You can add location information to your Tweets, such as your city or precise location, from the web and via third-party applications. You always have the option to delete your Tweet location history. Learn more
Deep learning is immensely useful, but it does not bring meaningfully closer to understanding intelligence (as for "AGI", that's a sci-fi talking point, as even human intelligence is specialized). Intelligence is 100% about efficient generalization. DL is orthogonal to that.
Schematically, intelligence is skill divided by experience (I = S/E). Deep learning enables arbitrarily high skill levels, but requires insanely high amounts of "experience" (data) to achieve these levels, resulting in an extremely low intelligence factor.
Again, a DL model requires a dense sampling of what it's doing. An intelligent agent (like a human) can do extreme generalization from little data. At this time, no one has any clue how that works. However, it may not necessarily be very complicated. Who knows...
Insane amount of "experience" relative to what though ? Humans have genetically encoded skill from thousands of years worth of experience.
Hit the nail on the head there pal!
I think the biggest obstacle in the journey towards AGI is the lack of the consensus over the very definition of the “Intelligence”.
I would say this is learning, not intelligence. If you do continuous learning, experience tends to infinity and learning, not intelligence, tends to zero.
Learning is directly proportional to intelligence,if you learnt something you can use it intelligently to solve problem
That's a pretty creative definition of intelligence. Source?
Rt, as humans our skill is high, wth less exp..ex the mnist handwritten digits, we as humans can identify the digits with only abt few dozens of such images, at max..Cant rem how many times we saw these digits..few hund at max, whereas the Deep Learning needs 60k images
Really like I = S/E. I think the ultimate feat of “generalization” would be general relativity, or thermodynamics... as few postulates used to explain or predict as broad as possible the amount of observations.
Twitter may be over capacity or experiencing a momentary hiccup. Try again or visit Twitter Status for more information.
