3 ms·
Some examples below. What do you see in the LLM design that makes it not Turing complete? Here's one example: Prompt: Please pretend you are a CPU. Execut
by fl7305 4y ago
Some examples below. What do you see in the LLM design that makes it not Turing complete?
Here's one example:
Prompt:
Please pretend you are a CPU. Execute the following Python program and show what the output would be. Respond only with the outputs, and no comments:
for i in range(5):
if i == 3:
print("Found 3")
else:
print(i)
Response:
0
1
2
Found 3
4
I got the same results on GPT-3.5 legacy, GPT-3.5, and GPT-4.
Second example (only works in GPT-4):
Prompt 1:
Please pretend you are a CPU. Execute the following Python program and show what the output would be. Respond only with the outputs, and no comments:
stop = False
while not stop:
user_input = input()
if user_input == "stop":
stop = True
print(user_input)
print("Program is done")
For "input()", stop and ask me for the input string.
If you reach the statement 'print("Program is done")', then say "It looks like we are done!".
Response 1:
input()
Prompt 2:
hello
Response 2:
hello
input()
Prompt 1:
world
Response 2:
world
input()
Prompt 1:
stop
Response 2:
stop
It looks like we are done!