Comment by aurareturn
7 hours ago
I’m still looking for no-moatists to logically explain why there is no moat in SOTA LLMS.
That paper released by a lone Google employee 3 years ago still misguiding people it seems.
7 hours ago
I’m still looking for no-moatists to logically explain why there is no moat in SOTA LLMS.
That paper released by a lone Google employee 3 years ago still misguiding people it seems.
The vast majority of people simply don't need SOTA models. I run most of my programming on a single 7900 XTX with Qwen 3.8 27b. I'm more interested in scaling out to run more instances of the model in parallel, than I am in scaling up to better models.
My reasoning is that we have seen multiple small labs come out of nowhere and create impressive models.
Impressive doesn't mean sustainable.
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
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"Impressive doesn't mean sustainable."
The frontier labs at the current rate are also not sustainable.
You make some incredibly stupid assumptions - like assuming revenue growth rate of Anthropic and OAI will continue on.
Elon-Musk type stuff. lmfao.
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