3 ms·

LLMs are tremendous force multipliers. They don't replace humans but increase the productivity of people quite a bit

johnnyanmac 2y ago
Motte: "AI will make humans more efficient and help scale small businesses and creators" Bailey:" AI can replace your entire human labor (the most expensive cost of business) by scraping the content made by laborers on the internet without compensation" Unfortunately, businesses are being sold the Bailey. And the sad part is that some companies aren't even pretending to hide behind the motte. I'm sure some, many businesses won't fall for the hype, but many others will and it will take a huge toll on the workers as a result.
bugbuddy 2y ago
That’s not a certainty but an AI salesman’s pitch.
- brookst 2y ago
  Lived experience for me.
jordanb 2y ago
I've seen that claim made but I've not seen it in reality. There are examples of where LLMs are useful for information retrieval in that they can take vague queries and produce good summaries, but they're just as likely to produce reasonable-sounding nonsense that needs to be carefully verified. I've also seen examples where LLMs can produce code that implements well-defined toy problems but when used on a real software system with millions of lines of context they do not produce code that can remain coherent with the system. From what I've seen LLMs have yet to graduate from "impressive demo" and everyone characterizing them as being a revolution are still describing some potential future state with no real evidence that we'll get there with this technology or any time soon.
- ianbutler 2y ago
  We live in different realities then. I can't talk about details for my previous employer, but I can say there is an implementation involving LLMs saving Data Scientists a lot of time right now. I witnessed impact first hand and advised on the implementation and refinement for the group that built it.
- photon_collider 2y ago
  I agree that LLMs are less useful for smaller scale use cases. I’ve found success using them for creating mock data, reformatting unstructured text into structured data, and a few other menial tasks that would take me a while to do on my own. I think so much of the hype is about potential larger scale applications but the models just don’t seem reliable enough yet for that.

Motte: "AI will make humans more efficient and help scale small businesses and creators" Bailey:" AI can replace your entire human labor (the most expensive cost of business) by scraping the content made by laborers on the internet without compensation" Unfortunately, businesses are being sold the Bailey. And the sad part is that some companies aren't even pretending to hide behind the motte. I'm sure some, many businesses won't fall for the hype, but many others will and it will take a huge toll on the workers as a result.

bugbuddy 2y ago

That’s not a certainty but an AI salesman’s pitch.

brookst 2y ago
Lived experience for me.

jordanb 2y ago

I've seen that claim made but I've not seen it in reality. There are examples of where LLMs are useful for information retrieval in that they can take vague queries and produce good summaries, but they're just as likely to produce reasonable-sounding nonsense that needs to be carefully verified. I've also seen examples where LLMs can produce code that implements well-defined toy problems but when used on a real software system with millions of lines of context they do not produce code that can remain coherent with the system. From what I've seen LLMs have yet to graduate from "impressive demo" and everyone characterizing them as being a revolution are still describing some potential future state with no real evidence that we'll get there with this technology or any time soon.

ianbutler 2y ago
We live in different realities then. I can't talk about details for my previous employer, but I can say there is an implementation involving LLMs saving Data Scientists a lot of time right now. I witnessed impact first hand and advised on the implementation and refinement for the group that built it.
photon_collider 2y ago
I agree that LLMs are less useful for smaller scale use cases. I’ve found success using them for creating mock data, reformatting unstructured text into structured data, and a few other menial tasks that would take me a while to do on my own. I think so much of the hype is about potential larger scale applications but the models just don’t seem reliable enough yet for that.