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This AI Boom Will Also Bust

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Re: This AI Boom Will Also Bust

#241

Post by xamuel »

logicallee wrote: post #214
xamuel wrote: post #209

Earlier quoted context omitted.

If P=NP then we already have the hardware to crack RSA encryption. The above sentence is true, but it has no bearing on anything.

don't you think it would have a lot more bearing if you had 7 billion devices nonchallantly walking around cracking RSA every day using the same or less hardware? (but we couldn't reverse-engineer them, because they were obfuscated in biology)? The fact that they weren't reverse-engineered (yet) would still have huge bearing on everything. By 7 billion samples I mean the humans walking around. Your analogy with an RS…

Interesting observation. If brains routinely cracked RSA, that could be evidence that P=NP.

Still it wouldn't help us find the P-time algorithm in question. We could say "it seems to exist", but that would not imply "we'll discover it any day now".

Re: This AI Boom Will Also Bust

#242

Post by dquail »

xamuel wrote: post #204
logicallee wrote: post #138

Earlier quoted context omitted.

It is not suffering from hype. There is too little hype. People are vastly underestimating what is about to happen. See my comments here: https://news.ycombinator.com/item?id=13079598 under our recent article " Artificial Intelligence Generates Christmas Song". Basically, if there is no pixie dust that makes humans intelligent, and instead it is a matter of the architecture of the brain and the first few years of sup…

>if there is no pixie dust that makes humans intelligent [...] then neural net breakthroughs [...] have the potential [...] You're assuming neural nets are the right model. Like a 19th century person saying, "if there is no pixie dust ... then eventually Newtonian mechanics will explain these unexpected wobbles we see in the planets' orbits."

Yes. Furthermore, neural nets are just one small part of the solution to [edit] general intelligence. A truly scalable intelligence that learns on its own, and doesn't rely on "the right answers" through training data by human experts. Without this training data, neural nets can't do much ...

Re: This AI Boom Will Also Bust

#243

Post by dquail »

bogomipz wrote: post #226
ma2rten wrote: post #101

I think this field is suffering from some confusion of terminology. In my mind there are three subfields that are crystallizing that each have different goals and thus different methods. The first one is Data Science. More and more businesses store their data electronically. Data Scientists aim to analyze this data to derive insights from it. Machine Learning is one of the tools in their tool belt, however often they…

This was a really nice breakdown, thanks. You mentioned that that Deep learning was a method of choice for AI researched because Deep it has unlocked a lot of new application. I have a question - is it also a "method of choice" for researchers because its not well understood yet why Deep Learning actually works?

Good question. Just one anecdotal data point here ... So take it for what it's worth. I'm a grad student focusing on reinforcement learning but have a lot of interaction with many deep learning folk. I'd have to say that they seem mostly motivated to learn how to make deep learning even more powerful and how to apply it. Not so much solving what's going on inside the box.

Re: This AI Boom Will Also Bust

#244

Post by euske »

I have a hard time understanding why even technical people use the term "AI" today. Its use should be limited to sensational media and cheesy sci-fi. It's roughly equivalent to saying "computery thingamabob". I would call a pocket calculator an AI too. Why not? It carries out certain mental tasks better than our brains do.

Re: This AI Boom Will Also Bust

#245

Post by dquail »

_fh5n wrote: post #141

I understand that most people working with deep learning wouldn't want this type of thinking to spread amongst the public, and I surely don't want it either. But you have to be totally unaware of reality to think that DL is the definitive tool for AI. Most impressive results in DL in the past 2 years happended like this: >deepmind steals people from the top ML research teams in univerisites around the world >these pe…

Agree generally. Except being unimpressed unless performance is achieved on sub Google scale hardware. Today's Google supermachine is tomorrow's raspberry pie. No need to artificially constrain our bounds. There is, after all, the inevitability of Moores law.

Re: This AI Boom Will Also Bust

#246

Post by ktRolster »

ma2rten wrote: post #101

I think this field is suffering from some confusion of terminology. In my mind there are three subfields that are crystallizing that each have different goals and thus different methods. The first one is Data Science. More and more businesses store their data electronically. Data Scientists aim to analyze this data to derive insights from it. Machine Learning is one of the tools in their tool belt, however often they…

A lot of standard automation is being called 'AI' too, because that sells.

Re: This AI Boom Will Also Bust

#247

Post by coldtea »

tim333 wrote: post #33

It seems a little odd that the author is focusing on machine learning not being terribly good for prediction from data to counter the "this time is different" argument. The reason this time is different is we are in a period when AI is surpassing human intelligence field by field and that only happens once in the history of the planet. AI is better at chess and go for example, is slowly getting there in driving and w…

>The reason this time is different is we are in a period when AI is surpassing human intelligence field by field and that only happens once in the history of the planet.

Citation needed.

Re: This AI Boom Will Also Bust

#248

Post by mcguire »

logicallee wrote: post #138
sidlls wrote: post #110

Earlier quoted context omitted.

It's also suffering from hype. And the criticism you note isn't one-directional in the field at large. I'm finding that ML/AI researchers deriding ML/Data engineers and "scientists" as not doing "real" ML or AI is becoming a thing, similar to how some computer scientists deride engineering as not doing real computing.

It is not suffering from hype. There is too little hype. People are vastly underestimating what is about to happen. See my comments here: https://news.ycombinator.com/item?id=13079598 under our recent article " Artificial Intelligence Generates Christmas Song". Basically, if there is no pixie dust that makes humans intelligent, and instead it is a matter of the architecture of the brain and the first few years of sup…

Historically speaking, this isn't the first time someone has said any of that.

Re: This AI Boom Will Also Bust

#249

Post by unscaled »

ma2rten wrote: post #163
sidlls wrote: post #110

Earlier quoted context omitted.

It's also suffering from hype. And the criticism you note isn't one-directional in the field at large. I'm finding that ML/AI researchers deriding ML/Data engineers and "scientists" as not doing "real" ML or AI is becoming a thing, similar to how some computer scientists deride engineering as not doing real computing.

It's also suffering from hype. If you mean hype in media and general public, I agree with you. Research is inherently risky and uncertain, often that is not conveyed correctly. Also research results are often oversold. If you mean that big tech companies are overinvesting in Machine Learning then I have to disagree. It's not a coincidence that the companies that invested the most in Machine Learning (Google and Faceb…

You mean, some tech companies understand the difference between Data Science, AI in general, ML and Deep Learning and try to utilize the best tools in hand to handle their data.

But what is driving this hype, as well as the Blockchain hype, is not engineer-driven companies like Google, but rather MBA-driven buzzword-friendly tech companies (imagine Balmer-era Microsoft), non-tech companies who want to share the cake, the media and finally the investors who are misled by the rest, but end up creating a capital-based feedback loop for them.

As far as the people driving the hype train right now are concerned, Machine Learning is the way you do AI, and Deep Learning is just a more powerful (ahem deeper) version of Machine Learning. This is what AlphaGo used to defeat Lee Sedol, so it's obviously superior, and we should use it to process all data, in the same way we should strive to store everything on a blockchain, which is clearly superior to hash tables and databases.

Re: This AI Boom Will Also Bust

#250

Post by itissid »

Thomson Reuter's ET&O and Risk division laid off 2000 people recently to fund a new center near university of Waterloo to provide "answers"(Its their mission statement) by recruiting people to provide deep learning solutions. NY suffered deep cuts. The sad part is it seems the leadership just want to use deep learning as a way to justify doing what they are doing, which is "starting from scratch"
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