471–480 of 518 posts
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It would be great if people feared climate change the same way they fear AI takeover.
Climate change is not an existential threat - primitive humans survived for 200+ kyrs when temps were 10°C cooler and thrived during warmer temps.
Sure, the human race is unlikely to die out unless we get to mass-exinction levels of climate change, but our civilisation is a lot more fragile.
An AI "winter" is a long period in which [edit: funding is cut because...] researchers are in disbelief about having a path to real intelligence. I think that is not the case at this time, because we have (or approaching) adequate tools to rationally dismiss that disbelief. The current AI "spring" has brought back the belief that connectionism may by the ultimate tool to explain the human brain. I mean you can't deny…
These days anyone with a few dollars to spend on compute time and some free software can do machine learning. I can’t see that going away.
Has anyone done something genuinely useful with ml/ai/whatever outside of advertising or stock trading? I am genuinely curious if it has really been applied to real commercial applications.
Not as sexy as the headlines, and less likely to involve DNN, but still profitable.
Truly, I agree. I've long been interested in learning about AI and deep learning, but to this day haven't done much that truly excites me within the field. It feels more or less impossible to make anything significant without Google-scale databases and Google-scale computers. AI really does make it easier for the few to jump far ahead, leaving everyone behind. I also agree that a lot the news around AI is just hype.…
I'm kinda curious now where those giant datasets will come from now that there's a big push for privacy with things like GDPR preventing some random researcher from just buying data off whatever data mining corp is most relevant to their AI's purpose
You won’t hear about these projects outside industry specific publications, if at all.
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Alright. What is the cost of a false positive in that case? The problem AI runs into is that with too much faith in the machine, people STOP thinking and believe the machine. Where you might get a .44 detection rate on radiology data alone, that radiologist with a .39 or a doctor can consult alternate streams of information. The AI may still be helpful in reinforcing a decision to continue scrutinizing a set of probl…
> The problem AI runs into is that with too much faith in the machine, people STOP thinking and believe the machine. See https://youtu.be/R_rF4kcqLkI?t=2m51s In medicine, I want everyone to apply appropriate skepticism to important results, and I don't want to enable lazy radiologists to zone out and press 'Y' all day. I want all the doctors to be maximally mentally engaged. Skepticism of an incorrect radiologist rep…
Unless i'm misunderstanding ML/AI, it'd be an important question for a radiologist, and you'd still need their trained eyes to make that final recommendation.
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Bayesian can be seen as a subset of deep learning or hell a superset. AI is a superset and Machine learning is a subset of AI and most funding is in deep learning. Once Deep Learning hit the limit I believe there will be an AI winter. Maybe there will be hype around statistic (cross fingers) which will lead to Bayesian and such.
>Bayesian can be seen as a subset of deep learning or hell a superset. eh-hem DIE, HERETIC! eh-hem Ok, with that out of my system, no, Bayesian methods are definitely not a subset of deep learning, in any way. Hierarchical Bayes could be labeled "deep Bayesian methods" if we're marketing jerks, but Bayesian methods mostly do not involve neural networks with >3 hidden layers. It's just a different paradigm of statisti…
He sees the latent layer in the hierarchical model as the hidden layer and the Bayesian just have a strict restrictions/assumptions to the network where as the deep learning is more dumb and less assuming. A few of my professor thinks that PGM, probability graphical model is a super set of deep learning/neural network.
This is where my thinking come from.
IIRC, a paper have shown that gradient descent seems to exhibit MCMCs (blog with paper link inside that led to this conclusion of mine: http://www.inference.vc/everything-that-works-works-because-...).
But I am not an expert in Neural Network nor know the topic well enough to say such a thing. Other than was deferring to opinions of some one that's better than myself. So I'll keep this in mind and hopefully one day have the time to do more research into this topic.
Thank you.
This is a deep, significant post (pardon pun etc). The author is clearly informed and takes a strong, historical view of the situation. Looking at what the really smart people who brought us this innovation have said and done lately is a good start imo (just one datum of course, but there are others in this interesting survey). Deepmind hasn't shown anything breathtaking since their Alpha Go zero. Another thing to co…
>Deepmind hasn't shown anything breathtaking since their Alpha Go zero They went on to make AlphaZero, a generalised version that could learn chess, shogi or any similar game. The chess version beat a leading conventional chess program 28 wins, 0 losses, and 72 draws. That seemed impressive to me. Also they used loads of compute during the training but not so much during play.(5000 TPUs, 4TPUs). Also it got better th…
Few would care. Your examiner doesn't give you extra marks on a given problem for finishing your homework quickly.
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AI winters are a result of a massive disparity between the expectations of the general public and the reality of where the technology currently sits. Just like an asset bubble, the value of the industry as a whole pops as people collectively realize that AI, while not being worthless, is worth significantly less than they thought. Understand that in pop-sci circles over the past several years the general public is be…
> AI winters are a result of a massive disparity between the expectations of the general public and the reality of where the technology currently sits. I think they also happen when the best ideas in the field run into the brick wall of insufficiently developed computer technology. I remember writing code for a perceptron in the '90s on an 8 bit system, 64 k RAM - it's laughable. But right now compute power and data…
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Climate change is not an existential threat - primitive humans survived for 200+ kyrs when temps were 10°C cooler and thrived during warmer temps.
They weren’t reliant on agriculture to sustain their civilisation. Sure, the human race is unlikely to die out unless we get to mass-exinction levels of climate change, but our civilisation is a lot more fragile.