[djhn]

I can take on a slightly weaker form in good faith: professionally it’s a non-starter until private, open source inference can be self-hosted and the ROI is clear enough to invest in that.

And on the ROI side, trying things out regularly, I haven’t seen the positive ROI in the limited time I’ve dedicated to exploring the tools. I’ve restricted experimenting to 4 hours per month, because spending more than 2.5% of the month chasing productivity improvements that realistically seem to be 10-20%, will quickly eat into those gains. After accounting for token costs, it ends up being a wash.

[theshrike79]

"I studied math 4 hours per month and I can confirm that mathematics is stupid"

You can't learn how to use _anything_ by experimenting 4 hours a month.

[djhn]

I think I should also clarify, I work in the training of encoder-decoder transformer models. Before the ChatGPT era I worked on on encoder-only transformer models. I'm not unfamiliar with the literature and general discourse. I just do not use LLMs for programming.

[intended]

The poster provided numbers and thresholds they used to evaluate the utility of a business product.

With infinite time anything is possible, but since we live within constraints, discussing practical, real world thresholds or evaluation methods is a worthwhile use of our time.