personal computing to manifest! > My point is that if all knowledge were stored in a structured way with rich semantic linking, then very primitive natural language processing algorithms could parse question like the example at the beginning of the article, and could find the answer using orders of magnitude fewer computational resources. And most importantly: the knowledge and the connections would remain accessible and comprehensible, not hidden within impenetrable AI models. It's a pocket hope of mine that AI brings us back to the Semantic Web, or something very like it. In many ways these embeddings are giant non-human lexicons already. Distilling this information out seems so possible. Even just making an AI to go markup (or uhh perhaps refine) a page with microdata seems conceptually very doable! More broadly, looking at personal computing: my personal belief is that failure is hugely because of apps. Instead of a broader personal computing that aggregates, that allows constructivism, that enables personal growth & development (barefoot developers & home-cooked software style), computing has been defined by massificstion, by big tech software. The dominant computing paradigm has been mainframe pattern: we the user have an app that acts as a terminal to some far off cloud-y data center. Whatever agency we get is hewn out for us apriori by product teams, and any behavior not explicitly built in is a "Felony Contempt of Business Model" (an oh so accurate Doctorow-ism)! https://maggieappleton.com/home-cooked-software https://maggieappleton.com/home-cooked-software https://news.ycombinator.com/item?id=40633029 https://news.ycombinator.com/item?id=40633029 https://pluralistic.net/2022/10/20/benevolent-dictators/#felony-contempt-of-business-model https://pluralistic.net/2022/10/20/benevolent-dictators/#fel... https://news.ycombinator.com/item?id=33279274 https://news.ycombinator.com/item?id=33279274 It is so so sad to see computing squandered so! The good news is AI is changing this relationship with software. I'm sure we will have no end of AI models built in to our software, that companies will maintain the strict control (tyrant's grip) over software as long as they can! But for AI to flourish, it's going to need to work across systems. And that means tearing down some of the walls, walls that have forcibly kept computing (ardently) anti-personal. I can go look at https://github.com/punkpeye/awesome-mcp-servers https://github.com/punkpeye/awesome-mcp-servers and take such great hope from it. Hundreds of ways that we have eeked out a way to talk interface with systems that, before, people had no say and no control over.

cdoctorow 1y ago

dawnofdusk 1y ago

Basically the same as decrying why we should have to learn foreign languages instead of everyone speaking Esperanto.

kbelder 1y ago
Which I still decry!

grumbel 1y ago

Cyc[0] tried for 40 years to make handwritten semantic rules a thing, but still don't have much to show for. Humans just aren't good or fast at writing down the rather fuzzy semantics of the real world into a computer readable format. With RDF specially, there was also the issue of "WTF is this good for?". Semantic Web sounds lofty in theory, but was there ever even a clear plan on how the UI would look like? How would I explore all that semantic data if it ever came into existence? How would it deal with link rot? And much like with RSS, I think a big failure of RDF is that it's some weird thing outside the Web, instead of just some addition HTML tags to enrich existing documents. If there is a failure, it's that. Even today, a lot of basic semantic tags are missing from HTML, we finally got <date> in 2011, but we still have nothing for names, cities, units, books[1], movie, gps coordinates and a lot of other stuff we use daily. Another big failure is that HTML has become a read-only format, the idea that one uses HTML as a source format to publish documents seems to have been completely abandoned. HTML is just a UI language for Web apps nowadays, Markdown, LaTeX or whatever is what one uses to write content. 0. https://en.wikipedia.org/wiki/Cyc https://en.wikipedia.org/wiki/Cyc 1. <a href="urn:isbn:..."> exists, but browsers don't support it natively

camgunz 1y ago

Isn't this what Reddit is for

pavel_lishin 1y ago

> AI is impressive Ok, but Google's result summary got the answer wrong. So did Gemini, when I tried it (Lion, Sierra Leone). And so did ChatGPT when I tried it (Lion, Sri Lanka). So... it's impressive, sure, because the author is correct that a search engine can't answer that question in a single query. But it's also wildly wrong. I also vaguely agree with the author that Google Drive sucks, but I wish they'd mentioned that the solution to their problem - using search! - also fucking sucks in Google Drive.

cgh 1y ago
I saw a quote somewhere to the effect of “LLMs are lossy compression of the internet” and it seemed about right.
- pavel_lishin 1y ago
  Yep, Ted Chiang wrote that for the New Yorker: https://www.newyorker.com/tech/annals-of-technology/chatgpt-is-a-blurry-jpeg-of-the-web https://www.newyorker.com/tech/annals-of-technology/chatgpt-...

yongjik 1y ago

This is a clickbait article one could've written when Google was new and people were getting used to the idea of "You can just search for things on the internet." It's just dressed up with mentions of AI for better "engagement."

d-mz 1y ago

The funny thing to me is that now more than ever structured data is important so that AI has a known good data set to train from, and so that search engines have contextual and semantically rich data to search. AI isn't a solution to this; on the contrary, whatever insufficiency exists in the original data set will only be amplified, as compression artifacts can be amplified in audio. We also can't trust any data that's created recently, because an LLM can be trained to provide correct-looking structured data that may or may not accurately model semantic structure. The best source of structured, tagged, contextually-rich data suitable for training or searching in the future will be from people who currently AREN'T using generative AI.

wagwang 1y ago

Building the semantic associations that LLMs can do is just building an LLM.

pradn 1y ago

Just complaining that the world is bad is a good way to waste your energy and end up being a cynic. So why is not all information organized in structured, open formats? Because there's not enough of an incentive to label/structure your documents/data that way. That's if you even want to open your data to the public - paywalls fund business models. There have been some smaller successes with semantic web, however. While a recipe site might not want to make it easy for everyone to scrape their recipes, people do want Twitter to generate a useful link preview from their sites' metadata. They do that with special tags Twitter recognizes, and other sites can use as well. The good news is that LLMs can generate structured data from unstructured documents. It's not perfect, but has two advantages: it's cheaper than humans doing it manually, and you don't have to ask the author to do anything. The structuring can happen on the read side, not the write side - that's powerful. This means we could generate large corpuses of open data from previously-inaccessible opaque documents. This massive conversion of unstructured to structured data has already been happening in private, with efforts like Google's internal Knowledge Graph. That project has probably seen billions in cumultative investment over the years. What we need is open data orgs like Wikipedia pick up this mantle. They already have Wikidata, whose facts you can query with a graph querying language. The flag example in the article could be decomposed into motifs by an LLM and added to the flag's entry. And then you could use SPARQL to do the structured query. (And that structured query can be generated from LLMs, too!) LLMs and structured data are friends.

rob_c 1y ago

Personal computing, best now it's flav djour we get to slam on cloud based approaches to everything being what they always were. Wasteful, slow and privacy invasive... But still can't just plainly say cloud has been mostly bad.

p3rls 1y ago

The last ten years of consumer web tech was dedicated to SEO slop and crypto. Google has destroyed everything else with its endless promotion of hindustantimes .com listicles.

mikewarot 1y ago

The root cause of this is that HTML is not a language for the markup of hypertext. Because everything has to be copied and/or compressed into a single layer document along with its markup, you almost never see actual markup in the web, just a lot of formatting and layout. Because you can't have multiple markup of a given source material, adding multiple hierarchies doesn't happen. Any given information structure is necessarily oversimplified and thus only fit for limited use. It's almost as if someone read Vannevar Bush's description of the memex and decided to actively prevent its reification. He said the organization of knowledge was the largest challenge facing mankind post war. Clearly he was right, and we've failed miserably. The thing LLMs provide is an impedance match between the data we do have, and the actual needs of mankind.