Comment by mynameisash
5 hours ago
Not GP, but as a data engineer who has worked with data scientists for 20 years, I think the assessment is unfortunately true.
I used to work on teams where DS would put a ton of time into building quality models, gating production with defensible metrics. Now, my DS counterparts are writing prompts and calling it a day. I'm not at all convinced that the results are better, but I guess if you don't spend time (=money) on the work, it's hard to argue with the ROI?
In what field do you work?
> writing prompts and calling it a day
What does this mean? They’re not creating pull requests and maintaining learning / analytics systems?
This kind of vagueposting gets on my nerves.
> They’re not creating pull requests and maintaining learning / analytics systems?
Sure, they check prompts into git. And there are a few notebooks that have been written and deployed, but most of that is collecting data and handing it off to ChatGPT. No, they're not maintaining learning/analytics systems. My team builds our data processing pipelines, and we support everything in production.
> This kind of vagueposting gets on my nerves.
What is vague about my comment?
Whereas in the past, the DS teams I worked with would do feature engineering and rigorous evaluation of models with retraining based on different criteria, now I'm seeing that teams are being lazy and saying, "We'll let the LLM do things. It can handle unstructured data, and we can give it new data without additional work on our part." Hence, they're simply writing a prompt and not doing much more.