Earlier quoted context omitted.
NO! This is the wrong approach that will turn us into serfs. We need big honking models that do what the leading foundation hyperscaler models do to within a few percentage points of measured performance. The small-scale models are not productive, and the duct tape solutions built on top of them are hobbyist-tier "year of Linux on desktop" toys. I imagine fedora-wearing, crypto-shilling, coupon-cutting boffins every…
Firstly, unless you are the leader of any of the faangs, you are a serf on the whole, if you believe in that philosophy as being relevant. We need the right tool for the job. Certain models have minimum energy expense no matter what the task is and that's often wasted, both on the scale of some tasks and also repetition. There is a place and a need for large models, local models, and single purpose models. The same w…
If you tell the open weights labs that you want tiny models, you'll get more shitty tiny models.
If tell them you don't want tiny models and you want big models, they'll change their focus.
> We need the right tool for the job.
The world has enough shitty tiny models. You can frankly distill your own without wasting the time of foundation labs.
> energy expense
You are so far removed from the discourse that I think I'm wasting my time talking to you. This is not about energy in the slightest.
> There is a place and a need for large models, local models, and single purpose models.
This is where 99.999% of the demand is. And if you look, you'll notice that most of the token usage is accruing to hyperscalers because the market isn't meeting this demand with enough alternatives.
The robotics industry will produce energy efficient models. Let them be the ones to press for that. Stop demanding cheapo LLMs, image, and video models. Big is all that matters in this domain.