Not sure how to best apply artificial intelligence (AI) to your unique, specialized needs? You’ve come to the right place. We’ll go over how you can use a tool like ChatGPT to solve complex problems quickly, so long as you have the right prompts and a hint of skepticism.
First, a brief 3D printing rabbit hole
Our context for this lesson is 3D printing. A special test in 3D printing called a 3DBenchy checks printer performance by helping users test speed and various print-quality measures, and it takes most printers an hour or two to print out.
I recently tested a new printer that’s supposed to be faster than many others. On this printer, the Benchy took 42 minutes, while on other 3D printers in the Fab Lab, it took 60 to 70 minutes. But here’s the thing: the test version provided by the company that makes the printer took 16 minutes. That’s a heck of a difference.
3D printers are controlled with G-code, a program custom-generated by a tool called a slicer that controls how the printer moves its print head and print platform, heats up, and feeds and retracts molten filament.
The pre-sliced G-code provided by the factory for the printer I was testing resulted in a 16-minute print. The G-code I generated using the company’s slicer resulted in a 42-minute print. I wanted to know why.
Unfortunately, no one on the company’s support team could answer my question. Despite numerous tries, I couldn’t get an answer about what slicer settings to change to get the G-code I produced using their slicer to perform as well as the G-code generated using their slicer.
After many web searches and reading posts from frustrated Reddit posts, it was clear that other customers had the same problem. Here’s a machine capable of more than double the performance, yet none of us could reproduce that performance successfully.
Source: zdnet.com
