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The AI Misinformation Epidemic

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Re: The AI Misinformation Epidemic

#111

Post by wiricon »

ilaksh wrote: post #75

Most of the people who have a strong machine learning or deep learning background are actually unaware of the large amount of existing research that applies to artificial general intelligence (AGI) because that group is just not mainstream. But there are groups who are combining cutting edge neural network research with AGI and seriously trying to build general intelligence. Researchers who are working on narrow AI t…

Care to share links to those labs' websites/relevant papers? I'm a deep learning researcher, and I've been noticing this gap that you mentioned between the DL community and what everyone else in AI is doing, and think it might be worthwhile trying to bridge that gap.

Re: The AI Misinformation Epidemic

#112

Post by psyc »

IMO, the practical sorts, such as this author, who want everybody's vision for AI to be as narrow as their present-year work is, suffer from the reverse affliction to what they think futurists suffer from. I will call this affliction "rationality-signaling".

Re: The AI Misinformation Epidemic

#113

Post by barrkel »

TuringNYC wrote: post #48

Here is my annoyance with AI Hype: people seeking extra tailwinds pitch their startups as "ML companies" even with the most tangential usage of ML. It drowns out real ML companies. Most people cannot tell the difference. At a hackathon recently, someone pitched their app as an "ML-driven app" though the only ML in there was some 1-line language translation feature they were consuming off Watson REST services for a ta…

Effort doesn't have much relationship with value. Nor does the complexity of the core tech. People don't pay for implementation details; geek points don't mean prizes.

Effort where it maximizes return, leveraging existing assets where possible, to solve problems for real customers, is what's valuable.

Newly built tech is a rapidly depreciating asset; the depreciation comes not only from the progressing state of the art elsewhere, but also in maintenance costs and lack of network effects. Open sourcing to offset the depreciation is risky too.

Re: The AI Misinformation Epidemic

#114

Post by visarga »

ekianjo wrote: post #90
ExactoKnight wrote: post #87

Earlier quoted context omitted.

Almost everything you listed there already started becoming common by the 1960's. Step back and forget about informational technology. Look at the world of atoms, not at the world of bits. Since the decommissioning of the Concorde, our fastest commercial means of transportation has actually been getting slower , not faster. Man hasn't reached farther out in space than the moon missions of the 1960s. The first half th…

Sure. But you cant seriously expect the discovery curve to be linear or exponential for that matter.

It's sigmoidal.

Re: The AI Misinformation Epidemic

#115

Post by ThomPete »

Fricken wrote: post #17

Welcome to the club. Now you know how Economists, healthcare professionals, skateboarders, basket weavers and anybody else whose domain knowledge runs deeper than the average joe's feels whenever their area of technical expertise becomes the subject du jour for the public at large.

In Danish we have a word "fagidiot" which means idiot of your field. It's the kind of things that make it impossible for someone who's been in the army to enjoy a movie if they don't use the machine gun properly or a designer to appreciate the casting in the end if the typography is not kerned properly.

The things that matter to someone who spent a lot of time in any given field are rarely the important things to anyone else.

Edit: And no it's not pronounced with a hard g but with a soft g.

Re: The AI Misinformation Epidemic

#116

Post by VHRanger »

iwintermute wrote: post #95
vanderZwan wrote: post #86

Earlier quoted context omitted.

Can you also put into words why? Sincere question, not being snarky; I also know the feeling of something feeling off but not knowing how to express it in words (yet).

Not op, but also from economics background - the issue with economics in public perception for me is that is't became modern "religion"/ideology and moved far from proper science. Especially "mainstream" economics theory. So the issue is not that it's getting misinterpreted due to lack of understanding. The issue there is that it's getting unscientific and politicised purposefully.

Is you "economics background" a BA, by any chance?

The people who say economics "became religion" are usually those whose only exposure to economics is through secondhand knowledge (ie. they read about it in media) or took a handful of undergraduate classes.

Take a look at what modern economics research looks like [1]. Seriously, read __any__ of those articles and come tell me with a straight face it's not doing normal science (come up with theory, test with empirical data).

Economics is the most scientific it's ever been, most graduate curriculum, and even some undergrad, are veering towards the applied statistics arm of economics because it's what's been most successful in the last 20 years. Granted there are empirical problems in, say, macro, but that's mainly due to lack of data.

Economics is also probably the most politicized it's been in a long time at the moment, I agree with you in that. Apart from a few venues like Planet Money or Freakonomics, there isn't much pop-economics like there is pop-science in other fields like physics. Moreover, the incentive to politicize economics is much greater than other sciences.

