this post was submitted on 19 Mar 2025
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It's ironic how conservative the spending actually is.
Awesome ML papers and ideas come out every week. Low power training/inference optimizations, fundamental changes in the math like bitnet, new attention mechanisms, cool tools to make models more controllable and steerable and grounded. This is all getting funded, right?
No.
Universities and such are seeding and putting out all this research, but the big model trainers holding the purse strings/GPU clusters are not using them. They just keep releasing very similar, mostly bog standard transformers models over and over again, bar a tiny expense for a little experiment here and there. In other words, it’s full corporate: tiny, guaranteed incremental improvements without changing much, and no sharing with each other. It’s hilariously inefficient. And it relies on lies and jawboning from people like Sam Altman.
Deepseek is what happens when a company is smart but resource constrained. An order of magnitude more efficient, and even their architecture was very conservative.
wait so the people doing the work don't get paid and the people who get paid steal from others?
that is just so uncharacteristic of capitalism, what a surprise
It’s also cultish.
Everyone was trying to ape ChatGPT. Now they’re rushing to ape Deepseek R1, since that's what is trending on social media.
It’s very late stage capitalism, yes, but that doesn’t come close to painting the whole picture. There's a lot of groupthink, an urgency to "catch up and ship" and look good quick rather than focus experimentation, sane applications and such. When I think of shitty capitalism, I think of stagnant entities like shitty publishers, dysfunctional departments, consumers abuse, things like that.
This sector is trying to innovate and make something efficient, but it’s like the purse holders and researchers have horse blinders on. Like they are completely captured by social media hype and can’t see much past that.
Good ideas are dime a dozen. Implementation is the game.
Universities may churn out great papers, but what matters is how well they can implement them. Private entities win at implementation.
The corporate implementations are mostly crap though. With a few exceptions.
What’s needed is better “glue” in the middle. Larger entities integrating ideas from a bunch of standalone papers, out in the open, so they actually work together instead of mostly fading out of memory while the big implementations never even know they existed.