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This AI Boom Will Also Bust

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Re: This AI Boom Will Also Bust

#31

Post by sgt101 »

IIIIIII wrote: post #13
jeyoor wrote: post #5

This article matches what I've been seeing anecdotally (especially at smaller tech firms and universities in the Midwest US). I've been hearing more folks in research and industry express the importance of applying simpler techniques (like linear regression and decision trees) before reaching for the latest state-of-the-art approach. See also this response to the author's tweet on the subject: https://twitter.com/and…

Saying that linear regression is easier to do properly than more complex methods like random forests, DL, boosting etc is like saying that people should code assembly instead of python

You might be being really subtle about python there ! I realize that one can create lines of code like :_ = ( 255, lambda V ,B,c :c and Y(VV+B,B, c -1)if(abs(V)abs(V)-0.4)/i ) ;v, x=1500,1000;C=range(vx );import struct;P=struct.pack;M,\ j ='x3+26,26,12,v,x,1,24))or C: i ,Y=_;j(P('BBB',(lambda T:(T80+T9 i-950T 99,T70-880T18+701 T 9 ,Ti(1-T452)))(sum( [ Y(0,(A%3/3.+X%v+(X/v+ A/3/3.-x/2)/1j)2.5 /x -2.7,i)*2 for \ A in C [:9]]) /9) ) ) (stolen from : http://preshing.com/20110926/high-resolution-mandelbrot-in-o...)

which could be seen as retrograde vs assembler (but not really for the very funny and brilliant code above - you have to see in formatted nicely and run it to realize that there are some great people out on the web!) perhaps in fact I would agree with this dig - some people do write horrid bits in their python code and python seems to facilitate (or enable) this behavior rather more than other modern languages like Julia. But taking your comment more at face value, reading it to say that more complex methods represent an evolution and that they should be accessed by users as they are easier or better I would disagree. It is easy to screw things up with a random forest or a booster in the sense of overfitting, focusing on the method and not the features and not understanding what the model extracted is telling you about the data. Often a regression model or a decision tree can reveal that there are a few simple things going on which say more about how a process or system has been implemented than the generating domain that that process or system is operating in. This can be gold dust. So, I think that they can be easier to use and simpler to understand, of course when they don't do the job better model generators are required.

Re: This AI Boom Will Also Bust

#32

Post by nilved »

whorleater wrote: post #8
adrenalinelol wrote: post #6

Earlier quoted context omitted.

No one can tell you for sure, if it's your passion do it, if you're hoping for a big payday, I'd reconsider.

I don't actually think that's true, if the "AI bubble" bursts at some point in the near future, the people who'll be in trouble with be those without formal education to back them up.

That's never really been how the industry works. Experience is more valuable than education, so you should get experience while you still can.

Re: This AI Boom Will Also Bust

#33

Post by tim333 »

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 will probably surpass general thinking at some point in the future though there's a big question mark as to when.

Re: This AI Boom Will Also Bust

#34

Post by spsgtn »

This reminds me of the stem cell research boom and bust of the late 90s and 00s. It turns out that the new and shiny toy doesn't work for everything. However, it's not really a bust, as AI, similar to stem cells applications, will continue to do wonders where it is the best tool for the job.

Re: This AI Boom Will Also Bust

#35

Post by h43k3r »

thesimpsons1022 wrote: post #29
h43k3r wrote: post #28

A little off topic but I think the VR boom will bust much more sooner than AI. I can't think of normal people wearing those heavy gears in their normal life. There will be its use cases in specialized applications like education, industry, games but I don't think it will get popular like an iPhone. AR is still OK since it augments real life but there is a long way before it will become mainstream.

have you tried it? i own an oculus and every family member i've seen has been shocked and loved it. Obviously the oculus is prohibitively expensive but with the release of Playstation VR i think the mainstream is poised to adopt it. I really believe the next game consoles that come out will simply be vr headsets

Game consoles will/should come with VR headsets. My point of view is daily normal consumption.

I wouldn't wear an Oculus while I am home sitting on my SOFA with my family members and not many people play games especially considering third world countries like India. VR would have its place but not to the likes of smartphones.

