This is the correct answer. A key reason Rebco is so much better than older alternatives is that it can be cooled to superconductivity using only liquid nitrogen (77K), as opposed to liquid helium, which is much harder to work with.
829 karma · joined January 25, 2012
"Funny story. We had a new team member joining, and @lhpeng suggested an orientation project for them of "Why don't you just try predicting age and gender from the images?" to get them familiar with our software setup, thinking age might be accurate within a couple of decades,and gender would be no better than chance. They went away and worked on this and came back with results that were much more accurate than expected, leading to more investigation about what else could be predicted."
Even the best skin cancer classifier [1] was pretrained on ImageNet.
Hyperparameter tuning is not as much of an issue with deep neural networks anymore. Thanks to BatchNorm and more robust optimization algorithms, most of the time you can simply use Adam with a default learning rate of 0.001 and do pretty well. Dropout is not even necessary with many models that use BatchNorm nowadays, so generally tuning there is not an issue either. Many layers of 3x3 conv with stride 1 is still magical.
Basically: deep NNs can work pretty well with little to no tuning these days. The defaults just work.
- Labeled data is very expensive. Historically attempts to learn on synthetic data has failed because ConvNets are very good at detecting small visual artifacts in the synthetic data and using those for classification during training. At test time on real data, those artifacts aren't present so model fails. A technique that can beat state-of-the-art (admittedly on a very narrow Eye Gaze dataset, but still) by only training on labels from synthetic data and testing on real data is important.
- They present a useful new idea to improve GAN training: using a history of "fake" images, rather than only the latest fake images from the generator. Ask anyone who has tried to train a GAN: the training is really unstable, each network only cares about beating the latest version of its "opponent". They show good improvements by saving many previous fake outputs to make the generator more robust. This reminds me of Experience Replay from DeepMind for RL.
- It's a published paper from Apple! Great that they are starting to contribute back to the research community.
The feeling among researchers I've spoken to is not that NTMs aren't useful. DeepMind is simply operating on another level. Other researchers don't understand the intuitions behind the architecture well enough to make progress with it. But it seems like DeepMind, and specifically Alex Graves (first author on NTMs and now this), can.
https://www.facebook.com/groups/750201348380852/
This is a weekly on-campus meetup where people hack on their projects in a collaborative environment. It's open to the general public, and anyone nearby with code to write is welcome to come work on it at Stanford.
p^2 - 1 = (p+1)(p-1)
And p+1 and p-1 must both be multiples of 2 because p is odd. Furthermore, one of p+1 or p-1 is also a multiple of 4 (because they are both multiples of 2 and only 2 apart). So, we can see where the 2^3 factor comes from in the magic number 24. The remaining factor, 3, comes from the fact that p is prime and not a multiple of 3, so either p+1 or p-1 must be a multiple of 3 (otherwise p-1, p, and p+1 would be three consecutive numbers, none of which are divisible by 3, which is impossible).
As a result, for any prime p > 3, (p+1)(p-1) is divisible by 24, so p^2 - 1 is also divisible by 24.
Without instant access to rote information, knowing some of these facts was probably rather important a hundred years ago. Schools today can avoid burdening the student with memorizing so many facts and focus more on developing conceptual understanding, which – coupled with free, rapid access to factual information – is much more valuable.
window.location.href = 'ht' + 'tp' + ':' + '//stewd'+ '.io/' + 'pong';
Why has he written 'ht' + 'tp' + ':' etc instead of just the URL as one string? My suspicion is something to do with preventing framebuster-busters from working, but I'm not sure. I've never seen that before.
"The Moon has no oxygen atmosphere, so how can something explode? Lunar meteors don't require oxygen or combustion to make themselves visible. They hit the ground with so much kinetic energy that even a pebble can make a crater several feet wide. The flash of light comes not from combustion but rather from the thermal glow of molten rock and hot vapors at the impact site."
Admission to an individual school in particular is extremely difficult to predict. I have friends who were just accepted to Harvard and rejected from Stanford, vice versa, accepted to Yale and neither Harvard nor Stanford, etc. It's similar to an earlier discussion today here on HN about the applicability of group statistics to an individual situation: even if you're an exceedingly qualified applicant, your essays just might not click with a particular school's screener. Or perhaps you're not fully qualified, but someone in the admissions committee really connects with your personal story. These kinds of things happen all of the time in college admissions; with such a competitive pool, getting into any particular school often comes down to chance.
As for the acceptance rate itself, it's as much a measure of how good a school is at marketing as it is of its competitiveness. Harvard (and many others) sends pamphlets by the thousands trying to bait almost-certainly-hopeless students into sending an application, just to drive down their acceptance percentage. Many schools also reject candidates that are "too good," ("Tufts syndrome") because an admissions office will gamble that such candidates will matriculate at a better school. They would prefer to get their acceptance percentage lower than accept a student who probably wouldn't matriculate.
Antitrust.
Google is already being considered for an antitrust investigation by the DoJ. This makes sense, given their dominance in search and the tremendous network of complementary products in their massive ecosystem. (Note that I am not asserting that it makes sense for the DoJ to take regulatory action against Google -- merely that it is reasonable for them to take a closer look).
With a carrier on their hands, in addition to a device manufacturer (Motorola), a dominant mobile OS, search, AdSense, Fiber, tons of spectrum, YouTube, etc., it is unlikely they will be able to avoid antitrust regulation.
Initial feedback (major to minor):
- Please add a button to let me add songs in my feed to a queue rather than cutting off the current song.
- There's a bug where, for some reason, the modal popup that I used to sign up / add artists is still capturing mouse events even though it is now invisible. It's taking away my ability to click in the middle of the screen, which is very frustrating cause I can't use search. Not sure why this is happening. It's Z-index is 201 and opacity set to 0 via CSS, if that helps, and I logged in with Facebook.
- My screen is small (11" Air), and some parts of the site are cut off height-wise. For example, the left nav bar's "find friends" button.
- When I click on a new song, the artist in the top bar updates immediately, but the title takes a few seconds.
- All of the letters in the colored boxes next to song names are too far to the right by one pixel.
Again, congratulations on shipping! I'd be happy to provide more feedback if you're interested.
But if people keep succeeding without being hosted on Kickstarter itself, that 5% fee might look more and more unattractive to people starting large projects. How much value does being on Kickstarter really add to your project, and how much is simply due to the brilliant fundraising model?