What I do, though, is writing them down, and perhaps 1 out of 100 ends up being successfully implemented by someone else (unrelated to me). Again, nothing special here.
Is there any way to leverage these ideas, provided you don’t have time to execute them? Is there any feasible way to externalize their development? Assuming you are not Google and can not afford funding a Google X-like lab.
Some possibilities I can think of at the moment is either becoming a professor and taking lots of interns, or funding a small startup with a bunch of developers.
Does anyone know if it's even technically possible to restore Android Whatsapp backups on an iPhone, and if so can recommend me some options (private message if you want)?
Not a very HN-like question, but it's the final resort because here I'm sure that people are legit and tech-savvy.
There have been some failed attempts, most famously the Ubuntu phone, and a few Kickstarter projects, as well as Microsoft trying to do an OS to fit them all. But none of them have been much serious.
With the current technology, an Android phone could be built such that when connected through HDMI it launched a Linux desktop such as Debian (like Maru OS, but it is a hobbyist project). Apple could do the same with iOS/Mac.
Furthermore, if foldable phones were industry standard (not there yet, I know), the phone could double up as a tablet/laptop.
Probably there is no demand for such a device, and we can argue that it's better to have a device specifically designed for one purpose (communicating, working or gaming). However, I believe that the failed/current attempts were not serious enough, and if a big OEM wanted, an excellent all-in-one device could be shipped. I would be the first customer, waiting the whole night like some Apple customers do. Also, I'm kinda tired of taking care of 3-4 devices with their own update cycles, cables, and so on.
a) Deep learning applications (adapting to different domains, solving a particular task)
or
b) Deep learning architectures (ie. 'macro').
My question is: are there people researching unit-level fundamentals? Eg. modifying the current "standard" neuron, like using alternative activation functions, or doing something more complex that just adding inputs (multiplied by their weights) and applying an activation function? (ie. 'micro' architecture)
At least I haven't been able to find new research that involves modifying the classic unit of deep learning models, probably because I'm using the wrong keywords.
I've been searching a lot but for me it's really difficult to judge whether a particular masters degree is really worth it or just "vapor". Also many programmes are very specific to one particular field (say, robotics) while many others include just too many generic Computer Science courses which I've already had.
I'm based in the EU (Spain).
Any suggestions would be highly appreciated. Thanks.
Yesterday I told a friend of mine (who is a self-taught frontend developer and user of Typescript) that sooner or later something similar will happen with the side-effects. I'm not saying that languages like Elm or Purescript will become mainstream, but I think that static side-effect checkers will gradually become widely used. Maybe starting with adding the "pure" annotation to the Typescript functions [1] (Solidity already has this feature), although I believe something more complex is needed.
What do you think? How would you implement this behaviour in a language targeted at JavaScript developers (transpiled to JavaScript)? I use Purescript myself but I don't think purely functional languages will ever be mainstream. Instead, traditional languages will be getting more and more functional-like features.
[1] Suggestion: document and enforce side effects of functions https://github.com/Microsoft/TypeScript/issues/19520