LeCun, who previously served as Meta's chief AI scientist, didn't mince words. "xAI is kind of a failure, frankly, because the founding team has" departed, he said,...
This is what people like Musk and Zuckerberg don’t seem to understand.
Training scales very poorly past a certain cluster size, especially if you go for new architectures to actually pursue improvements, hence reports of GPUs being tasked with busywork just to meet utilization quotes. Increasing data size and training scale hits diminishing returns, quick, or even regresses models because the bulk data is shit and the model is too inefficient. A prime example: Llama 4. “Superstar” AI engineers are better and Tweeting and sycophantic gaslighting than coding something interesting.
In other words, I’d argue there’s a much smaller “sweet spot” for pure LLMs that these billionaires are way, way past. And no one is telling them no because they’re too rich to hear it. It’s all going to collapse on itself because scaling like that just does not work.
This is what people like Musk and Zuckerberg don’t seem to understand.
They know, but can’t admit it. Pretend and keep the stock price going up makes them money, so for them it’s still working. Meanwhile they hope for a breakthrough, bail-outs or a new hype train to jump on.
AI is so weird, it absolutely is useful and has uses, but it absolutely is NOT what these billionaires want it to be.
And even IF IT COULD BE all they claim, it would literarily cause an economic collapse.
The truth is that AI is a tool that’s useful, but anyone in those companies trying to dampen things will be immediately moved to the side in favor of a guy saying, dude we can go to the moon with this trust me!
So yea… I don’t know how we get out of this… It’s very similar to the dot-com bubble. Internet was/is important and transformative but it wasn’t what everyone was claiming… So the crash came.
They don’t even need to dampen, just redirect. Pay engineers to make them specialized tools, don’t waste so much money on GPUs, and give part of the compute to the community to tinker with, instead of hoarding it and doing squat.
More GPUs =/= better AI.
More data =/= better AI.
More tech bro “superstars” =/= better AI
This is what people like Musk and Zuckerberg don’t seem to understand.
Training scales very poorly past a certain cluster size, especially if you go for new architectures to actually pursue improvements, hence reports of GPUs being tasked with busywork just to meet utilization quotes. Increasing data size and training scale hits diminishing returns, quick, or even regresses models because the bulk data is shit and the model is too inefficient. A prime example: Llama 4. “Superstar” AI engineers are better and Tweeting and sycophantic gaslighting than coding something interesting.
In other words, I’d argue there’s a much smaller “sweet spot” for pure LLMs that these billionaires are way, way past. And no one is telling them no because they’re too rich to hear it. It’s all going to collapse on itself because scaling like that just does not work.
They know, but can’t admit it. Pretend and keep the stock price going up makes them money, so for them it’s still working. Meanwhile they hope for a breakthrough, bail-outs or a new hype train to jump on.
No, they don’t.
They’re surrounded by yes men. And from everything I hear them say, they don’t understand the first thing about how LLMs actually work.
AI is so weird, it absolutely is useful and has uses, but it absolutely is NOT what these billionaires want it to be.
And even IF IT COULD BE all they claim, it would literarily cause an economic collapse.
The truth is that AI is a tool that’s useful, but anyone in those companies trying to dampen things will be immediately moved to the side in favor of a guy saying, dude we can go to the moon with this trust me!
So yea… I don’t know how we get out of this… It’s very similar to the dot-com bubble. Internet was/is important and transformative but it wasn’t what everyone was claiming… So the crash came.
They don’t even need to dampen, just redirect. Pay engineers to make them specialized tools, don’t waste so much money on GPUs, and give part of the compute to the community to tinker with, instead of hoarding it and doing squat.