A few lessons learned concerning MotorDocAI’s work on a portable Motor Current Signature Analyzer using AI tools such as ChatGPT, GitHub Copilot, and other tools with Python and using Visual Studio Code as the IDE. We also go through the features of the resulting system that was created in about 8 weeks from concept to delivery.
“The danger of AI may not be in a technology that develops a will of it’s own. The real danger, it would seem, is that humans will simply believe anything the machines says, no matter how wrong.” – Matt Novak
In reality, using technology to support the structure of the system and troubleshooting, and not the key components, such as algorithms and the specific functions, results in more rapid development and deployment with potentially fewer errors. What should have been many months of development dropped to weeks but required a high level of expertise in the programming language and the technology being automated.
The danger of jobs replaced actually falls to the mediocre programmer or technician and those who do not try to understand what they are dealing with. In the case of such things as the business environment, if you are working from garbage data or incorrect assumptions then not only will you fail, you will automate that failure. This has been found over and over again in automation. In the case of digital transformation, our Podcast 50 topic, you MUST understand all aspects of the goal, the information, assumptions, and correctness of data Or. You. Will. Fail. Not something the marketing and sales people tell you, is it.
