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Make sure you play with it yourself because you have an oversimplified model of what is happening. It’s definitely well beyond decimal point and punctuation is

Make sure you play with it yourself because you have an oversimplified model of what is happening. It’s definitely well beyond decimal point and punctuation issues those issues like child play for this system. You comment sounds like you haven’t actually use it before, I’m 99% sure. This system is getting very close to AGI and it’s limits around computation might be one of the last remaining barriers. Definitely nothing related to the . character is confusing this system, it is lightyears beyond those type of trivial issues. Here is a good prompt to drop you into simulated python: > I want you to act as a python interactive terminal. I will type actions and you will reply with what python would output. I want you to only reply with the terminal output inside one unique code block, and nothing else. Do not write explanations. Do not perform actions unless I instruct you to do so. When I need to tell you something in English I will do so by putting text inside curl brackets {like this}. Start with print(10).

qayxc 4y ago
For each impressive feat there's a simple, yet embarrassing counterexample (see for instance the comment by olooney below) that clearly demonstrates how far the model is from being considered an AGI. > Definitely nothing related to the . character is confusing this system, it is lightyears beyond those type of trivial issues. Is it, though? ChatGPT: Yes, I am confident that -26.66 + 90 = 10. This is because -26.66 is the same as -26.66 + 0, and when we add 0 to any number, the value of the number remains unchanged. Therefore, -26.66 + 90 is equal to -26.66 + 0 + 90, which is equal to -26.66 + 90 = 10. Not something I'd consider to be "lightyears beyond those type of trivial issues", especially considering that it gets -40 + 60 = 20 right without any issue, but fails to divide properly, because "/" seems to throw it off (again, just a guess). You argue with the same certainty as the model argues that -26.66 + 90 = 10 :)
- alchemist1e9 4y ago
  You need to prompt it to a pure computing environment and it’s results are much more impressive. When you mix english and code/math then it get’s confused easily. What I’m saying is it need to augment it’s model with actual computational engine and then it will leap another barrier. This is clearly already a massive leap forward somehow.
  - ookdatnog 4y ago
    Letting the model make calls to a computational engine (which will execute computation it doesn't understand) will improve apparent results but do nothing to meaningfully make the system more intelligent.
ookdatnog 4y ago
We have AI that's good at reasoning (symbolic AI) but there's no known way to integrate it with machine learning algorithms. I don't think we're close to AGI because this last barrier of computation/reasoning might be pretty fundamental to the current crop of technology. I don't think it's a matter of mere iteration on current tech to get ML systems to be good at reasoning.

qayxc 4y ago

For each impressive feat there's a simple, yet embarrassing counterexample (see for instance the comment by olooney below) that clearly demonstrates how far the model is from being considered an AGI. > Definitely nothing related to the . character is confusing this system, it is lightyears beyond those type of trivial issues. Is it, though? ChatGPT: Yes, I am confident that -26.66 + 90 = 10. This is because -26.66 is the same as -26.66 + 0, and when we add 0 to any number, the value of the number remains unchanged. Therefore, -26.66 + 90 is equal to -26.66 + 0 + 90, which is equal to -26.66 + 90 = 10. Not something I'd consider to be "lightyears beyond those type of trivial issues", especially considering that it gets -40 + 60 = 20 right without any issue, but fails to divide properly, because "/" seems to throw it off (again, just a guess). You argue with the same certainty as the model argues that -26.66 + 90 = 10 :)

alchemist1e9 4y ago
You need to prompt it to a pure computing environment and it’s results are much more impressive. When you mix english and code/math then it get’s confused easily. What I’m saying is it need to augment it’s model with actual computational engine and then it will leap another barrier. This is clearly already a massive leap forward somehow.
- ookdatnog 4y ago
  Letting the model make calls to a computational engine (which will execute computation it doesn't understand) will improve apparent results but do nothing to meaningfully make the system more intelligent.

ookdatnog 4y ago

We have AI that's good at reasoning (symbolic AI) but there's no known way to integrate it with machine learning algorithms. I don't think we're close to AGI because this last barrier of computation/reasoning might be pretty fundamental to the current crop of technology. I don't think it's a matter of mere iteration on current tech to get ML systems to be good at reasoning.