Perhaps this post will provide Generative AI use case that hadn’t been thought of, I see Chris’s post brilliantly provides a rewrite based on the question, and the code that's been shared (and knowledge the LM has). The experience I had that was more profound was when I used a SQL editor that gave suggestions that blew me away. When I peaked at the code what it was essentially doing was building a narrative around what it knew about my active connection to the ChatGPT engine to give WAY more context to what I would have posed to ChatGPT. So, where someone might write "rewrite this code EXAMPLE CODE to do something" the editor I saw was doing something more like... "<IDE>On an Oracle 6.5.1 system with parallelism 8 with table structures <the whole 9 yards> (including example data if you toggled that on)</IDE> rewrite this code EXAMPLE to do something." In the background the code I saw (open source project) even did a pre-generative AI "what convention of variable naming is mostly being used in (give all the variables names defined)" and then modifying the generative AI to ask, "with variables in <CamelCase> style". It did so many of these simple but smart things that only an integrated IDE could that really impressed me, you'd be amazed at how much crisper the results are given more details and minutia. The other thing that struck me is it was using a scoring mechanism to real time determine what sections were not maintainable and given the suggestions around that. If your query didn't seem offensive it said nothing, but if your query irked its maintainability score it would simply ask ChatGPT in the background "how to rewrite <CODE> to be more maintainable." When the IDE was taking these active measures to improve my code that's when I found the experience more profound. There are statistical functions to score the complexity of code and other maintainability metrics. The Data interface suggestions to show how to optimize the data is something that would require SAS to describe to a generative AI something that may not be apparent in just a simple code analysis or may require SAS to build/leverage engine specific generative AI. Maybe not in the current scope of work. The post analytic log would be a different type of AI to give suggestions about how their code performance has improved, or to show when performance is an anomaly. We often get tickets about why something is so slow, and it’s that they’re running on the 3rd of the month and their code is always slow on the 3rd of the month, they just never noticed it. Or they worked late at night and the system had no constraints and that’s why it was fast. It would help to cure a lot of tickets we deal with. I believe it's no mystery that s/he who conquers AI first will win this century.
... View more