The end game of generative AI
I’m now starting to be convinced that the only maybe-possibly-sustainable use case of AI is going to be ad-driven entertainment/chatbots/“virtual girlfriend” type apps, as well as low-effort social malware such as spam, astroturfing, and phishing, running on very old non-reasoning models (and small diffusion models for generating the “photos” of your artificial girlfriend).
I say this because a trillion+ dollars have been spent on making generative AI productive enough to replace humans, and so far, there has been zero use cases that are even plausible. The cost per inference for reasoning models is absolutely exploding to literally hundreds- or thousandfold over non-reasoning models, and there is little evidence that anything works as claimed.
Low-effort chatbots, though, have been shown to effectively prey on the addictive nature of staring into an interactive funhouse mirror, and has the potential to generate more “engagement” (i.e. ad impressions) than traditional algorithmic social media.
Unless there is a significant advance in semantic modeling and inference, this is as good as it gets: we are now seeing the limits of predictive pattern-matching models. Improvements in “reasoning” are quite clearly asymptotic—a huge increase in token output and processing time only produces marginal improvement in output quality, and is not worth the extra money in virtually all cases.