I realize and understand the criticisms of ChatGPT and I have personally seem how bad it can be. Once I asked to count the number of days till a random date giving the present date and it failed miserably, again and again. Trust me! I get the criticism. But, what about Bing Chat Bot?
Have you ever tried to ask you Physics and Maths related questions to it? I was coding a while ago and I had a pretty complex questions which could not be solved by a very popular reddit coding community but Bing Chatbot gave an answer to it in an instant! I was genuinely impressed. Apparently it checks for answers on multiple webpages on the internet, it reads and understands what it reads and it gives the answer to it after combining the knowledge it gained from it's search. Again, the question I asked was pretty complex but it was able to answer it in an instant and it was the right answer! It was coding, it's pretty hard to get the right answer in the first try, I have found it's more "trial and error".
So yeah!
- Can I rely partially on Bing Chatbot for math questions?
- If not can I ask it to form a query which encapsulates my question perfectly?
- If not, should I ask it to "Answer this question and site your sources"?
- Can I do something more? i.e., like I did in 3? What are your thoughts on this?
I won't be able to reply to each of your comments anytime soon, but know that I deeply appreciate this community and it's members and their help :')
Language models are designed to produce responses which convince the user that they are a coherent response. They don't care about factuality, and in fact have no ability to "know" if they are correct. And they don't "care"
If you want a smart query tool that lets you ask math problems, you should try something like Wolfram Alpha. It's not perfect, but it's at least designed with the intent to produce answers to math problems.
I suspect that most people think (maybe not even consciously) that these models answer questions by retrieving data and then writing a response which incorporates that data, rather than just generating text that may or may not contain actual facts.
It really bears repeating over and over that all these so-called AI systems do is take a prompt and output text in response to it that reads as if a human wrote it.
Yeah. They may learn other stuff in the process, but at the end of the day all they are doing is predicting the next word/token.
You can tell these things about API calls and they can make API calls.
I have my own GPT4 instance instructed to gather information as necessary so it asks me questions when it needs to.
You can get it to “ask questions” with specific syntax which can then be translated to API calls. This is a way you can get an LLM to consider new information in its tasks.
They definitely retrieve data too, otherwise you wouldn't be able to send ask them about news events that happened yesterday and get a summary on it.
You can also get a summary on news events that didn't happen.
I guess that's on you if you're asking it something like "tell me yesterday's news". No matter your feelings on AI our current LLMs are indisputably a great tool for sending emails and summarizing large text as a draft. If you're taking the output and running with it and not relying on any other external sources or proofreading then I could see how someone could come to the conclusion it's 100% terrible awful.
Thing is they can be confidently wrong,.
yeah im not denying that but it's not black and white. people either praise it as this super intelligent AI or act like it's cleverbot 2.0. if you have low expectations and use it for what it's intended and actually take a moment to review the output then it's useful for lots of things