One of four (MXNet and CNTK alongside TF and Theano), and the Amazon deep learning API forked Keras to default to MXNet support before it was really ready - which irked the Keras authors quite a bit.
This observation is the single most important thing you need to know if you work in consumer mobile.
To first order, iPhone owners spend money. Android owners don't. This is because your average iPhone user cares more about what phone they're using and simply uses it more.
This is a first-order approximation. The small percentage of people who actively choose Android do spend and do use their phones a lot, and by goodness are they vocal, but the more useful way of thinking about the market is not two-segment, it's three-segment:
* Vast majority: don't care about their phone OS, won't pay for anything
* Significant minority: want iPhones, will most probably spend money
* Significant but even smaller minority: actively want Android, will buy premium Android phones (e.g. Nexus, high-end Samsung), will either spend money or, with roughly equal likelihood, jailbreak and pirate everything in sight.
From this perspective iOS remains the most compelling mobile OS to target. Additionally, iOS users – on average - use apps more and for longer, though again that effect is small when you control for the kind of Android devices people go out of their way to choose.
Absolutely, yes. Your moral argument there is pretty undeniable; I'm speaking purely to propensity-to-spend and that's a pretty narrow lens.
In fact, I'd say "target the web" if you're going for maximum accessibility and you're not driven by commercial factors, though that doesn't work for every app and the usability/discoverability issues can be real. Favoring any commercial platform as a government is a very uncomfortable place to be.
If the first segment won't pay for anything, and 50% of Google's mobile revenue comes from iOS products, that implies that the second and third segments must be of roughly equal size?
It's even more dramatic than that. Google make money on advertising, not direct sales, so what you're saying is "the (usage * advertiser desirability) from the entirety of group 2 is roughly equal to groups 1 and 3 combined".
Given group 1 is many times bigger than group 2, that's a very strong statement, but it's borne out in all the data I've ever seen, both public and private.
>To first order, iPhone owners spend money. Android owners don't. This is because your average iPhone user cares more about what phone they're using and simply uses it more.
More like, is willing to spend $700 on a phone.
The problem with android is that even the "high end" android phones (in the US anyway) are still just wrappers around the snapdragon 8xx SOCs. They're all exactly the same and feel almost as closed as the iphone.
When people compare phone prices, they don't count extended warranties in the listed price.
iPhones have a warranty at list price; AppleCare extends it and increases the scope of service.
I do agree that anyone who plans on purchasing an extended warranty for any product research it ahead of time so the total purchase price fits into their budget, though, and the same goes for sales taxes.
More "chooses to spend what money they have on a phone" plus "has the money to spend", which is almost but not quite what you're saying. I know some very rich people with whatever Android device the network gave them. They just don't care that much.
Exactly. There's good reason to think that most of human reasoning and the way we attain "knowledge" is not strict deductive logic from firm premises. Rather it's a mixture of Bayesian inference, abductive reasoning "to the best explanation", etc.
At a previous company, I worked with someone in a recent highly-public sexism scandal (if I said who or where, I would no longer be a genericpseudo).
I knew that the person was extremely brash and was told that they indulged in "locker-room talk", though I didn't personally observe any harassing behavior. I didn't speak up about what I heard. I wish I had. I wonder, and worry, if anything as bad as what happened at their next company happened at the company I worked at. I'm really uncomfortable with the odds that it did.
The problem isn't the mods' local actions (though the mods are not nearly as assertive as I would like in this area); it's the Hacker News community's toleration of bigots and therefore the macro action of failing to remove them.
I didn't down vote these stories, but to be blunt they aren't value adding content. I come to hacker news for interesting discussions and to learn. Reading yet another story about sexism or inequality in tech doesn't add any value to my life. The stories are predictable; the comments are predictable; and there are very few opportunities for meaningful discussion or learning. I therefore typically ignore them and I can understand why others down vote them.
Bitching about things online isn't action. Changing behavior offline is action, and I doubt these stories generate any meaningful behavioral changes among the groups that need them, so what's the point?
Close but not quite. The difference between (soft) SVM and a kernel linear classifier is choice of loss function; SVM minimizes hinge loss, linear regression minimizes squared loss.
(Choice of different loss functions will also give you Elastic Net, LASSO, logistic regression. From an engineering point of view I tend to think of the entire class as being different flavors of "stochastic gradient descent", in the spirit of Vowpal Wabbit etc.)
Jobs has form for this kind of thing, too (breaking something to force developer behavior before reintroducing it when habits have changed).
Best example: the original Mac had no cursor keys (to force developers to build mouse-based UIs). Steven Levy writes about it at length in "Insanely Great".
