demonshalo

ok so what do they have exactly that is worth 1B? I mean sure, sounds cool but what is so unique about them?

That's my #3 question in a nutshell. And this seems to be a rather good strategy imo. However, the way everyone is talking about ML makes it seem as a diamond bullet to solve all that is holy and sacred!

I didn't say that I assume mine to be the peak. My intention was to point out that any efficiency that could be reached beyond what is statistically possible (i.e. if you only rely on statistical metrics and parsing), could be considered unreasonably efficient. At least, there is an argument for that to be made.

My method should in no way, shape or form be considered as a "peak".

> I prefer statistical metrics because they seem more simple to derive.

That's exactly how I view it as well. My goal for this project is to reach a 90% "perfect" score. And in that case, ML seems to not even be needed. Perhaps the gap between 90 and 95-100% is where ML can help add value. But that in itself is what #3 is about in my original post.

Thank you for confirming my suspicions regarding the threshold though!

here is what I don't understand about deep NLP (please keep in mind that I just began exploring this field):

I am currently working on an algorithm that uses elementary text cues in combination with large data-table lookups to determine things like relevant keywords of news articles scraped from various sites. I have given my results to hundreds of people independently to provide me with some feedback regarding the quality. Here is the current breakdown:

80% of the cases I get perfect score.

10% of the cases I get acceptable score.

10% of the cases needs improvement.

My questions here are:

1. if deep nlp can only provide us with the same level of efficiency/accuracy, then why the hell would we use it?

2. if deep nlp can provide us with more efficiency than what is stated above then wouldn't it be safe to assume that is UNREASONABLY efficient?

3. why are most people using deep nlp or ML in general right off the bat. Theoretically, it would be far more interesting to construct a model where the result of a statistical/linguistically parsing is fed to some sot of ML algo in order to tackle that 10% of bad cases.

So she did this for free? :D please tell me this is a paid internship!

ELI5?

no ty!

The problem is datasets. How can you distinguish a good result from a bad result? In some cases, depending on the user, it could be both at the same time.

Most advancements in ML is not accomplished by some new super algorithm. Rather, advancements are reached when new datasets are presented!

I never thought about this particular use-case. The subtitle for TED talks should be an ocean of info for you to extract keywords from :D Pretty neat site you got there. I will be using it. Thanks!

I started even simpler than that. I started by just eliminating stopwords and count the frequency in each word in the document itself. I did not use a set of documents as the goal was for the algorithm to be used on the spot for a single block of text.

A few months later and after many iterations + a whole lot of testing, the algorithm now can extract super relevant keywords 90%+ of the time!

I wish I knew about the WikiCorpusExtractor. Thanks for the link!

u welcome!

How? just get started working on a fun problem. A good place to start is keyword extraction. You don't need a PhD or expensive tools. All you need is some free time and willingness to read some cool stuff.

Copy a few articles into text files and get working on implementing some of these methods until you have enough of an understanding to construct your own methods for the fun of it.

Here's some good reading material:

https://www.facebook.com/notes/facebook-engineering/under-th...

https://www.researchgate.net/profile/Stuart_Rose/publication...

http://cdn.intechopen.com/pdfs/5338.pdf

https://arxiv.org/pdf/1603.03827v1.pdf

https://www.quora.com/Sentiment-Analysis-What-are-the-good-w...

http://hrcak.srce.hr/file/207669

http://nlp.stanford.edu/fsnlp/promo/colloc.pdf

https://arxiv.org/ftp/cs/papers/0410/0410062.pdf

http://delivery.acm.org/10.1145/1120000/1119383/p216-hulth.p...

Edit: Don't get deterred by the math formulas in these papers. They look far more complicated than they actually are.

yes indeed!

This makes 0 sense to my heavily biased brain. As a Swede that is keeping a close eye on the domestic market, I can't find that many "innovations" taking place in most commercial sectors. R&D means quack-all if you cant translate that research into good and services that the citizens of said country can take advantage of.

the Automaton interpretation sounds like something I would enjoy reading. But considering that I do not have the time this week nor enough knowledge in the subject, could you perhaps provide me with a quick summary as to what it is about?

much powerful maybe, but not much faster.

> Whether you like it or not, most discoveries will be made by those who enjoy discovery, not by those who view it as a means to reach utopia.

I like this. A lot!

this is essentially the argument for functional tests over unit tests and while I generally agree, I think a mixture of the two is important.

Unit tests should be used for extremely small and isolated mission critical objects while functional tests should generally cover the entirety of the I/O chain. That's how I do it at least and it works extremely well for a fraction of the cost!

no! simply no!

DigitalOceans main selling point is not only the price and speed at which you setup a node. The main selling point is their freaking awesome support and their tutorial/help pages that help a lot of people with troubles that might have.

AWS, with its amazing stack size, cannot compare in those 2 departments IMO!

What I mean is, Europe generally does not even come close to that level of pay/compensation. So I assumed that these are US based startups. I could be wrong though.

sigh... Europe does not stand a fucking chance!

How about you go fuck yourself, your pixel and your iphone? jesus. What is up with all this gizmo competitions for gadgets that are BARELY an incremental improvement on something that has existed for a decade now?! This fanboy bullcrap is really rendering an entire industry into nothing but hype-driven clusterfuck that benefits only those who sell these devices while we, the consumers, get the same re-packaged trash for double the price each year...

Come back to me when you have a phone that can do something new and useful!

I think the problem resides in the west's insistence on spreading the ideas of equality. Watching a youtube video from buzzfeed is (in the minds of many) a legitimate way to learn about things like group conflict or any other social phenomenon. Mass communication has indirectly given rise to mass access to bad information. However, that alone would not be a problem. What makes it a problem is once you are told that your opinion is equal to all others in society, you begin to believe that your buzzfeed backed opinion is on par with a nobel prize winning POLS professor.

It's simple. Europe has no money. The middle class has no savings and the investment sector is far too regulated, confined and incapable of looking at a multi-year timescale.

Don't have any figures but I lived in the US and I can confirm that statement on a personal level.

> The first exit by any nation is likely to receive poorer terms than they might expect in any subsequent trade negotions, "pour encourager les autres".

Absolutely. But someone has to be the first. Could/should it have been someone else? absolutely, but that's just how things unfolded.

> In lacking any plan, team or responsibility for the outcome we are even less likely to get good deals.

Couldn't agree more. I just think that the anti-EU themselves did not believe it would happen so fast.

Yea so is Sweden, Norway and a ton of other places. FOR NOW... That is the whole point.

https://en.wikipedia.org/wiki/Critical_mass_(disambiguation)

I did not use the word immigrants. Not even once. I was talking about homogeneity. A society without immigrants can turn heterogeneous as well. This has nothing to do with immigration, it has to do with cultures and ideas.

> The most multi-cultural areas of Britain voted to remain i.e. cities and university towns... The areas that voted leave seem to demonstrate xenophobia in its fundamental form: fear of the other.

This is why I can't take the leftist arguments seriously. You refute phenomenon that have been taking place for thousands of years in order to glorify an ideology that you believe in without a single shred of evidence...

If you think that the fact that certain cities voted X compared to others who voted Y describes the sudden rise of nationalism across all of Europe AT THE SAME TIME, then you sir are in for a ride.