Maybe the business model is to break even on bleeding edge models while making money on the long tail of usage once systems are tuned for a specific model and running in production.

▲

NoDodgeQuestion 21 minutes ago | parent | next [-]

How can system be tuned for a specific model? Model is fungible, often one model strictly greater on both quality and price.

▲

seizethecheese 10 minutes ago | parent | next [-]

Think of it this way: you are at an enterprise business. You have a workflow implemented a year ago that is working just fine. Swapping out the model for a new one changes behavior in unpredictable ways. Eventually, you'll do it once cost is low enough, but it takes serious labor to validate this, so you'll wait a long enough time for Google to make money.

	▲	10 minutes ago \| parent [-]
		[deleted]

▲

nickserv 14 minutes ago | parent | prev | next [-]

Prompts can certainly be tuned to a particular model, where updating the model actually results in worse performance. This is perhaps less true today than a year or two ago, but we have seen this on newer models as well. Typically, the less specific the instructions are, the less it's a problem. But sometimes you really need to get into specifics to get good results. Area of work is code porting and translation.

▲

andai 10 minutes ago | parent | prev | next [-]

The business model is to replace the entire human economy.

▲

ipsod 20 minutes ago | parent | prev [-]

Models are not fungible, if you're building certain types of products on them.

▲

serf 14 minutes ago | parent [-]

this is becoming less true with every generation of model.

a decent model with a decent harness will determine when the knowledge base is lacking and attempt to fill the holes; thus the good general models can be very easily brought up to speed on niche domains.

	▲	j16sdiz 6 minutes ago \| parent \| next [-]
		Ugh? It is not just the knowledge Some model are more aggressive by default, some are more verbose by default. To get the result you want for your specific application, you run experiment with prompts and parameters.
	▲	margalabargala 11 minutes ago \| parent \| prev [-]
		You're thinking like an engineer. Think like a regulator.

▲

npn 8 minutes ago | parent | prev [-]

it is partly true, but like I said it is not 2025 anymore. models now get released more often, and still have notable progress so they can safely replace the old models while being faster/cheaper. and thank to chinese models the pricing is pretty much stable and affordable now.

and now we have ai agents to automatic migrate the system with new models. in the past we would need to spend hours to design the prompts, then test the output, then write codes to babysitting it. nowadays any ai agent can do it effortlessly.