What do you think about structured outputs / JSON mode / constrained decoding / whatever you wish to call it?

To me, it's a criminally underused tool. While "raw" LLMs are cool, they're annoying to use as anything but chatbots, as their output is unpredictable and basically impossible to parse programmatically.

Structured outputs solve that problem neatly. In a way, they're "neural networks without the training". They can be used to solve similar problems as traditional neural networks, things like image classification or extracting information from messy text, but all they require is a Zod or Pydantic type definition and a prompt. No renting GPUs, labeling data and tuning hyperparameters necessary.

They often also improve LLM performance significantly. Imagine you're trying to extract calories per 100g of product, but some product give you calories per serving and a serving size, calories per pound etc. The naive way to do this is a prompt like "give me calories per 100g", but that forces the LLM to do arithmetic, and LLMs are bad at arithmetic. With structured outputs, you just give it the fifteen different formats that you expect to see as alternatives, and use some simple Python to turn them all into calories per 100g on the backend side.

Me too. It was my favorite talk of the ones I saw.

I wonder at what point all the self-driving code becomes replaceable with a multimodal generalist model with the prompt “drive safely”

[flagged]

Funny thing is that in more than one of the iron man movies the suits end up being bad robots. Even the ai iron man made shows up to ruin the day in the avengers movie. So it’s a little in the nose that they’d try to pitch it this way.

>> A recurring theme presented, however, is that LLM's are somehow not controlled by the corporations which expose them as a service. The presenter made certain to identify three interested actors (governments, corporations, "regular people") and how LLM offerings are not controlled by governments. This is a bit disingenuous.

> I don't think that's what he said, he was identifying the first customers and uses.

The portion of the presentation I am referencing starts at or near 12:50[0]. Here is what was said:

  I wrote about this one particular property that strikes me
  as very different this time around.  It's that LLM's like
  flip they flip the direction of technology diffusion that
  is usually present in technology.

  So for example with electricity, cryptography, computing,
  flight, internet, GPS, lots of new transformative that have
  not been around.

  Typically it is the government and corporations that are
  the first users because it's new expensive etc. and it only
  later diffuses to consumer.  But I feel like LLM's are kind
  of like flipped around.

  So maybe with early computers it was all about ballistics
  and military use, but with LLM's it's all about how do you
  boil an egg or something like that.  This is certainly like
  a lot of my use.  And so it's really fascinating to me that
  we have a new magical computer it's like helping me boil an
  egg.

  It's not helping the government do something really crazy
  like some military ballistics or some special technology.

Note the identification of historic government interest in computing along with a flippant "regular person" scenario in the context of "technology diffusion."

You are right in that the presenter identified "first customers", but this is mentioned in passing when viewed in context. Perhaps I should not have characterized this as "a recurring theme." Instead, a better categorization might be:

  The presenter minimized the control corporations have by
  keeping focus on governmental topics and trivial customer
  use-cases.

0 - https://youtu.be/LCEmiRjPEtQ?t=770

> If anyone has a browser plugin which automatically redirects to llms.txt sign me up.

Not a browser plugin, but you can prefix URLs with `pure.md/` to get the pure markdown of that page. It's not quite a 1:1 to llms.txt as it doesn't explain the entire domain, but works well for one-off pages. [disclaimer: I'm the maintainer]