@codinghorror “I can cite several dozen very specific examples in the last 2-3 weeks where it saved me, or my team, quite a bit of time.”

Please do, if you can. Because most time I’ve tried to use LLMs for work the error rate ends up costing me MORE time than I would have spent without, and most AI boosters are short on specifics. We just had a presentation at my job on how we all need to be using AI with no case studies of how it’s actually been useful so far.

@sethrichards here's one: a friend confided he is unhoused, and it is difficult for him. I asked ChatGPT to summarize local resources to deal with this (how do you get ANY id without a valid address, etc, chicken/egg problem) and it did an outstanding, amazing job. I printed it out, marked it up, and gave it to him.

Here's two: GiveDirectly did two GMI studies, Chicago and Cook County and we were very unclear what the relationship was, or why they did it that way. ChatGPT also knocked this out park and saved Tia a lot of time finding that information out, so she was freed up to focus on other work.

I could go on and on and on. Email me if you want ~12 more specific examples. With citations.

But also realize this: I am elite at asking very good, well specified, very clear, well researched questions, because we built Stack Overflow.

You want to get good at LLMS? learn how to ask better questions of evil genies. I was raised on that. 🧞

@codinghorror The problem is not "LLMs are useless and when the bubble bursts they go away," they aren't going away any more than websites went away when the .com bubble burst.

The problems are
1. They are a 6/10 tool being advertised as an 11/10 tool with the folks selling this stuff consistently overstating what they're capable of doing.
2. The few hundred billion spent building them needs the 11/10 promises to come true in order to be justified.
3. They're really good at making up answers that appear *plausible* but are also completely wrong, and verifying the answers is becoming increasingly difficult as the top search results are increasingly flooded with output from the same LLMs.
4. 'AI' is being used to try to sell a bunch of completely unrelated stuff like 'copilot+ pcs' even though everything meaningful in the LLM space only runs in datacenters due to GPU memory limitations.