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Machine Learning Expert Michael Jordan On the Delusions of Big Data
First time accepted submitter agent elevator writes In a wide-ranging interview at IEEE Spectrum, Michael I. Jordan skewers a bunch of sacred cows, basically saying that: The overeager adoption of big data is likely to result in catastrophes of analysis comparable to a national epidemic of collapsing bridges. Hardware designers creating chips based on the human brain are engaged in a faith-based undertaking likely to prove a fool's errand; and despite recent claims to the contrary, we are no further along with computer vision than we were with physics when Isaac Newton sat under his apple tree.
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... and despite recent claims to the contrary, we are no further along with computer vision than we were with physics when Isaac Newton sat under his apple tree.
That's true, I looked into object recognition for image classification by content. Face recognition is proceeding fairly nicely but doing stuff like just programmatically classifying/tagging images by whether they contain a car, airplane, house, tree, dog, mountain .... without even trying to do things like identifying the type of airplane/dog/car is pretty much undoable in any reasonable amount of time with human level accuracy needed on garden variety PCs and tablets which is the application I'd be interested in. The fastest and most accurate image classifier/tagger is still a human. Am still looking forward to they day that changes but I'm not sure that will be within my lifetime.
Only to idiots, are orders laws.
-- Henning von Tresckow
Since when does Michael Jordan know more about neuroscience than dunking?
This is why I don't take Ray Kurzweil's predictions seriously. People like Prof. Jordan, who would actually make the vision become reality, dont take Kurzweil's ideas seriously.
His Presponce: "Come on and slam"
Yeah, that and the fact that Kurzweil is the biggest hack on the planet.
I've never read anything by him before but it's one of the best pieces I've seen posted around in here in a long time. That guys oozes intellect.
This is where you're wrong and people need to stop thinking this way. Nowadays, any even moderately heavy compute job is shipped off to the cloud where it is done in massively parallel systems. Hell even Google Now and Siri need the cloud for simple voice commands. Picasa uses it for face recognition. All of these things are done in near real time due to our much faster and robust worldwide Internet. There is no reason to think that any of these jobs need to be done directly on the phone or laptop.
As it happens, I am a computer vision expert.
I do wonder how much useful stuff was done with the results from physics back then as opposed to emperical hand-hacking of everything. I suspect not much.
Computer vision has a long way to go. On the other hand, there are plenty of things which it does do, some of which are more or less impossible otherwise.
OCR is very useful. It runs the mail system of many countries and has plenty of use when it comes to digitising old documents. This would be possible, but deeply tedious by hand.
Structure from motion is used heavily in the film industry to work out 3D structure and motion for placing virtual objects. Almost impossible to do well without computer vision.
Photo stitching for automatic panoramas. Classic CV system, and my phone comes with it built in.
Number plate recognition. Apart from the rather unpleasant big brother potential, London's congestion charging system runs off this and it does very good things for London.
Those cameras/phones with face detection built in. Not sure how useful it is but it works.
Lego Fusion is a recently released game which appears to rely on computer vision.
Oh those phone based barcode and QR scanners. Very useful.
The pick and place machines which use vision for accurate placement.
This machine which is really awesome: https://www.youtube.com/watch?...
Lots of other industrial things are controlled by CV.
Certain types of super resolution microscopy are based on computer vision.
And that's just a few off the top of my head.
So yeah computer vision has a long way to go. On the other hand, it's out there doing real things right now. It might not be very advanced CV (the industrial stuff often is not because it needs to be reliable), but it's still CV and it's still being used.
SJW n. One who posts facts.
"[W]e are no further along with computer vision than we were with physics when Isaac Newton sat under his apple tree."
On the other hand, we have 10 times the population today so there are 10 Isaacs working on the problem.
Probably closer to 100.
I am doing a postdoc in applied statistics/machine learning and I was very surprised by this interview since it is contradictory to what Michael Jordan has himself expressed as an invited speaker at conferences as well as what his most recent research projects are focused at. It appears that, according to Michael Jordan himself as expressed on his webpage, the article is a hack-job where the journalist is completely misrepresenting his view on big data. To quote:
I’ve found myself engaged with the Media recently (...) for an interview that has been published in the IEEE Spectrum.
That latter process was disillusioning. Well, perhaps a better way to say it is that I didn’t harbor that many illusions about science and technology journalism going in, and the process left me with even fewer.
