Comment by rusk | Hacker News Reader

Comment by rusk | Hacker News Reader

Parent Full thread

Edit: sorry just realised you’re making the same point as me more or less. Putting yourself in third person. I’ll let my comment stand anyhow :)

Screwing my face up, looking at this sideways … but it seems as though you’re saying that the Bozos of HN have nothing useful to contribute to this discussion based on … [rereads] … their lack of academic credentials in the area… you could say this about just about any HN post I’m just wondering why this one? Here’s a thing though … if the understanding of a technology is so nuanced … that Bozos can’t “get” it … is it really that mature? We had functioning computers for 50 years but it was only when the Bozos got their hands on it that things took off. Internet for 20. Cell phones for 10. How long are we dabbling with neural networks? 50 years or so? All I see in this most recent explosion in AI is a rapid jump in the availability of cores. Ala Malthus once that newly available “source of nutrition” has been used up we will see a rapid die off once more and it will be another 20 years once the Bozo intellect has caught up before we look at this topic en masse again. Dismiss the Bozos at your peril. You’re dependent on them for innovation and consumption. Your sincerely, a Bozo.

Not quite the same point. Yep some bozo is me but needn't be. There's plenty who share that suspicion of AI research but have little else in common. And all of us may be wrong for different reasons.

The vague point was to show someone with zero reputation, credentials, specific expertise in the field or anything much seems to be pretty convincing in response to this hugely funded ivory tower exercise by spitting, cocking an eyebrow and saying "So you think so, eh? Wanna bet?"

This is a statement about the state of AI research credibility. Do you feel the first breezes of a deep AI winter coming on? (I don't know, I'm disinterested but not uninterested. Rising tides lift all ships etc. And vice versa). Neutral nets are cool. Is all ML a bit overrated? Is learning a misleading name to give to applied statistics?

I don't have answers, just suspicions. I could be very wrong, of course.

I’ve a minor in psych so I like to think I have a bit of a non-techy perspective on this, and what’s being pushed now, forms just a segment of the overall topic of AI. It just so happens to be the segment that benefits from the technology we suddenly have a rapid increase in. There’s been great successes in areas where a degree of inference is required but this hardly qualifies as even mere intelligence, and in cases where neural nets have been deployed in more human centered tasks, or even well designed symbolic systems the results speak for themselves. What even is intelligence? I think we’re going backwards because we’re investing all this talent in this simple segment I fear largely to fatten the chip makers share price while neglecting tried and true approaches that deliver far better results but perhaps crucially have a higher operating cost … who remembers google of 2010 from whom the Internet in all her glory leapt forth, or iPhone spell check of 2015 where you could confidently batter out your messages with little fear it would make a fool of you; you’re not going to nurture a nascent intelligence if you’re going to be continually hobbling it for business reasons. I’m certain we will get there eventually if we don’t destroy ourselves before then but I don’t think the current trends portray a picture of how it will be. I think we have a long way to go ourselves before we can be worthy of creating our successor, but when/if it comes it will be a beautiful thing and we will embrace it as we would our own child.

The algorithms to train, initialize the networks, new architectures are far more important than the hardware advances. If people knew how to train NNs 50 years ago we would live in a different world.

We did. they just didn't have the same computation abilities back then.

I find it really interesting that when Richard Feynman did a sabbatical at Thinking Machines when they were developing the early parallel execution hardware that's really not worlds away from modern GPUs he got them in touch with one of the leading neural network theorists as an obvious use for the tech. When he wasn't fixing their hardware designs using systems of differential equations.

It would be an interesting thing to know more about.

the basic concepts underlying DNNs have been known for decades, it has been exponential increases in compute power that have made them practical

Reply on news.ycombinator.com