Bitshares did low cost transactions at high volume years ago, so I'm never quite sure why Nano gets so much attention because those features aren't novel.
Furthermore, free transactions with minimal POW don't create proper incentives and will not scale because there is an extremely low cost to spam the network. This means you can essentially use full historical nodes as a data storage for anything you want.
Adding to this, representative nodes (DPOS) do not get any rewards for being online and behaving correctly. Which is a recipe for tragedy of the commons. Worse yet, a voter can issue two conflicting votes, and the system has no mechanism let alone penalty for handling this. The defense against these attacks seems to be, reps have stake, therefor they wont take actions detrimental to coin value..
The marketing is strictly speaking false. A transaction is not instant, as you must wait for sufficient time to ensure that a conflicting transaction has not been published (and hope that you are not network partitioned). Otherwise, you might as well settle for "instant" BTC 0-conf transactions. Free, is debatable, considering the difficulty of POW that would be required to effectively deter spam.
I am a web dev, JS being my first lang of choice :-), and i have been trying to get into machine learning/deep learning/AI, but I am having a information overload.
I have 0 knowledge about this field, so my question is should i just start with machine learning, instead of jumping right into deep learning ? Or is it ok to jump right into deep learning and is it possible to do all the stuff done with machine learning with deep learning ?
Just like when a person who shows an interest on learning to code I refer them to Python instead of C++, what do you recommend ?
Just jump in with this course. Your background in web dev will be really helpful, but there will be plenty of new concepts to learn - don't try to understand everything perfectly the first time through, but just try to complete each week's assignments as best as you can. You'll need to learn python and numpy along the way, but there's plenty of free online resources you can refer to when you see something you don't understand. And use http://forums.fast.ai of course.
You can then go back through them a 2nd time and do a deeper dive. By that time, our Intro to Machine Learning course will be out too :)
