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Over half of all tech industry workers view AI as overrated
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this post was submitted on 21 Nov 2023
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ChatGPT has never worked well for me. Sure, it can tell you how to center a div, but for anything complex it just fails. ChatGPT is really only useful for elaborating on something. You can give it a well commented code snippet, ask it to add some simple feature to it, and it will sometimes give a correct answer. For coding, it has the same level of experience as a horde of highschool CS students.
Sorry that my personal experience with ChatGPT is 'wrong.' if you feel the need to insult everyone who disagrees with you, that seems like a better indication of your ability to communicate than mine. Furthermore, I think we're talking about different levels of novelty. You haven't told me the exact nature of the framework you developed, but the things I've tried to use ChatGPT for never turn out too well. I do a lot of ML research, and ChatGPT simply doesn't have the flexibility to help. I was implementing a hierarchical multiscale LSTM, and no matter what I tried ChatGPT kept getting mixed up and implementing more popular models. ChatGPT, due to the way it learns, can only reliably interpolate between the excerpts of text it's been trained on. So I don't doubt ChatGPT was useful for designing your framework, since it is likely similar to other existing frameworks, but for my needs it simply does not work.
You talk a confident, condescending game for someone who cant substatiate any of their claims lol.
EDIT: Dear lord after looking through your comments i regret enabling you. Fuck isreal, free palestine, AI is overhyped...
LOL
Let's play a little game, then. We bothe give each other descriptions of the projects we made, and we try to make the project based on what we can get out of ChatGPT? We send each other the chat log after a week or something. I'll start: the hierarchical multiscale LSTM is a stacked LSTM where the layer below returns a boundary state which will cause the layer above it to update, if it's true. the final layer is another LSTM that takes the hidden state from every layer, and returns a final hidden state as an embedding of the whole input sequence.
I can't do this myself, because that would break OpenAI's terms of service, but if you make a model that won't develop I to anything, that's fine. Now, what does your framework do?
Here's the paper I referenced while implementing it: https://arxiv.org/abs/1807.03595