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Imagination? Or more seriously perhaps a higher tolerance for not 100% accurate output?
I don't expect or demand 100% accuracy. As to imagination... perhaps. I'm not sitting around trying to think up things to have it do. I've just tried using it to speed up rote stuff, but I find it's faster and easier just to do it myself to begin with.
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I don't expect or demand 100% accuracy. As to imagination... perhaps. I'm not sitting around trying to think up things to have it do. I've just tried using it to speed up rote stuff, but I find it's faster and easier just to do it myself to begin with.
What is some of the stuff that you tried it for?
But my original comment wasn't really about me in particular, it was a general question about what the difference between the two groups are.
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> If you actually use it you know it's incredibly useful for learning, getting answers to general problems that 99% of the time work fine and helps you understand its answers. The amount of times it's wrong or misleading is not significant enough to even be annoying during day to day use. Just talking about current practical usefulness here not even speculating about the future, just want it's useful for today. We us…
I am having good conversations with the thing about books as I read them and having it summarize parts I want to keep notes on and make knowledge graphs, and construct new worked examples and diving into specific topics and having significantly enhanced learning experiences with it as a partner literally every day for the last few months. So you're entitled to your opinion but it's simply not the same thing as a sear…
I spent some time talking to chatgtp about the history of art philosophy and technology, as if we were writing a book together.
I found it was great to just get a very broad overview and then ask questions about the things I wanted to know more about.
Not a groundbreaking way to use an LLM but I really enjoyed it.
I'm going to take your idea of talking to it about books too.
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I haven't found it to be more than very marginally useful in my life. It's interesting that some people think it's incredibly useful and others find it not worth the bother. I wonder what the difference is?
I use it for tons of things personally. 1. Data reformatting, data parsing, anything that requires transforming data in anyway. E.g. give me all blah in this massive raw content of whatever. Give this data as json, this as csv. 2. Writing small scripts to do various other data related actions, automations. 3. Summaries. Extracting key points. Asking questions about content I don't understand well. Asking clarificatio…
Microsoft could 'embrace' a significant portion of ChatGPTs use cases, if they trained up something 80% as good as ChatGPT and bundled it with Office 360.
We've seen AI techniques find new homes in Photoshop, 3D modelling software, ect.
ChatGPT needs it's own use case.
It’s like nobody wants to talk about reasonable solutions that incrementally make things better, everything has to be some meme “revolution”
It feels like we are well on our way toward the Trough of Disillusionment in the Gartner hype cycle for ChatGPT. It’s losing users daily. People are saying that it’s gotten worse since launch (don’t know if this is true but it’s what I’m hearing). As far as I know, it hasn’t revolutionized anything except spam generation.
I wish people would just do some deeper investigation before forming opinions based on their biases. If you actually use it you know it's incredibly useful for learning, getting answers to general problems that 99% of the time work fine and it helps you understand those answers. The amount of times it's wrong or misleading is not significant enough to even be annoying during day to day use. Just talking about current…
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I wish people would just do some deeper investigation before forming opinions based on their biases. If you actually use it you know it's incredibly useful for learning, getting answers to general problems that 99% of the time work fine and it helps you understand those answers. The amount of times it's wrong or misleading is not significant enough to even be annoying during day to day use. Just talking about current…
> I wish people would just do some deeper investigation before forming opinions based on their biases. well then they wouldn’t be people now, would they? your reaction is fair. and rare.
He read something he didn’t like and then attacked the person who said it by basically calling them an unthinking robot. It’s not fair and it’s incredibly common.
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I wish people would just do some deeper investigation before forming opinions based on their biases. If you actually use it you know it's incredibly useful for learning, getting answers to general problems that 99% of the time work fine and it helps you understand those answers. The amount of times it's wrong or misleading is not significant enough to even be annoying during day to day use. Just talking about current…
I didn’t say it wasn’t useful to some people, I just said it hadn’t revolutionized anything. Also, the Gartner hype cycle ends with the “Plateau of Productivity,” in which the technology is proven to be useful over the long term, so it is sort of implicit in my comment that I expect we will ultimately find lots of niches where LLMs are useful. Maybe you should have gotten ChatGPT to explain that to you before you mad…
Isn't this a bit of an oxymoron?
I feel like every comment on HN of mine now lately is just defending ChatGPT, but I don't think that's a reason to self-censor my comments... yet.
I was watching a car chase on youtube yesterday and used an LLM to tell me the city location based on a description of the news station logo. So that was a "niche" I guess. I also got it to teach me how to use the https://gene.iobio.io/ software as I was using it, and I'm pretty good at it now! I asked it to help me to understand the connotations of several similar sentences in another spoken language I'm learning. It's helped me with understanding property tax appraisal records. We use it at work daily to analyze code, it shortens research by 30% or so. Calling it "niche" is 100% correct: yes it's very good at its "niches" which happen to be... almost everything except math? Have it craft a choose-your-own-adventure detective story and get back to me, because that niche is surprisingly fun.
If you can predict the implications of this technology or make an insightful assessment beyond "we don't have flying cars yet" ... let me know.
How much money does pg have on OpenAI?
The cap table is moot in the near-term because of the profit precedence structure.