4 ms·

> Compared to the olden days, when specs were written by pedantic old Unix dudes I think that is one of the reasons (among many others) that the semantic web f

> Compared to the olden days, when specs were written by pedantic old Unix dudes I think that is one of the reasons (among many others) that the semantic web failed (which doesn't contradict the author, whose point is literally the worse-is-better mantra). People really leaned into the eXtensible part of XML and I think a certain amount of fatigue set it. XSL, XHTML, XSD, WSDL, XSLT, RDF, RSS, et al. just became a bit too much. It was architecture astronautics for data formats when what the world at the time needed was simple interchange formats (and JSON fit the bill). But I actually believe XML's time has come. I've noticed that XML appears a lot in leaked system prompts from places like Anthropic. LLMs appear to work very well with structured text formats (Markdown and XML specifically). I believe that MCP is the wrong model, though. I believe we should be "pushing" context to the models rather than giving them directions on how to "pull" the context themselves.

MrBuddyCasino 1y ago
Two years ago he would have written „pedantic white old Unix dudes“.
- M4rkJW 1y ago
  True, though "dudes who were never in danger of being gruntled" made it pretty clear who he was targeting.
mdaniel 1y ago
> I believe we should be "pushing" context to the models rather than giving them directions on how to "pull" the context themselves. How could that possibly work for the cases that people want the intern to solve for them? If they knew the information ahead of time, presumably they'd just solve the problem by themselves I get the impression that the value folks get from MCP is "run some query for me, don't make me learn how to glue together 15 sources"
- zoogeny 1y ago
  I'm not sure I understand your objection. You seem to imply that knowing the context is the same as knowing the solution to the problem the context provides? Let me think of an example here. Context needed to determine if there is cancer in a radiology scan would be the contents of the scan. So there are two modes here, one I say "LLM please tell me if there is cancer in this patients scan" and the LLM makes an MCP call to load the patients report. The second mode is I say "LLM, here is the patients radiology scan, can you tell me if it has signs of cancer". The first example is what I was calling a "pull" model and the second example is what I am calling a "push" model.
  - goncalo-r 1y ago
    For a lot of office jobs, knowing the context is almost the same as knowing the solution to the problem at hand.
    - zoogeny 1y ago
      I'd be interested in examples of this. I've worked in offices for all of my adult life and I don't have any examples that come to mind. I think of logic puzzles I used to do as a kid. The whole idea of the puzzle is that all of the information you need is provided, the fun is in solving using deduction. Sudoku scratches the same itch. At the least, I would argue there are many problems that don't fit the mold you are suggesting and MCP is not the correct method for addressing them.
      - mdaniel 1y ago
        > I'd be interested in examples of this. I've worked in offices for all of my adult life and I don't have any examples that come to mind. Wow, you must have worked in some really mature shops then if you knew instantly which of [Google Drive, Confluence, Airtable, GitHub wiki, ${that one deprecated thing that Alice was using}, ...] contained the reference to Project Frazlebaz mentioned in Slack last.. day? week? Maybe it was today but time is a blur?
        1y ago
- ranguna 1y ago
  I'm not sure if it's productive to give a full database worth of context to an LLM. There'd be a lot of data that could potentially pollute the LLM's reasoning with information that it doesn't need to answer your prompts. This can be specially troublesome for small models.
wongarsu 1y ago
XML tags work well for LLMs. But notably the vast majority are just xml tags. Nobody™ is feeding LLMs well-formed XML with an xml declaration (the <?xml version="1.0" encoding="UTF-8"?> at the start) and we aren't using namespaces, XSLT, XML Schemas etc. It's just some ad-hoc collection of sgml-style tags
- zoogeny 1y ago
  I've noticed that as well, but I doubt those additional tokens hurt. You can make an unholy mess with namespaces and all of the bells-and-whistles that XML provides, or you can not. But even if you just structure using <tag></tag> without any of the fancy stuff, you still can create pipelines that operate on that structured format in ways that are more powerful than plain text.
- selfselfgo 1y ago
  [dead]
- jazzyjackson 1y ago
  still its a format that allows for lossy transmission which I think meshes well with the fuzzy ingestion of llms, the closing tags' redundancy is a feature that helps the llm stay focused
  - deleted 1y ago
    [deleted]
this_user 1y ago
I think the main reason that "Semantic Web" has failed is that basically no one can even explain what the "Semantic Web" is or what it's good for. It's all just a bunch of generic sounding buzzwords about exchanging data in some way.
- achierius 1y ago
  Is it that hard? Instead of just providing data, you provide data plus "semantic tags" that make the data machine-indexable. It was ultimately meant to solve the same sort of "fuzzy-search" problem that we today can use LLMs for: "find me a website which sells home goods" could be addressed with tags that classify a page as a marketplace, and therein one which sells home goods. I think the real problem is that this requires a cohesive ontology, and if you've ever gotten really into tagging your notes/bookmarks/whatever you'll know how hard that can be.
  - fabrice_d 1y ago
