So if we divide the cost of training and running a specifically-tailored ChatGPT by $183k, at what point would the company save money were it to go with the AI, versus paying for the engineers (and their office rent, etc...)?
Because I suspect that's almost certainly the kind of calculation they hoped to sit down and make were they to conclude this experiment successfully.
In 1800 what was the cost to from New York to LA at over 200 mph average speed?
What is the cost today?
The real question is over time how much will be able to reduce the energy and computation requirements to successfully train a model. The cost per unit conversions are also rather screwy in comparing AI with humans. For AI we have a rather well defined hardware + power + programming time that gives us a realistic answer. With humans we externalize the time and cost of training onto society. For example if your jr engineer that is getting close to going above the jr state gets hit by a bus what is the actual cost of that event to the company for onboarding and training? It's far more than the salary they are paid.
Do LLMs suffer from catastrophic interference? A SWE is expected to learn continuously as the dujour stack constantly changes under our feet. This can be brute force mitigated by epochal retraining from ground up but that will cost money. So the cost equation must include a periodic 'rebuild of the dev team'.
Because I suspect that's almost certainly the kind of calculation they hoped to sit down and make were they to conclude this experiment successfully.