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This is incredibly, incredibly naive. "Within minutes, I learned" -- absolutely nothing. At most you've learned how the answers to your question would sound lik
by chx 4y ago
This is incredibly, incredibly naive. "Within minutes, I learned" -- absolutely nothing. At most you've learned how the answers to your question would sound like. They are not the answers.
- simonw 4y agoHow sure are you about that?
- chx 4y agoEven if the answers accidentally happen to be correct, that's just the broken clock happens to be correct twice a day. The information value of answers by ChatGPT is zero.
- dmbche 4y agoI mean did you read the discussion he had with the language model? Does it clarify anything better than you would get by skimming wikipedia? I have not found these explanations sufficient, while I have done a bit of chemistry and physics I understand the basics of light emissions, but reading this has the same value as reading the wiki article on LEDs to me.
- simonw 4y agoIt was a lot shorter than the Wikipedia articles.
- dmbche 4y agoSure - when I skim articles, I often don't read all of it and stick to what I'm interested in - I'd argue that even takes less time than chatting with chat-gpt and fact checking it (Edit: - and you get sources right away with wikipedia!)
- p-e-w 4y ago> They are not the answers. You can't possibly know that.
- chx 4y agoI can. Even if the answers accidentally happen to be correct, that's just the broken clock happens to be correct twice a day. The information value of answers by ChatGPT is zero.
- simonw 4y agoIt sounds to me like you're letting your firmly held existing biases get in the way of you learning a powerful new tool. As I said in https://simonwillison.net/2023/Apr/8/llms-break-the-internet/ https://simonwillison.net/2023/Apr/8/llms-break-the-internet... > This is the thing I worry that people are sleeping on. People who think “these language models lie to you all the time” (which they do) and “they will produce buggy code with security holes”—every single complaint about these things is true, and yet, despite all of that, the productivity benefits you get if you lean into them and say OK, how do I work with something that’s completely unreliable, that invents things, that comes up with APIs that don’t exist… how do I use that to enhance my workflow anyway?
- chx 4y agoThat large language models are stochastic parrots is not a bias, it's a fact. You feed it a very large amount of structured data and then put up a question which it'll answer with a series of those which are most likely to follow. There is nothing else.
- tempestn 4y agoYeah. And in doing so, it will usually give you the correct answers.
- simonw 4y agoI know how they work. What's so interesting to me about them is how useful they turn out to be despite the seemingly dumb and simple way they are built. I encourage you to experiment more! Here are my notes so far: https://simonwillison.net/tags/llms/ https://simonwillison.net/tags/llms/
- ipnon 4y ago“There’s no sense in being precise when you don’t even know what you’re talking about.” John von Neumann