The interview is here: http://spectrum.ieee.org/robotics/artificial-intelligence/machinelearning-maestro-michael-jordan-on-the-delusions-of-big-data-and-other-huge-engineering-efforts
Read the title and the first paragraph and attempt to infer what’s in the body of the interview. Now go read the interview and see what you think about the choice of title.
The title contains the phrase “The Delusions of Big Data and Other Huge Engineering Efforts”. It took me a moment to realize that this was the title that had been placed (without my knowledge) on the interview I did a couple of weeks ago. Anyway who knows me, or who’s attended any of my recent talks knows that I don’t feel that Big Data is a delusion at all; rather, it’s a transformative topic, one that is changing academia (e.g., for the first time in my 25-year career, a topic has emerged that almost everyone in academia feels is on the critical path for their sub-discipline), and is changing society (most notably, the micro-economies made possible by learning about individual preferences and then connecting suppliers and consumers directly are transformative). But most of all, from my point of view, it’s a *major engineering and mathematical challenge*, one that will not be solved by just gluing together a few existing ideas from statistics, optimization, databases and computer systems.
Source: https://amplab.cs.berkeley.edu/2014/10/22/big-data-hype-the-media-and-other-provocative-words-to-put-in-a-title/
No, seriously. Here are some choice quotes:
"I read all the time about engineers describing their new chip designs in what seems to me to be an incredible abuse of language. They talk about the “neurons” or the “synapses” on their chips. But that can’t possibly be the case; a neuron is a living, breathing cell of unbelievable complexity."
"It’s always been my impression that when people in computer science describe how the brain works, they are making horribly reductionist statements that you would never hear from neuroscientists."
"Lately there seems to be an epidemic of stories about how computers have tackled the vision problem, and that computers have become just as good as people at vision."
"Even in facial recognition, my impression is that it still only works if you’ve got pretty clean images to begin with."
"I have a hobby of searching for information about silly Kickstarter projects, mostly to see how preposterous they are, and I end up getting served ads from the same companies for many months."
Here's the catch: all of these quotes are from the interviewer. Jordan has a lot of really nuanced claims here, but it's clear that the interviewer has an agenda of his own.
Garbage in, garbage out. Mindlessly throwing analytics at data which is garbage will result in ..... garbage. I have worked at a number of places where we aggregated data from numerous sources. I most cases when we QA'd those data we found missing data, stale data, and flat out incorrect data. We had to spend a large sum of $$ scrubbing it. Once a data stream is polluted cleaning it is almost impossible.
And the matter is made worse by poor DB design, anyone who designs a DB which allows nulls and does not make proper use of constraints should not be allowed anywhere near software development or data analysis, and DB engines which give you "eventuality consistent" data. "Faith based" is right.
putting the 'B' in LGBTQ+
WTH?
Hardware designers creating chips based on the human brain are engaged in a faith-based undertaking likely to prove a fool's errand;
Wouldn't it be a faith-based statement to say such a thing when other fields readily exploit the efficiencies the process of evolution has lead to?
Michael Jordan is talking about the pitfalls of machine learning, not big data which is about much more than just machine learning for analysis.
As the wikipedia page on big data explains, the kinds of processing you do on big data include capture, curation, search, sharing, storage, transfer, visualization, and privacy violations.
"we are no further along with computer vision than we were with physics when Isaac Newton sat under his apple tree"
That is a somewhat offensive statement to all the people who live, eat and sleep with the standard model. While true that Newtonian physics still holds true today, I think we have progressed by a huge leap with breaking it all down enough to prove what was at his time theory. Computer vision being much younger has yet to become functional enough to begin recognition autonomously. The complexity of the cerebral cortex and the interrelation capabilities to use the occipital lobes as a cross reference of images and other light data is yet a few years to go. The trouble with todays techniques is using chips with logic to duplicate the plasticity of the brain is a HUGE hinderance. Forty years of AI development on mostly linear computational machines is a spec on the millions of years of evolution of brains.
Dangit, I clicked on the comments hoping for some good "+5, Funnies" about "Michael Jordan," and all I got was a stupid on-topic, well-researched, and educational comment on what the real Michael Jordan thinks about the challenges of "big data." And the best we could do on the name is "A man of many talents"? That does it. Slashdot is dead. (Netcraft confirms it.)
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