    Yes, most of the problem with the semantic web is that you end up with having to agree on how to describe the world: what are the concepts, and how they are related. This kind of work on semantic networks has been done for a while in computational linguistics for natural language processing, but it's very tedious. For instance users of the Minitel in France in the 80s could lookup vets by querying the yellow pages directory with sentences such as "my dog is sick". Nice tech, but not that useful and not very discoverable either. LLMs promise to just discover all these relations between concepts for you and do the right thing instead. Sometimes it works, sometimes not...
    - jcelerier 1y ago
      > Sometimes it works, sometimes not... Sometimes it won't work because there just isn't agreement between humans on what the concept is. Semantic also fails there.
blitzar 1y ago
> the semantic web failed It failed because they couldn't figure out how to stuff ads in.
- bastawhiz 1y ago
  It failed because nobody wanted to use it. Nobody built a compelling product from it, nobody wanted to author the data, nobody cared to use it when anyone did. It wasn't killed, it never got started because it never had a useful purpose.
  - phatskat 1y ago
    I remember learning XML and XSLT from library books in the late 90’s and found it interesting, but couldn’t find a use for it - I wasn’t really handling data in any meaningful way back then, it was all just hobby learning, but in the decades since I’ve touched XML _at all_ maybe three times? Once was a Salesforce integration I wish I could fully forget, the other times were client one-offs when they had a few things stored in XML that we needed to pipe into WordPress.
kiitos 1y ago
> I believe we should be "pushing" context to the models rather than giving them directions on how to "pull" the context themselves. Models have very very very limited capacity for context, it's one of their primary bottlenecks, therefore it's important to optimize (minimize) that information as much as possible, allowing the model to pull what it decides it needs makes that constraint much easier to satisfy.
- zoogeny 1y ago
  >what it decides it needs This is what I am suggesting: relying on the model to decide what it needs is maybe not the best use of the available context. It might be better for us to give it the information we are certain it will need.
  - kiitos 1y ago
    I'm talking about situations where the user wants to ask questions about data that's many orders of magnitude larger than what can be included in any LLM request context. I just provide access to the data (via MCP server, RAG server, whatever) and my question/prompt, it's the LLM's responsibility to do everything else.
jazzyjackson 1y ago
Interesting observation. I've been kinda hyped about XML/XSLT lately because I was working on a JSON macro expansion language (just four different macro tags that replace themselves with the macro's expansion, #= #& #? #! assignment, substitution, conditional branch like cond, and call for custom functions) and realised I was re-inventing XSLT, but what I really wanted was xpath, a way to describe traversal over graphs, back and forth along different axes, it's actually an amazing spec. Then I found basex [0] which pulls arbitrary XML documents into a queryable database that can be have queries described in XPATH or XQUERY. In my mind the best way to create a reliable natural language interface to a dataset without hallucination would be to hand over XML schemas to the system prompt and have it write the queries to retrieve the data. [0] https://basex.org/ https://basex.org/
- zoogeny 1y ago
  What I miss is E4X [1]. The ability to grab collections of child elements and collections of descendent elements made working with XML bearable. 1. https://en.wikipedia.org/wiki/ECMAScript_for_XML https://en.wikipedia.org/wiki/ECMAScript_for_XML
th0ma5 1y ago
The Semantic Web has yet to fully fail. Most companies have implemented a closed world limited version of it internally. It has already been proposed as a solution to correct LLM outputs by many people.
sbierwagen 1y ago
>LLMs appear to work very well with structured text (XML Plausible. >Markdown What? Markdown is specifically designed to be the least structured markup format possible, the absolute minimum set of features. Did you mean JSON or something?
MarkMarine 1y ago
I found this talk really interesting at conj, argues that RDF and the semantic web may have finally found its niche. https://youtu.be/OxzUjpihIH4?si=DRSp1n9u56iGbZFZ https://youtu.be/OxzUjpihIH4?si=DRSp1n9u56iGbZFZ
crq-yml 1y ago
I occasionally dally with XML in hobby code as a document source format, but I think what drives me away at the end is silly stuff with syntax, because it is a big spec well beyond the angle-bracket stuff, it wants to cover all the bases, do security right and do character encoding right - which means that "plain text editing" in it is some really unintuitive stuff where you can type in something like this paragraph and it might be parsed in a compatibility mode, but it won't be valid. As an interchange format or something loaded into application software tailored for it, it has more legs - and LLMs definitely wouldn't have any trouble making sense of it, which is good. A lot of yesteryear's challenges came from programmers short on time and eager to hack in features taking a heavily structured spec and wielding it like a blunt instrument. "XML? Sure, I can write a regex for that." Repeat that across three different programs and three different authors and you have a mess. There is a format that I've hit upon that actually does get at what I want for myself, and that's BBCode. That's a great source format for a lot of stuff - still basically an angle-bracket, but with the right amount of structure and flexibility to serve as a general-purpose frontend syntax. Early implementations were "write a regex for that" but after decades of battle-testing, there are more graceful parsers around these days as well.
cube2222 1y ago
> I believe we should be "pushing" context to the models rather than giving them directions on how to "pull" the context themselves. I believe MCP "Resources"[0] are what you're looking for. [0]: https://modelcontextprotocol.io/docs/concepts/resources#resources https://modelcontextprotocol.io/docs/concepts/resources#reso...

