The only way they’d not be API accessible is surely if they contained some new and extremely difficult to replicate innovation that prevents important capabilities from being commoditised.
What reason or evidence do you see that that is (or will be) the case rather than those features simply representing a temporary lead for some models, which others will all catch up to soon enough?
Yeah, this reminds me of the breathless predictions (and despair, some corners) that flew around shortly after the initial ChatGPT launch. “Oh, they have a lead so vast, no one could ever catch up.” “[Insert X field] is dead.” Et cetera. I didn’t buy it then, and I’m not buying it now.
Of course OpenAI and Anthropic wish they could dominate the application layer. I predicted that two years ago: that model providers would see their technology commoditized, and would turn to using their customers’ data against them to lock them out with competing in-house products. But I don’t think they will succeed, for the reasons rbren mentioned previously. Good application development requires a lot of problem specific knowledge and work, and is not automatable.
On the point of RL — I predict this will generate a some more steam to keep the investment/hype machine cranking a little longer. But the vast majority of tasks are not verifiable. The vast majority have soft success criteria or are mixed, and RL will not overcome the fundamental limitations of GenAI.
What reason or evidence do you see that that is (or will be) the case rather than those features simply representing a temporary lead for some models, which others will all catch up to soon enough?