If you are looking for a computational graph toolkit that is based on clean C++ go for Dynet.
It is very complete. Similar to pytorch (which borrowed some ideas from Dynet) and backed up by top academia (not big tech, hence its lower profile). It has a python wrapper as well, as everything nowadays.
If you are into deep learning for sequence to sequence (machine translation) Marian is also C++ centered. Fastest MT around. Complete (transformer and the like), extendable. Not that reading friendly from what I have heard.
IMO the economical argument is the most robust. I see it like this:
There is a big margin between
1) the amount of information that you are legally obligated to provide to public and private sectors
2) the amount information that can be mined about you through facebook and other services (+smart data-crunching)
Safeguarding that information that falls between 2 and 1 is not a matter of moral standpoints or having something to hide. It has only to do with a properly informed rational decision about your personal economy and your well being.
That information that you are willfully leaking will weaken your position in any future negotiation including, financial credit, insurance and employment among others. After Cambridge Analytica it is more clear than ever that it will also weaken your ability to protect yourself against well armed psychological manipulation.
and that is all assuming that public and private institutions do not make mistakes, that legal boundaries and procedures are flawless and that you leave in a well executed democracy.
I have not followed the news but was this really "considered the country's own answer to the iPhone"?. By whom exactly?
One thing is to say "A Spanish company's iPhone killer is a scam" an another "Spain's iPhone killer is a scam". I hope racism/cliches did not play a role here.
You surely can find other cases in which you end up paying more than the average. In the end, what matters is information asymmetry in any negotiation. In those terms, the consumer seems to be in an increasingly weaker position with the recent technological changes, social media, etc.
As a consumer I don't think that allowing market micro-segmentation is a sensible strategy. It's more something that I don't know very well how to stop, and it worries me.
Context: I lived in Lisbon four years and know one of the founders of Unbabel. I do not know you, neither your story.
Regarding your comments:
> That's one thing I really hated about Portugal, they just don't offer any information in English
>Thanks, but from the experience I had with both my employer and my landlord in Portugal I'd rather not do business with any Portuguese people ever again. Sorry.
>it does seem like fucking people over is business as usual in Portugal
>Have you had any experience with the Portuguese state or legal system? I'd probably still be standing in a queue somewhere.
Blaming the whole country for a 90 day experience does not seem very proportional to me.
Again, I do not know your story and can not speak for the veracity of your facts. What I do know is Lisbon (and I have lived many years in Spain and Germany to compare with). From that I know that you are just being, at best, exaggerated and I wonder if you have been exaggerating other stuff too.
Yet, as a portuguese, it's hard to dismiss his claims. The queues and slow state services, the "fucking people over" (mainly in employer-employee and vendor-customer relationships), the lack of information in english (unless you consider the restaurant menus as sufficient)... well, you run into this every-fuckin-day.
He may be escalating his issues, but - again, as a portuguese - I don't think he got the wrong idea about the sad state of affairs here.
no OCR. It's a feature i considered but then wasn't sure how useful it'd be.
Most of the time i just need to recall my receipts and hand them to my accountant.
And there are apps that do OCR better. Didn't want to get stuck into the OCR sucks problem.
It would be interesting to see if this is really so. The post just cites circumstantial evidence and does not reason why this would happen.
I personally hope the days of amateur, low frequency, niche blogging are not over. It seems to me as one of the fundamental goods that internet has brought and, as the post indicates, a solid reason to have RSS readers.
they use DNNs not DBNs (DBNs only used for pre-training, sometimes). Also if you read Microsoft's paper Table2, 7 hidden layer networks, which clearly qualifies as deep, work just fine with Back-propagation. Just a bigfat-MLP, no preprocessing! but 17.4 Word Error Rate (WER) vs 17.0 WER for DBN pre-training.
>they're not much like the old ANNs. DBNs are generative probabilistic graphical models using Bayesian inference.
MLPs (DNNs) can also be interpreted probabilistically. Just a directed model where inference is attained by marginalization of the hidden binary nodes in a layer-wise manner and by using a naive mean field approximation. All that to say the classic "forward-pass" ;).
Also could you indicate me a source confirming that Siri (Nuance) also switched to DNNs?. I am interested in that.
>Conceptually, going deeper (LOL) allows the networks to learn higher level concepts.
That is the really interesting part!. Now, I have not seen a proof for that. Wondering at individual neurons modeling individual features of e.g. a face or so is also a trend of the 90s and does not count as proof. I said this because it is what I usually hear.
Until now the justifications I saw for multiple layers of perceptrons being suitable for modeling arbitrary high level abstractions are reduced to
1) MLPs are universal approximators. This in my opinion is a superficial argument. GMMs also allow modeling "any" distribution and Taylor series any linear function, but in reality there are physical limitations to this argument. Maybe is true if you had a billion layer net, but will you get there?. If you had that computing power maybe a more realistic modeling of the brain might work better
2) They resemble how brain architecture works and similar arguments. Which I am fairly sure is not true. There are more human-brain based approaches to AI like e.g. cortical learning algorithms and those just seem to model that stuff to a certain extent.
It is very complete. Similar to pytorch (which borrowed some ideas from Dynet) and backed up by top academia (not big tech, hence its lower profile). It has a python wrapper as well, as everything nowadays.
If you are into deep learning for sequence to sequence (machine translation) Marian is also C++ centered. Fastest MT around. Complete (transformer and the like), extendable. Not that reading friendly from what I have heard.
Disclaimer: Python type of guy here.