971–980 of 1001 posts
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What people here forget is coding is a tiny minority of the actual usage. ~5% if I remember correctly? Their best market might just be as a better Google with ads
Yep, bulk of AI usage is generating marketing emails
I don't think marketing emails are written enough to constitute the "bulk" of it, but writing in general seems to be
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I’m with the people pushing back on the “confidence scores” framing, but I think the deeper issue is that we’re still stuck in the wrong mental model. It’s tempting to think of a language model as a shallow search engine that happens to output text, but that metaphor doesn’t actually match what’s happening under the hood. A model doesn’t “know” facts or measure uncertainty in a Bayesian sense. All it really does is t…
> A model doesn’t “know” facts or measure uncertainty in a Bayesian sense. All it really does is traverse a high‑dimensional statistical manifold of language usage, trying to produce the most plausible continuation. And is that that different than what we do under the scenes? Is there a difference between an actual fact vs some false information stored in our brain? Or both have the same representation in some kind o…
I work at the intersection of AI and investing, and I'm really amazed at the ability of this model to build spreadsheets. I gave it a few tools to access sec filings (and a small local vector database), and it's generating full fledged spreadsheets with valid, real time data. Analysts in wallstreet are going to get really empowered, but for the first time, I'm really glad that retail investors are also getting these…
Can't wait for being fired because some VP or other manager asked some model to prepare list of people with lowest productivity to pay ratio. Model hallucinated half of the data?! Sorry we can't go back on this decision, that would make us look bad! Or when some silly model will push everyone to invest in some radicoulous company and everybody will do it. Poisoning data attack to inject some I am Future Inc ™ company…
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I think the better word is confabulation; fabricating plausible but false narratives based on wrong memory. Fundamentally, these models try to produce plausible text. With language models getting large, they start creating internal world models, and some research shows they actually have truth dimensions. [0] I'm not an expert on the topic, but to me it sounds plausible that a good part of the problem of confabulatio…
That's right - it does seem to have to do with trying to be helpful. One demo of this that reliably works for me: Write a draft of something and ask the LLM to find the errors. Correct the errors, repeat. It will never stop finding a list of errors! The first time around and maybe the second it will be helpful, but after you've fixed the obvious things, it will start complaining about things that are perfectly fine,…
Not my experience. I find after a couple of rounds it tells me it's perfect.
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A part time minimum wage worker can't code
Check the wages of coders outside of the US
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Old people? I think it would be hard to find a lot of people under 20 who don't use ChatGPT daily. At least among ones that are still studying.
I wanted to reflect a bit on this. I have hard time to imagine why non-tech people would find a use for LLMs, let's say nothing in your life forces you to produce information (be it textual, pictural or anything that can be related to information). Let's say your needs are focused on spending good times with friends or your family, eating nice dishes (home cooked or restaurant), spending your money on furnitures, ren…
Re: books. Your imagination falters here too. I love sci-fi. I use voice AIs ( even made one: https://apps.apple.com/app/apple-store/id6737482921?pt=12710... ). A couple of times when I was on a walk I had an idea for a weird sci-fi setting, and I would ask AI to generate a story in that setting, and listen to it. It's interesting because you don't know what will actually happen to the characters and what the resolution would be. So it's fun to explore a few takes on it.
In my experience, the best models are already nearly as good as you can be for a large fraction of what I personally use them for, which is basically as a more efficient search engine. The thing that would now make the biggest difference isn't "more intelligence", whatever that might mean, but better grounding. It's still a big issue that the models will make up plausible sounding but wrong or misleading explanations…
I've been working on this problem with https://citellm.com, specifically for PDFs.
Instead of relying on the LLM answer alone, each extracted field links to its source in the original document (page number + highlighted snippet + confidence score).
Checking any claim becomes simple: click and see the exact source.
Wow, there's a lot going on with this pelican riding a bicycle: https://gist.github.com/simonw/c31d7afc95fe6b40506a9562b5e83...
I added GPT-5.2 Pro to my pelican-alternatives benchmark for the first three prompts: Generate an SVG of an octopus operating a pipe organ Generate an SVG of a giraffe assembling a grandfather clock Generate an SVG of a starfish driving a bulldozer https://gally.net/temp/20251107pelican-alternatives/index.ht... GPT-5.2 Pro cost about 80 cents per prompt through OpenRouter, so I stopped there. I don’t feel like spendi…
I work at the intersection of AI and investing, and I'm really amazed at the ability of this model to build spreadsheets. I gave it a few tools to access sec filings (and a small local vector database), and it's generating full fledged spreadsheets with valid, real time data. Analysts in wallstreet are going to get really empowered, but for the first time, I'm really glad that retail investors are also getting these…
Here's a nice parsing of all the important financials from an SEC report. This used to be really hard a few years ago. https://docs.google.com/spreadsheets/d/1DVh5p3MnNvL4KqzEH0ME...
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I ask for confidence scores in my custom instructions / prompts, and LLMs do surprisingly well at estimating their own knowledge most of the time.
I’m with the people pushing back on the “confidence scores” framing, but I think the deeper issue is that we’re still stuck in the wrong mental model. It’s tempting to think of a language model as a shallow search engine that happens to output text, but that metaphor doesn’t actually match what’s happening under the hood. A model doesn’t “know” facts or measure uncertainty in a Bayesian sense. All it really does is t…