Re: This AI Boom Will Also Bust

#36

Post by UncleMeat »

iwritestuff wrote: post #3

I plan to enter a PhD program in 1-2 years to specialize in ML/Deep Learning. Assuming it'll take 5-6 years to complete my degree how applicable should my skill sets be in industry at that point?

If your plan ahead of time is to go into industry then a PhD is not a really great plan unless you will get a lot of personal satisfaction out of research. PhDs are incredibly inefficient from a professional development for industry perspective.

Re: This AI Boom Will Also Bust

#37

Post by cerrelio »

godmodus wrote: post #18
iwritestuff wrote: post #3

I plan to enter a PhD program in 1-2 years to specialize in ML/Deep Learning. Assuming it'll take 5-6 years to complete my degree how applicable should my skill sets be in industry at that point?

you'll be a programmer - that is what counts. How good of a programmer you will be will determine your success. never put your eggs in one basket (not saying you shouldn't become an ML expert though, that's pretty damn nice). as a Phd, you are probably good enough. as to ML, its adoption is hyped. it is powerful, but not as anyone really talks about. support vector machines and Bayesian learning have been around sinc…

> support vector machines and Bayesian learning have been around since the 70s/80s (ninja edit: SVM's since 1963! Markov Chains 1950s, Bayesian Learning/Pattern recognition sine the 1950's), but adoption has been slow due to the nature of business, which is now drooling over it since neural networks beat a few algorithms.

This is one of the things I find hardest about convincing managers and leads of. They think things like CRFs and Markov models are "new" methods and too risky. So they opt for explicit rule-based systems that use old search methods (e.g. A*, grid search), which hog tons of memory and processor. Those methods rarely ever work on interesting problems of the modern day.

They can understand the rule-based methods easily. They have a hard time leaping to "the problem is just a set of equations mapping inputs to outputs, and the mapping is found by an optimization method."

Re: This AI Boom Will Also Bust

#38

Post by nwjtkjn »

toomuchtodo wrote: post #21
whorleater wrote: post #8

Earlier quoted context omitted.

I don't actually think that's true, if the "AI bubble" bursts at some point in the near future, the people who'll be in trouble with be those without formal education to back them up.

> the people who'll be in trouble with be those without formal education to back them up. The people who can't hack it are those who'll be in trouble. Tech has never much been the place where credentials are necessary. Don't specialize and saddle yourself with years of college debt if you're unsure of the field's long term prospects.

FWIW, one does not accrue debt doing a PhD in something like Machine Learning.

Re: This AI Boom Will Also Bust

#39

Post by dheera »

pesenti wrote: post #11

When I was at Watson this is the first thing I told every customer: before you start with AI are you already doing the more mundane data science on your structured data? If not, you shouldn't go right away for the shiny object. This said I still believe the article is mistaken in its evaluation of potential impact (and its fuzzy metaphore of pipes). Unstructured or semi-structured or dirty data is much more prevalent…

And before you do mundane data science on your structured data, you should figure out if there is a better way to get cleaner raw data, more data, as well as more accurate data.

For example, I predict stereo vision algorithms will die out soon, including deep-learning-assisted stereo vision. It's useful for now but not something to build a business around. Better time-of-flight depth cameras will be here soon enough. It's just basic physics. I worked on one for my PhD research. You can get pretty clean depth data with some basic statistics and no AI algorithm wizardry. We're just waiting for someone to take it to a fab, build driver electronics, and commercialize it.

Re: This AI Boom Will Also Bust

#40

Post by jondubois »

Journalists and investors only seem to get excited about buzzwords - Maybe that's because they don't actually understand technology.

To say that technology is like an iceberg is a major understatement.

The buzzwords which tech journalists, tech investors and even tech recruiters use to make decisions are shallow and meaningless.

I spoke to a tech recruiter before and he told me that the way recruiters qualify resumes is just by looking for keywords, buzzwords and company names; they don't actually understand what most of the terms mean. This approach is probably good enough for a lot of cases, but it means that you're probably going to miss out on really awesome candidates (who don't use these buzzwords to describe themselves).

The same rule applies to investors. By only evaluating things based on buzzwords; you might miss out on great contenders.

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