MrBuddyCasino 1y ago

Two years ago he would have written „pedantic white old Unix dudes“.

M4rkJW 1y ago
True, though "dudes who were never in danger of being gruntled" made it pretty clear who he was targeting.

mdaniel 1y ago

> I believe we should be "pushing" context to the models rather than giving them directions on how to "pull" the context themselves. How could that possibly work for the cases that people want the intern to solve for them? If they knew the information ahead of time, presumably they'd just solve the problem by themselves I get the impression that the value folks get from MCP is "run some query for me, don't make me learn how to glue together 15 sources"

zoogeny 1y ago
I'm not sure I understand your objection. You seem to imply that knowing the context is the same as knowing the solution to the problem the context provides? Let me think of an example here. Context needed to determine if there is cancer in a radiology scan would be the contents of the scan. So there are two modes here, one I say "LLM please tell me if there is cancer in this patients scan" and the LLM makes an MCP call to load the patients report. The second mode is I say "LLM, here is the patients radiology scan, can you tell me if it has signs of cancer". The first example is what I was calling a "pull" model and the second example is what I am calling a "push" model.
- goncalo-r 1y ago
  For a lot of office jobs, knowing the context is almost the same as knowing the solution to the problem at hand.
  - zoogeny 1y ago
    I'd be interested in examples of this. I've worked in offices for all of my adult life and I don't have any examples that come to mind. I think of logic puzzles I used to do as a kid. The whole idea of the puzzle is that all of the information you need is provided, the fun is in solving using deduction. Sudoku scratches the same itch. At the least, I would argue there are many problems that don't fit the mold you are suggesting and MCP is not the correct method for addressing them.
    - mdaniel 1y ago
      > I'd be interested in examples of this. I've worked in offices for all of my adult life and I don't have any examples that come to mind. Wow, you must have worked in some really mature shops then if you knew instantly which of [Google Drive, Confluence, Airtable, GitHub wiki, ${that one deprecated thing that Alice was using}, ...] contained the reference to Project Frazlebaz mentioned in Slack last.. day? week? Maybe it was today but time is a blur?
      - 1y ago
ranguna 1y ago
I'm not sure if it's productive to give a full database worth of context to an LLM. There'd be a lot of data that could potentially pollute the LLM's reasoning with information that it doesn't need to answer your prompts. This can be specially troublesome for small models.

