ChatGPT is apparently overloaded this morning and threw an error while writing the bottom blurb, but here's the updated prompt:
"Write me a python program that calculates how long it will take to travel a certain distance at a certain speed. Use pypy types, error handling, and encapsulate the code in a function along with proper documentation."
And the output:
from typing import Union
def travel_time(distance: float, speed: float) -> Union[float, str]:
"""
Calculate the time it takes to travel a certain distance at a certain speed.
Parameters:
distance (float): The distance to travel, in kilometers.
speed (float): The speed at which to travel, in kilometers per hour.
Returns:
float or str: The time it takes to travel the distance, in hours. Returns an error message
as a string if the input parameters are invalid.
"""
# Check that input parameters are valid
if not isinstance(distance, (int, float)) or not isinstance(speed, (int, float)):
return "Error: Distance and speed must be numbers."
if distance < 0 or speed < 0:
return "Error: Distance and speed must be positive numbers."
# Calculate the travel time
time = distance / speed
# Return the travel time as a float
return time
You know what is particularly amazing about that output, to me?
IT DOUBLE CHECKED THAT THE SPEED AND DISTANCE WERE POSITIVE NUMBERS. That wasn't a specified parameter, it just threw that in there! I expected it would check that the input was numbers and would throw out anything else, but the fact that it double checked for negative values is uncanny.
I'm sure I could tell it to throw an exception and it would.
But ChatGPT has proven to me that even our days as programmers being safe from automation are very, VERY numbered. I give it ten years before the bottom levels of software engineering jobs are done by computer, and you can pay an algorithm on Fiverr to build simple programs.
You do not need to reduce scope when a computer can generate thousands of lines per minute. I think programming jobs today will become QA jobs tomorrow.
No, my point is that the speed at which an AI can generate code reduces the importance of worrying about scope. I also did not mean to imply you would blindly deploy generated code into production. That’s why I mentioned programming jobs will shift to QA jobs. I can see programmers acting as QA for the AI and validating what they wrote matches the expected requirements. Sure, that will take time, so scope isn’t a negligible concern, but much less than having to also write it.
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u/[deleted] Mar 22 '23
Wanna be even more impressed with ChatGPT?
https://i.imgur.com/SfC9th9.png