Facebook AI Research (FAIR) is pretty reputable in the the AI/ML world
Thanks
Are the people who depend on it seriously incapable of taking up the load?
Probably. First of all most are domain experts not at all systems programmers. That’s the main value of such libraries.
And even for those who work close to the iron: plenty depend on, say, the Linux kernel without being able to write patches or even diagnose problems. And few, if any kernel developers have submitted patches to, say, GCC.
If these suggestions are credible and don't come from the Facebook team, that might sidestep your concerns.
Is there reason to expect this to change? Maintaining something like Torch and keeping it competitive in terms of speed is a HUGE amount of work for systems development, writing insane numbers of GPU kernels, etc. After having read it, I wouldn't quite yet call the tone of the discussion you linked "serious talk"...
[1]: https://discourse.julialang.org/t/state-of-machine-learning-...
BTW I was speaking generally about open source libraries, not just PyTorch, though indeed a Julia port sounds interesting.
You could argue that at it's peak Bell labs was a vanity division. That research may have changed the world, but very little of it likely ended up benefiting AT&T in any major way financially. It's telling that once AT&T was broken up Bell labs, while existing in some form for years after, was never reestablished.
But the days of telecom research making rapid and monumental advances peaked decades ago. Nokia or AT&T or Huawei or Ericsson could quadruple their R&D spending and it wouldn’t reestablish the impact of Bell Labs of last century, because it’s simply a much more mature field.
Whether it was a vanity division or not, it did serve one practical purpose for AT&T: it presented the company as a benevolent monopoly, spending its profits on developing technologies that benefitted the nation. This helped stave off anti-trust action for a long time.
I work for a big AI consultancy, but we haven't seen relevant work from Meta for a while. Their non-bayesian stuff is "meh" and often seriously misguided in their business approach. (which makes sense, they're not accustomed to work as consultants on setups with limited data)
Maybe you meant something else, but that’s how your statement reads.
What the hell is a big AI consultancy? As far as I can tell, these do not exist. Why would you expect to see meta doing consulting work at all?
It seems snake oil adjacent to me, at least at this point.