Take as much probability and linear algebra as you can conveniently do – as much for the intuition as for the symbol-manipulation mechanics – and don't underrate the importance of domain expertise in any problem you get interested in!
The Shipping Forecast is a very significant cultural reference in the UK. It crops up all over the place. Britain is _fundamentally_ an island and a seafaring nation, and that's something Americans miss; you're never more than seventy miles from the sea. It's as iconic as, I don't know, Thanksgiving football in the US; it's a thing everyone knows about without explanation.
Density functional theory, for example, is taught at undergraduate level as part of both chemistry and physics triposes. Probably materials science too, and it certainly used to be an option within earth sciences (as part of the mineral physics path).
The team behind Detectron have published an enormous amount of really good research, but the Detectron codebase struck me as "good research code" rather than something you'd ideally want in production.
Not at the kind of resolution you'd want to be using on, e.g., Twitch. In that setting, you could just use chromakey, though? That's '70s technology, cheap and very reliable.
It's not quite as simple as "this one has highest mAP, let's use it"; the tradeoffs are complex. In particular, as you can see in the image here, one thing DeepLab doesn't do is segment instances – so you get a mask of "people", not a mask per person. Mask R-CNN does a better job on that by design, because it predicts both bounding boxes and a mask per bounding box.
This means that codec development makes no sense for anyone who doesn't own either a large distribution platform or a large playback platform. (Much of the research has been done by middleware companies attempting to tax the two; their business goes from royalties to work-for-hire, at best, which is way less attractive for them).
This is fine – in a macroeconomic sense – but of course it sucks if you're one of the companies being disrupted.
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.
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.
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.
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.
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.