4 ms·
I would hardly characterize this as a breakthrough: https://openreview.net/forum?id=r1RQdCg0W https://openreview.net/forum?id=r1RQdCg0W
by primitivesuave 7y ago
I would hardly characterize this as a breakthrough: https://openreview.net/forum?id=r1RQdCg0W https://openreview.net/forum?id=r1RQdCg0W
- billconan 7y agothank you for the link. I couldn’t understand it as explained by Ars. I found open reviews are better.
- Audoenus 7y agoA good rule of thumb I always use if a science article title has the word "breakthrough"in it, then it's probably not a breakthrough. If the title does nothing to describe the actual discovery made and solely consist of "Breakthrough in [Field]" then it's definitely not a breakthrough.
- jvm_ 7y agoSounds like the rule where if the headline ends in a question mark, the answer to the question is No.
- jkaptur 7y agoI wonder why no one seems to have published an article titled "Is Betteridge's Law of Headlines True?" edit: who else? https://www.johndcook.com/blog/2013/03/18/was-betteridge-right/ https://www.johndcook.com/blog/2013/03/18/was-betteridge-rig...
- taneq 7y agoOh, you mean Cunningham's law.
- rflrob 7y agoI see what you did there...
- smaddox 7y agoAny rule that reduces the posterior of a breakthrough is generally going to be an improvement. Unless your definition of "breakthrough" is extremely generous.
- 19f191ty 7y agoUnless it's in Math. If a Math breakthrough makes it to the popular media then it's most likely a very big breakthrough.
- remarkEon 7y agoWhy is that? I suppose complex maths is harder for the science journalist to understand, and doesn’t get as many clicks, so if they are reporting on it it’s because it’s substantial?
- t_mann 7y agoA good rule that could be refined by applying it only to topics that the general public cares about. A breakthrough in analytic number theory or international accounting standards is probably genuine, one in AI or battery technology probably not.
- allovernow 7y ago>"[its] training times are about 7-10 times faster, and... memory footprints are 2-4 times smaller" than those of previous large-scale deep learning techniques. Which matches the abstract. If this has general applications it's a pretty big leap to shrink model sizes and speed up training by orders of magnitude, especially at a time when many SOTA models are only feasible for well funded groups because of their size.
- primitivesuave 7y agoThis is not a strong result as noted by the reviewers, and they have not proven state-of-the-art performance among other things. Those of us who did ML in academia also look down upon using the media to bolster ones claims before a thorough peer review of research.