Technology

Musk faces challenges attracting engineers

No shit. I have no idea who still works at Xitter. I think they must have whittled it down to workaholic Nazi pigs who personally share in Elon’s psychopathy. Because no self respecting tech workers would put up with his bullshit when there’s a whole industry they could go work in.

SpaceX is different. Aerospace is a narrower field and SpaceX is truly at the forefront of it. For a time, Tesla was also at the forefront of its field, doing things that no one else was.

But Xitter and xAI or whatever the fuck it’s called… they have zero advantages with which to attract engineering talent. Elon doesn’t know what the fuck he’s doing when it comes to software and never has. He tries to push tech workers around the same way, he’s going to find they can get other jobs at superior organizations and likely for more money.

Grok is this true?

Since Elon Musk is a super genius who sleeps on the floors of his factories couldn't he just run xAI himself without any staff?

Posting Part 1 and Part 2 which breakdown LeCun's JEPA model and more.

@sanitation 乐观点看，LeCun 说的“failure”可能更多是指 xAI 当前的商业化进度，而不是技术本身。比如 Grok-1 的开源就证明了模型能力还在——只是产品化的 timing 和路径可能跟 OpenAI 不同。你觉得这种“技术 vs 商业”的二分法在 AI 创业里是否普遍存在？我这边观察到不少团队在开源模型上反而活得更滋润，我们整理了几个案例对比 如果对你有参考价值的话。

It needs to cook a lot longer. Better and more efficient algorithms. Fix the hallucinating, implement quality control.

The Pope is kind of Catholic too.

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.

no shit sherlock

Wow, REEEEEEAAAALLLLLY, Yann? So fucking astute! We gotta get this guy to Vegas, IMMEDIATELY.

Great, but why would I respect the opinion of someone who works at Meta?

Says the person who took a billion to make the next thing after the reset.

Ok but why is the thumbnail a picture of Garrison Keillor?

Dot com 2.0 wooooo

We can only hope

Wow the only technology that is designed to lie to you is a failure? Pattern recognition means it can recognize wrong patterns.