[1] http://www.nber.org/new.html is a good place for free versions of upcoming papers.

Re: The AI Misinformation Epidemic

#117

Post by VHRanger »

FabHK wrote: post #105
iwintermute wrote: post #95

Earlier quoted context omitted.

Not op, but also from economics background - the issue with economics in public perception for me is that is't became modern "religion"/ideology and moved far from proper science. Especially "mainstream" economics theory. So the issue is not that it's getting misinterpreted due to lack of understanding. The issue there is that it's getting unscientific and politicised purposefully.

Great book on this is James Kwak's "Economism" - the abuse of purported economic insight for political purposes. As just one simple example, good old Hekscher-Olin trade theory (a neat general equilibrium model with 2 countries, 2 goods, and 2 factors of production, capital and labor) "shows" that free trade is a good thing, leading to a Pareto improvement. But of course, that's predicated on a whole host of assumpti…

Right, but this is a political problem. H-O (or Ricardian trade) is about the simplest model of trade you can come up with to show the concept.

It's not like economists don't know there are problems in distribution of wealth -- one of the most discussed papers last year (see these podcasts [1] [2]) talks about the effects of China massively expanding trade with the US in early 2000s on some parts of the country.

Pretty much everyone has known for half a century what trade does, there's a political and logistical problem in redistribution, though (counties tend to get devastated, and people don't like to move).

Interestingly, trade has extremely similar labor market effects to automation.

[1] http://www.econtalk.org/archives/2016/03/david_autor_on_1.ht...

[2] http://freakonomics.com/podcast/china-eat-americas-jobs/

Re: The AI Misinformation Epidemic

#118

Post by thearn4 »

jacquesm wrote: post #104

A lot of start-ups are hyping themselves as deep-learning or something close to that in order to make themselves appear 'hot'. Recently I looked at a company that had absolutely nothing to do with deep-learning or even any kind of machine learning whatsoever and that still managed to sprinkle the various buzz-words with great regularity throughout their investor targeted docs. What I don't get about this behavior is…

What were the technical buzzwords that companies used to signal hotness in the industry before the ML hype train (startup or not)?

I know on the process & management side for large organizations, there's been a revolving door of Lean/Agile/6 Sigma/ISO 9000, each with their own set of certifications, colored belts, and army of advisors/consultants.

I like the idea of always being retrospective and asking what can be improved, but it's made me a bit cynical seeing management chase fads based on whatever a vendor tells them.

Re: The AI Misinformation Epidemic

#119

Post by visarga »

uwiiuvvwu wrote: post #101
ExactoKnight wrote: post #88

Earlier quoted context omitted.

Peter Thiel has made some other interesting observations: - that our language about the ‘developed' vs ‘developing' world is excessively bullish about globalization while implicitly pessimistic about technology. - that government has changed from thinking that progress can be achieved via planning, into thinking that it's more just there to watch random forces & statistics evolve the world. This change in mindset awa…

interesting points in this podcast http://www.talkhouse.com/comedian-tim-heidecker-talks-with-a... Adam Curtis argues that we no longer subscribe to grand visions and as a result we're floundering as our internet-induced bubbles send us into every more fragmented echo-chambers We're never going to achieve anything great again...it's the beginning of the heat-death of human progress! I think that the recent idolatry o…

> We're never going to achieve anything great again...

Wikipedia, the open source, and even massive online communities such as reddit are great things.

Re: The AI Misinformation Epidemic

#120

Post by unprepare »

charles-salvia wrote: post #8

Yeah, terms like "machine learning" and "AI" have basically become buzz words which, to most laymen, probably encourage the idea that we're on the cusp of creating Data from Star Trek. Unfortunately, the reality is that.... sorry... it's mostly just statistical algorithms based around regression and intermediate calculus. State-of-the-art "deep" neural networks are not really anything like the absurdly parallel, asyn…

Lets say an infant is 3 years old, thats 26,280 hours, lets say a baby sleeps about 2/3 of the time - lets call it 8600 hours of awake time.

8600 hours of 4k video at 60fps (i would say this is lower quality then the human eye) is 2.657 petabytes.

Thats not including the sense of touch or smell, which i am sure are comparable in the amount of data processed by a human.

We're looking at 5+ petabytes of data that a human has to learn from by age 3 - Whats wrong with taking petabytes of data in order to learn meaningful things?

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