SELECT 'black' AS outline_color
  FROM elements parent
  JOIN elements child ON parent.id = child.parent_id
  WHERE parent.data_theme = 'light'
    AND child.data_theme = 'dark'
    AND child.focused = true

eg this example:

  [data-theme="dark"] [data-theme="light"] :focus {
      outline-color: black;
  }

so we could write this also as, e.g.:

  outline-color(Y, black) if 
    data-theme(X, "dark") and
    parent(X, Y) and
    data-theme(Y, "light") and
    focused(Y)

if we want even more syntax sugar, we could do:

  Y.outline_color := black if
    X.data-theme == dark and
    Y.parent == X and
    Y.data-theme == dark and
    Y.focused

the declaration and scope of these variables is implicit here; if you want something even more ALGOL-family, we could write

  forall Y {
    Y.outline_color := black if 
       Y.data_theme == "dark" and
       Y.focused and
       Y.parent.data_theme == "light"
  }

> we copy and reapply patterns in different contexts and that might enable unexpected things

yeah, that's exactly what I am trying to do here. Mostly it doesn't go anywhere, but it's interesting for the hacker spirit within me :)

I think the conclusion (which I may not have made clear enough) is less like "These are limitations of modern CSS which ought to be fixed" and more "Maybe a CSS-like syntax could be added to a Datalog-like system and that would be helpful for making it more accessible to more engineers, navigating tree-shaped data, etc"

thanks for the feedback, anyway!

Comments URL: https://news.ycombinator.com/item?id=47893427

Points: 81

# Comments: 27

What would your ideal RDBMS / tooling look like, that facilitates 6nf effectively? Do you think it's more a limitation of the query/storage engine, or the query language (SQL), or the user interface? Do you think founding on Datalog (or similar), which kinda lends itself to "narrow" relations, instead of SQL which kinda lends itself to "wide" relations, would help here?

(I ask as one of my personal hobby-horses is trying to design better query languages and tooling, and 6nf/datalog maintains a kinda special place in my heart)

The basic idea is: at each auto-regressive step (each token generation), instead of letting the model generate a probability distribution over "all tokens in the entire vocab it's ever seen" (the default), only allow the model to generate a probability distribution over "this specific set of tokens I provide". And that set can change from one sampling set to the next, according to a given grammar. E.g. if you're using a JSON grammar, and you've just generated a `{`, you can provide the model a choice of only which tokens are valid JSON immediately after a `{`, etc.

[0] https://github.com/dottxt-ai/outlines [1] https://github.com/guidance-ai/guidance

n=1 here, though I've heard others say the same -- but I (fairly healthy 30s male, vaccinated) found Paxlovid massively reduced symptom intensity for me. Within a day my symptoms went from "top 5 fevers I've ever experienced, normal function significantly impaired" to "feels like a cold; can reasonably handle myself around the house and even take a software engineering interview".

I most likely would not have got a severe infection and probably would not have got Long Covid, given my age / health / vaccine status, even if I hadn't taken it; but nonetheless I'm glad I was able to get it. Definitely worth it for the weird taste (hard candy helps).

I think I’ve got a grasp of the fundamentals and the ability to learn fast on the job, but every MLE job listing I see wants “4+ years of experience training and deploying models in a production environment” or something (even non-Senior roles!). I’m not sure how to break into it, to acquire a MLE job to get the experience to acquire an MLE job. Does anyone have any advice?

a) a linear SSM (a form of RNN?) is equivalent to Attention without the scaling and softmax; and

b) Attention is "all you need" and the thing that made Transformers radically outperform all the previous architectures like LSTMs that used to dominate NLP;

does that imply c) the scaling and softmax parts of the attention equation, in particular, is the magic touch that makes Transformers work so well?

Then it could have syntax highlighting, auto complete, and so on. The type system for such a language could possibly include verifying shapes at compile time.

What would a language comprised of .ein source files for manipulating tensors, which compiles down to the same low level ops, look like?

They've made it harder for competitors like Google or TikTok to compete with Meta on the basis of "we have a super secret proprietary AI that no one else has that's leagues better than anything else". If everyone has access to a high quality AI (perhaps not the world's best, but competitive), then no one -- including their competitors -- has a competitive advantage from having exclusive access to high quality AI.

[0]: https://www.joelonsoftware.com/2002/06/12/strategy-letter-v/

[1]: https://gwern.net/complement