61–70 of 198 posts
I'm personally starting with learning Guidance and LMQL rather than LangChain just in order to get a better grasp of the behaviors that I've gathered LangChain papers over. Even after that, I'm likely to look at Haystack before LangChain. Just getting the feeling that LangChain is going to end up being considered a kitchen sink solution full of anti patterns so might as well spend time a little lower level while I se…
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.
So, in the end, we abandoned that project and years later just rewrote the system so we could write claim rules in EDN format (from the Clojure world) to make our own lives easier.
In theory, the business users could also learn how to write in this EDN format, but it wasn't something the stakeholders outside of engineering even wanted. On the one hand, their expertise was in insurance claims---they didn't want to write code. More importantly, they felt they would be held accountable for any mistakes in the rules that could well result in thousands and thousands of dollars in overpayments. Something the engineers weren't impervious to, but there's a good reason we have quality assurance measures.
This reminds me of the time when I wrote a cgi script. Basically instructing the templating engine (a very crude regex) to replace session variables, database lookups to the merge fields: Hello {{firstname}}! 1996 and 2023 smells alike.
Earlier quoted context omitted.
Not quite sure what the spirit of your comment is. But, yes, they are real technologies. Very confused as to why you would even find that dubious.
Not dubious, I just read your comment and it felt like I was reading satire. Even the cadence of your words felt funny. Anyway, I’m not surprised. It’s a new market, everyone’s in on it.
It’s pretty clear that we are in the phase where everyone is rushing to get a slice of the pie selling dubious thing and people start parroting word soup hoping they actually make sense and fearing they will miss out. That’s indeed what people often and rightfully satirise about the IT industry. That’s the joke phase before things settle.
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 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.
Hear me out, just incubated a hot new lang that's about to capture the market and VC hearts: SELECT * FROM llm
I’m not understanding how Guidence Accelerating works. It says “ This cuts this prompt's runtime in half vs. a standard generation approach.” and it gives an example of it asking LLM to generate json. I don’t see anywhere how it accelerates anything because it’s a simple json completion call. How can you accelerate that?
Let's say you're halfway through a generation of a json blob with a name field and a job field and have already generated
{
"name": "bob"
{
"name": "bob",
"job":
Then guidance passes control back to the model for generating the next field value.
{
"name": "bob",
"job": "programmer"
{
"name": "bob",
"job": "programmer"
}
Edit: spacing
Earlier quoted context omitted.
Not quite sure what the spirit of your comment is. But, yes, they are real technologies. Very confused as to why you would even find that dubious.
Consider how similar your comment reads, for an outsider, to this explanation of AWS InfiniDash: https://twitter.com/TartanLlama/status/1410959645238308866
I’m not understanding how Guidence Accelerating works. It says “ This cuts this prompt's runtime in half vs. a standard generation approach.” and it gives an example of it asking LLM to generate json. I don’t see anywhere how it accelerates anything because it’s a simple json completion call. How can you accelerate that?
Earlier quoted context omitted.
Not quite sure what the spirit of your comment is. But, yes, they are real technologies. Very confused as to why you would even find that dubious.
Not dubious, I just read your comment and it felt like I was reading satire. Even the cadence of your words felt funny. Anyway, I’m not surprised. It’s a new market, everyone’s in on it.
It might have saved me from having a ridiculous conversation about the cadence of my words, and instead there might have been a higher chance of someone saying something substantive about my assumptions regarding the technology.
But here we are.