So what are some actual quotes or references of deep learning researchers (*not* media or popular science reporters) overhyping, overclaiming, etc? My hunch is that the anti-hype pushback is ironically hyped.
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Thanks. I agree the former is overshooting, though the context in which I've heard it was more as a rule of thumb regarding the types of things we should try to apply ML/DL to? In that regard it isn't that far fetched. And Geoff is notoriously tongue-in-cheek :)
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and no re.
@AndrewYNg. it’s a quote fromhttps://hbr.org/2016/11/what-artificial-intelligence-can-and-cant-do-right-now … - 2 more replies
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I went to a very informative tumour imaging workshop today at
@BCCancer. After seeing a few imaging case studies, my impression is that current AI is pretty far (decades) from replacing radiologists. Assisting - yes, perhaps. -
Very interesting, thanks! Do you think the current limitations are in the techniques, or access to data or other resources needed to train good models?
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Here is the video of
@geoffreyhinton on radiologistshttps://www.youtube.com/watch?v=2HMPRXstSvQ&feature=youtu.be … -
Thanks! What's your interpretation of the meaning behind the words, given this context?
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These sound like wacky claims. Do you have any links? a radiologist friend of mine did say as a registrar (i.e between age 35 and 45) you basically stand in a dark room all day sorting scans to send to a consultant. Maybe
@geoffreyhinton was referring to that? -
watch
@judywawira’s link and learn, instead of reflexively defending Hinton. or wind up a rube, like Rubio, above
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@geoffreyhinton knows his and everyone else’s predictions should be taken with a healthy dose of uncertainty beyond the short term. I’ve heard him say multiple times that the future is in a dense fog a few years out. -
list to the prediction
@judywawira; it’s about 5-10 years out, presented with very little humility or recognition of uncertainty. people rush to defend him, much like people rush to defend POTUS, without pausing to look at actual record. - 1 more reply
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