wongarsu 1y ago

XML tags work well for LLMs. But notably the vast majority are just xml tags. Nobody™ is feeding LLMs well-formed XML with an xml declaration (the <?xml version="1.0" encoding="UTF-8"?> at the start) and we aren't using namespaces, XSLT, XML Schemas etc. It's just some ad-hoc collection of sgml-style tags

zoogeny 1y ago
I've noticed that as well, but I doubt those additional tokens hurt. You can make an unholy mess with namespaces and all of the bells-and-whistles that XML provides, or you can not. But even if you just structure using <tag></tag> without any of the fancy stuff, you still can create pipelines that operate on that structured format in ways that are more powerful than plain text.
selfselfgo 1y ago
[dead]
jazzyjackson 1y ago
still its a format that allows for lossy transmission which I think meshes well with the fuzzy ingestion of llms, the closing tags' redundancy is a feature that helps the llm stay focused
- deleted 1y ago
  [deleted]

this_user 1y ago

I think the main reason that "Semantic Web" has failed is that basically no one can even explain what the "Semantic Web" is or what it's good for. It's all just a bunch of generic sounding buzzwords about exchanging data in some way.

achierius 1y ago
Is it that hard? Instead of just providing data, you provide data plus "semantic tags" that make the data machine-indexable. It was ultimately meant to solve the same sort of "fuzzy-search" problem that we today can use LLMs for: "find me a website which sells home goods" could be addressed with tags that classify a page as a marketplace, and therein one which sells home goods. I think the real problem is that this requires a cohesive ontology, and if you've ever gotten really into tagging your notes/bookmarks/whatever you'll know how hard that can be.
- fabrice_d 1y ago
  Yes, most of the problem with the semantic web is that you end up with having to agree on how to describe the world: what are the concepts, and how they are related. This kind of work on semantic networks has been done for a while in computational linguistics for natural language processing, but it's very tedious. For instance users of the Minitel in France in the 80s could lookup vets by querying the yellow pages directory with sentences such as "my dog is sick". Nice tech, but not that useful and not very discoverable either. LLMs promise to just discover all these relations between concepts for you and do the right thing instead. Sometimes it works, sometimes not...
  - jcelerier 1y ago
    > Sometimes it works, sometimes not... Sometimes it won't work because there just isn't agreement between humans on what the concept is. Semantic also fails there.

blitzar 1y ago

> the semantic web failed It failed because they couldn't figure out how to stuff ads in.

bastawhiz 1y ago
It failed because nobody wanted to use it. Nobody built a compelling product from it, nobody wanted to author the data, nobody cared to use it when anyone did. It wasn't killed, it never got started because it never had a useful purpose.
- phatskat 1y ago
  I remember learning XML and XSLT from library books in the late 90’s and found it interesting, but couldn’t find a use for it - I wasn’t really handling data in any meaningful way back then, it was all just hobby learning, but in the decades since I’ve touched XML _at all_ maybe three times? Once was a Salesforce integration I wish I could fully forget, the other times were client one-offs when they had a few things stored in XML that we needed to pipe into WordPress.

