Yah, people don’t seem to get that LLM can not consider the meaning or logic of the answers they give. They’re just assembling bits of language in patterns that are likely to come next based on their training data.
The technology of LLMs is fundamentally incapable of considering choices or doing critical thinking. Maybe new types of models will be able to do that but those models don’t exist yet.
A grown man I work with, he’s in his 50s, tells me he asks ChatGPT stuff all the time, and I can’t for the life of me figure out why. It is a copycat designed to beat the Turing test. It is not a search engine or Wikipedia, it just gambles it can pass the Turing test after every prompt you give it.
Honestly though, with a bit of verification, chatgpt 4 gives waaaaaay better answers than any search engine. Like, it’s how it was back when you’d just ask Google a plain-english question and it’d give you SOMETHING at least.
Again, verify everything it tells you, it’s still prone to hallucinations, but it’s a damn good first step.
Right, which is why I suggested to verify whatever it spits out, I’m just saying it’s not entirely outlandish to ask it quick questions as opposed to your search engine of choice.
Well, I tried to test it and it started OK, but then gave me a content violation as it was generating, so that may be one of the ones that don’t work as well.
People want functioning web searching back, but rather than address issues in the industry breaking an otherwise functional concept, they want a new fancy technology to make the problem go away.
It works well if you know what to use it for.
Ever had something you wanted to Google, but couldn’t figure out the keywords?
Ever saw someone use a specific technique of something, which you could describe, but wouldn’t be able to find unless someone on a forum asked the same question?
That’s were chatgpt shines.
Also for code it’s pretty sweet
But yeah, it’s not a wiki or hard knowledge retriever, but it might help connect the dots
There are techniques to make these kinds of errors less common already today. For example, you can ask it to think through its answers step by step using first principals. If you and an LLM to do that it will write out the letters line by line which gives it enough context to correctly answer using the improved probability the context window gives it. You can even ask it to write programs to answer questions so it could write a quick script to do it programmatically.
The main reason you don’t see AIs doing this today is that producing all that extra context is slow and expensive and it’s unnecessary a lot of the time for most prompts. As the technology gets faster and cheaper and the use cases get more complex these techniques will be used more and more often.
While the technology does have fundamental flaws, that doesn’t mean there aren’t ways to work with those flaws to avoid the problems they have when using the raw output.
Yah, people don’t seem to get that LLM can not consider the meaning or logic of the answers they give. They’re just assembling bits of language in patterns that are likely to come next based on their training data.
The technology of LLMs is fundamentally incapable of considering choices or doing critical thinking. Maybe new types of models will be able to do that but those models don’t exist yet.
A grown man I work with, he’s in his 50s, tells me he asks ChatGPT stuff all the time, and I can’t for the life of me figure out why. It is a copycat designed to beat the Turing test. It is not a search engine or Wikipedia, it just gambles it can pass the Turing test after every prompt you give it.
Honestly though, with a bit of verification, chatgpt 4 gives waaaaaay better answers than any search engine. Like, it’s how it was back when you’d just ask Google a plain-english question and it’d give you SOMETHING at least.
Again, verify everything it tells you, it’s still prone to hallucinations, but it’s a damn good first step.
Sure. But take it for what it is. It is a language model designed to imitate humans writing. What the future holds, I can’t say
Right, which is why I suggested to verify whatever it spits out, I’m just saying it’s not entirely outlandish to ask it quick questions as opposed to your search engine of choice.
Like if I ask it for the lyrics of a song it’ll give me the lyrics?
Well, I tried to test it and it started OK, but then gave me a content violation as it was generating, so that may be one of the ones that don’t work as well.
Anything copyright related gets blocked like this, I don’t remember the other example, but this one was in recent memory
People want functioning web searching back, but rather than address issues in the industry breaking an otherwise functional concept, they want a new fancy technology to make the problem go away.
It works well if you know what to use it for. Ever had something you wanted to Google, but couldn’t figure out the keywords? Ever saw someone use a specific technique of something, which you could describe, but wouldn’t be able to find unless someone on a forum asked the same question? That’s were chatgpt shines.
Also for code it’s pretty sweet
But yeah, it’s not a wiki or hard knowledge retriever, but it might help connect the dots
There are techniques to make these kinds of errors less common already today. For example, you can ask it to think through its answers step by step using first principals. If you and an LLM to do that it will write out the letters line by line which gives it enough context to correctly answer using the improved probability the context window gives it. You can even ask it to write programs to answer questions so it could write a quick script to do it programmatically.
The main reason you don’t see AIs doing this today is that producing all that extra context is slow and expensive and it’s unnecessary a lot of the time for most prompts. As the technology gets faster and cheaper and the use cases get more complex these techniques will be used more and more often.
While the technology does have fundamental flaws, that doesn’t mean there aren’t ways to work with those flaws to avoid the problems they have when using the raw output.