[godelski]

ML researcher here.

I will second this. Even if you think localghost is wrong about AI, it is important to always trust that voice of skepticism (to a limit).

But I will say that we are in a hype cycle and as a researcher I'm specifically worried about this. I get that we have to bootstrap because you can't say "we want to spend money on research" (why?), but if you make a bubble the goal is to fill that bubble before it pops. The more hype you make, the more money you get, but the quicker that bubble pops. My concern here is that too much hype makes it difficult to distinguish charlatans form honest people. Charlatans will jump from cool topic to the next (don't trust someone who was a VR founder, then a crypto founder, and now a ML founder. Trust people who have experience and can stick with a topic for longer than a hype cycle).

The big danger, is if charlatans dominate the space, the hype disappears, and then there is no money for everyone. So if you do believe in the possibility of AGI and that AI/ML can make the world better (I truly do), make sure that we don't over hype. There's already growing discontent for products pushed too early with too big promises. If you really believe (like I do), you have to get rid of the bad apples before they spoil the whole barrel.

[mnky9800n]

Yes as someone who works in geophysics and AI I see a lot of people promising a lot of things that no neural network will be able to do no matter how much attention it has because good data is actually what people need and they typically lack it. There's a ton of use cases across geophysics for AI, I'm even organising a conference at the end of September about this. But imo there's a bigger need for better data and better software tools first.

[Yhippa]

This is such a good perspective and thank you for posting. I agree with your statements and of all the hype cycles that have happened, I think this does have a real shot of becoming something. Because of that I think they’re going to keep throwing money at this until someone figures it out. Because what else is there left to grift on in tech right now?

[godelski]

  > I think this does have a real shot of becoming something.

I wouldn't be doing a PhD if I didn't. PhDs are terrible. I'm amazed people do them for "the money" and not the passion.

  > Because of that I think they’re going to keep throwing money at this until someone figures it out.

My concern is who they throw money at, and even more specifically who they don't throw money at.

  Some people known to do carpet pulls, no prior experience in ML, and throw together a shitty demo that any ML researcher should be skeptical of?
  $_$ 
  PhD researchers turning their theses into a product?
  ._.

Something's off.... But I guess when Eric Schmidt is saying you should steal and ask for forgiveness later, I don't think anyone should be surprised when unethical behavior becomes prevalent.

  > Because what else is there left to grift on in tech right now?
 

l̶i̶f̶e̶Hype finds a way. There's always something to grift.

The key thing to always recognize: grifters are people who have solutions and are looking for problems (e.g. hamstring AI into everything) while honest people have problems and are looking for solutions (i.e. people understand the limits of what we can do, the nuances of these things, and are looking to fill in that gap). I can tell you right now, anyone saying anything should be end-to-end AI is a grifter (including Google search). We just aren't there yet. I hope we get there, but we are quite a ways. Pareto is a bitch when it comes to these things.