We're also seeing behemoths like Google and Meta both fail to keep up with OpenAI and Anthropic. Microsoft has given up on SOTA training. Loads of once promising LLM training companies are no longer relevant at the SOTA stage such as Cohere, Mistral.
I've said this countless times but SOTA LLM market looks like a classic monopoly/duopoly market over time. Each generation requires magnitudes more resources to train and you can only compete if you've made enough money on your previous generation.
On the contrary, small efficient models using recent improvements should be more sustainable than huge frontier models that require billions and years to train
The obvious draw-down on resources being used by companies following the token price hikes?
The fact that in the testimonials both frontier labs quote the same company (who I'm led to believe is still tokenmaxxing).
The fact that we've not seen actual productivity benefits or new products resulting from people outside the companies using it and a lot of things that in most businesses would result in a lot of investor skepticism and concern.
The fervent development and focus on 'the next big thing'.
We're also seeing behemoths like Google and Meta both fail to keep up with OpenAI and Anthropic. Microsoft has given up on SOTA training. Loads of once promising LLM training companies are no longer relevant at the SOTA stage such as Cohere, Mistral.
I've said this countless times but SOTA LLM market looks like a classic monopoly/duopoly market over time. Each generation requires magnitudes more resources to train and you can only compete if you've made enough money on your previous generation.