111–120 of 198 posts
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We really need to start thinking of how to reduce magical thinking in the field. It’s not pretty. They literally quote biblical guidance for the models and pray that this would work. And start their prompts with “You”. Who is “You”?
“You” is an optimization for the human user. Here’s some insight: https://news.ycombinator.com/item?id=35925154
I like this step towards greater rigor when working with LLM's. But part of me can't help but feel like this is essentially reinventing the concept of programming languages: formal and precise syntax to perform specific tasks with guarantees. I wonder where the final balance will end up between the ease and flexibility of everyday language, and the precision / guarantees of a formally specified language.
I don’t think formal languages are going anywhere because we need the guarantees that they can provide. From Dijkstra: https://www.cs.utexas.edu/users/EWD/transcriptions/EWD06xx/E... You need to be able to define all of the possible edge cases so there isn’t any Undefined Behavior: that’s the formal part Humans can use LLMs to manipulate these languages to achieve specific goals. I can imagine designing formal langua…
They must hate lisp so much that they opt to use {{}} instead.
I like this step towards greater rigor when working with LLM's. But part of me can't help but feel like this is essentially reinventing the concept of programming languages: formal and precise syntax to perform specific tasks with guarantees. I wonder where the final balance will end up between the ease and flexibility of everyday language, and the precision / guarantees of a formally specified language.
But is it a step to greater rigor? Or is it an illusion of rigor? They talk about improving tokenization but I don't believe that's the fundamental problem of controlling LLMs. The problem with LLMs is all the data comes in as (tokenized) language and the result is nothing but in-context predicted output. That's where all the "prompt-injection" exploits come from - as well as the hallucinations, "temper tantrums" and…
And starting prompts with “You”? Seriously. Can we at least drop that as a start?
I like this step towards greater rigor when working with LLM's. But part of me can't help but feel like this is essentially reinventing the concept of programming languages: formal and precise syntax to perform specific tasks with guarantees. I wonder where the final balance will end up between the ease and flexibility of everyday language, and the precision / guarantees of a formally specified language.
Earlier quoted context omitted.
But is it a step to greater rigor? Or is it an illusion of rigor? They talk about improving tokenization but I don't believe that's the fundamental problem of controlling LLMs. The problem with LLMs is all the data comes in as (tokenized) language and the result is nothing but in-context predicted output. That's where all the "prompt-injection" exploits come from - as well as the hallucinations, "temper tantrums" and…
It is not a step towards greater rigor. They literally have magical thinking and “biblical” quotes from GPT 11:4 all other the place, mixing code and religion. And starting prompts with “You”? Seriously. Can we at least drop that as a start?
What is wrong with this?
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Consider how similar your comment reads, for an outsider, to this explanation of AWS InfiniDash: https://twitter.com/TartanLlama/status/1410959645238308866
I'm not considering outsiders. Why should I. It's a reasonable assumption that readers of HN are accustomed to ridiculous sounding tech product names. Further, this is a comment on a thread regarding a particularly new technology in a particularly newly thriving domain. The expectation should therefore be that there will be references to tech even more esoteric than normal. The commenter should have instead thought:…
You ran into the tech equivalent of poe’s law. You said something that makes perfect sense in your technical sphere, but it read as indistinguishable from parody to an audience unfamiliar with the technologies in question.
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> but it wasn't something the stakeholders outside of engineering even wanted Ha this reminds me of the craze for BDD/Cucumber type testing. Don’t think I ever once saw a product owner take interest in a human readable test case haha
I've used Cucumber on a few consulting projects I've done and had management / C-level interested and involved. It's a pretty narrow niche, but they were definitely enthusiastic for the idea that we had a defined list of features that we could print out (!!) as green or red for the current release. They had some previous negative experiences with uncertainty about what "was working" in releases, and a pretty slapdash…
I like this step towards greater rigor when working with LLM's. But part of me can't help but feel like this is essentially reinventing the concept of programming languages: formal and precise syntax to perform specific tasks with guarantees. I wonder where the final balance will end up between the ease and flexibility of everyday language, and the precision / guarantees of a formally specified language.
I don’t think formal languages are going anywhere because we need the guarantees that they can provide. From Dijkstra: https://www.cs.utexas.edu/users/EWD/transcriptions/EWD06xx/E... You need to be able to define all of the possible edge cases so there isn’t any Undefined Behavior: that’s the formal part Humans can use LLMs to manipulate these languages to achieve specific goals. I can imagine designing formal langua…
Absolutely not. LLMs do not "manipulate" language. They do not have agency. They are extremely advanced text prediction engines. Their output is the result of applying the statistics harvested and distilled from existing uses of natural language. They only "appear" human because they are statistically geared toward producing human-like sequences of words. They cannot choose to change how they use language, and thus cannot be said to actively "manipulate" the language.
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It is not a step towards greater rigor. They literally have magical thinking and “biblical” quotes from GPT 11:4 all other the place, mixing code and religion. And starting prompts with “You”? Seriously. Can we at least drop that as a start?
> And starting prompts with “You”? Seriously. Can we at least drop that as a start? What is wrong with this?
And if there is an attempt to define the model itself, then this definition should be correct, should not contradict anything and should be useful.
Otherwise it’s just dead code, waiting to create problems.