kiitos 1y ago

> I believe we should be "pushing" context to the models rather than giving them directions on how to "pull" the context themselves. Models have very very very limited capacity for context, it's one of their primary bottlenecks, therefore it's important to optimize (minimize) that information as much as possible, allowing the model to pull what it decides it needs makes that constraint much easier to satisfy.

zoogeny 1y ago
>what it decides it needs This is what I am suggesting: relying on the model to decide what it needs is maybe not the best use of the available context. It might be better for us to give it the information we are certain it will need.
- kiitos 1y ago
  I'm talking about situations where the user wants to ask questions about data that's many orders of magnitude larger than what can be included in any LLM request context. I just provide access to the data (via MCP server, RAG server, whatever) and my question/prompt, it's the LLM's responsibility to do everything else.

jazzyjackson 1y ago

Interesting observation. I've been kinda hyped about XML/XSLT lately because I was working on a JSON macro expansion language (just four different macro tags that replace themselves with the macro's expansion, #= #& #? #! assignment, substitution, conditional branch like cond, and call for custom functions) and realised I was re-inventing XSLT, but what I really wanted was xpath, a way to describe traversal over graphs, back and forth along different axes, it's actually an amazing spec. Then I found basex [0] which pulls arbitrary XML documents into a queryable database that can be have queries described in XPATH or XQUERY. In my mind the best way to create a reliable natural language interface to a dataset without hallucination would be to hand over XML schemas to the system prompt and have it write the queries to retrieve the data. [0] https://basex.org/ https://basex.org/

zoogeny 1y ago
What I miss is E4X [1]. The ability to grab collections of child elements and collections of descendent elements made working with XML bearable. 1. https://en.wikipedia.org/wiki/ECMAScript_for_XML https://en.wikipedia.org/wiki/ECMAScript_for_XML

th0ma5 1y ago

The Semantic Web has yet to fully fail. Most companies have implemented a closed world limited version of it internally. It has already been proposed as a solution to correct LLM outputs by many people.

sbierwagen 1y ago

>LLMs appear to work very well with structured text (XML Plausible. >Markdown What? Markdown is specifically designed to be the least structured markup format possible, the absolute minimum set of features. Did you mean JSON or something?

MarkMarine 1y ago

I found this talk really interesting at conj, argues that RDF and the semantic web may have finally found its niche. https://youtu.be/OxzUjpihIH4?si=DRSp1n9u56iGbZFZ https://youtu.be/OxzUjpihIH4?si=DRSp1n9u56iGbZFZ

crq-yml 1y ago

I occasionally dally with XML in hobby code as a document source format, but I think what drives me away at the end is silly stuff with syntax, because it is a big spec well beyond the angle-bracket stuff, it wants to cover all the bases, do security right and do character encoding right - which means that "plain text editing" in it is some really unintuitive stuff where you can type in something like this paragraph and it might be parsed in a compatibility mode, but it won't be valid. As an interchange format or something loaded into application software tailored for it, it has more legs - and LLMs definitely wouldn't have any trouble making sense of it, which is good. A lot of yesteryear's challenges came from programmers short on time and eager to hack in features taking a heavily structured spec and wielding it like a blunt instrument. "XML? Sure, I can write a regex for that." Repeat that across three different programs and three different authors and you have a mess. There is a format that I've hit upon that actually does get at what I want for myself, and that's BBCode. That's a great source format for a lot of stuff - still basically an angle-bracket, but with the right amount of structure and flexibility to serve as a general-purpose frontend syntax. Early implementations were "write a regex for that" but after decades of battle-testing, there are more graceful parsers around these days as well.

cube2222 1y ago

> I believe we should be "pushing" context to the models rather than giving them directions on how to "pull" the context themselves. I believe MCP "Resources"[0] are what you're looking for. [0]: https://modelcontextprotocol.io/docs/concepts/resources#resources https://modelcontextprotocol.io/docs/concepts/resources#reso...