proofofstake's comments

From the article:

> The incentive for holding OMGs, is to take part in the network validation process. We also see a long term value/appreciation in the OMG price as more and more transactions take place on the network.

So you can stake your tokens for a cut of the transaction fees (much like miners do).

HackerNews used to be all about cryptocurrencies. I think the original Satoshi paper was posted here soon after it was released. But about your cynicism-remark, this never changed. People that jumped on the opportunity were too busy to post on HN. People that did not, well... this is the first ever comment on HN about Bitcoin, 3037 days ago:

Well this is an exceptionally cute idea, but there is absolutely no way that anyone is going to have any faith in this currency. [1]

> Why can't we just have an intelligent conversation about this new technology?

It is quite the same with HN and SEO: Because there are a few scumbags in the SEO space that are very obvious for HN readers, every thread about optimizing websites for search engines has a negative sentiment.

This technology has a lot of obvious scumbags too. Now the companies in the article did not get to a billion market cap by being scumware. Speculators just assume the value of the coin will rise (again) with increased adoption of the technology.

Then I think a lot of early HN posters moved elsewhere or just stick to read-only mode. Also, maybe, "me too hates this!" is more popular on HN than "I like this".

I agree it is a shame that there isn't a single comment about the technology of the two ICO unicorns in the article. About successfully skipping VC and crowdfunding your next startup by issuing a token.

Instead we get a thread that is pushed off the front page, due to more comments than upvotes, most of the comments talking about unrelated scams or conflating value of distributed tokens with business evaluation.

[1] https://news.ycombinator.com/item?id=599852

> No, don't worry, this isn't a bubble.

Crypto is definitely a bubble. Perhaps one of the biggest bubbles to burst when this happens four to five years from now.

> I need to start thinking of a few product roadmaps

I know you are being facetious, but it really is not as simple as putting out a roadmap. Think about it: If you could pull this off, but are not doing it, you'll have us believe you are willingly turning down millions. If you can't pull it of, your comment becomes a cheap meaningless jab at things bigger than you. Both options are quite unbefitting of HackerNews.

> You also have to write a whitepaper.

http://plasma.io/ Pay attention to mentions of "micropayments".

> What maths must be understood to enable pursuit of either of the above fields?

None.

> Are there any seminal texts/courses/content which should be consumed before starting?

No.

You don't need to know binary to start being a programmer/developer either. Just start already. As long as you are not in charge of a medical diagnosis or financial model, you don't get any drawback in experimenting (and failing miserably).

Assuming applied ML, the most difficult part will be the human-political business element of it: People not understanding your model or using its output correctly, bias, feedback loops, acquiring enough resources, etc. The more you can explain to them, without resorting to heavy maths, the better communicator you are.

That said, it can't hurt to do Ng's Coursera course (a lot of top performers started out with this course). Learning from Data by Caltech's Abu-Mostafa goes very wide on machine learning. "Programming Collective Intelligence" is a, somewhat dated, good book.

As for seminal texts, the field is too wide for this. A better bet is: Find a professor in the field you are interested in. Say "Deep Learning", you could have a look at LeCun, Hinton, Schmidhuber, Bengio, ... Now look at their PhD-students, their papers, their courses, their conference talks, their software, their current research. Basically become a student under the most authoritative professor in the subfield you can find and resonate with, without ever paying any university tuition or them knowing you exist. This is very possible these days.

But by all means: Just start out. Machine learning is fun. Learning about dry 100 year old maths not so much. Make mistakes. Learn to detect and avoid overfit. Find out if you are passionate and curious about parts of the field, then the theory will come eventually. A lot of the time these questions seem to demand answers like: "You need a PhD-level understanding of mathematics" Just so your brain can go: "I am not good enough for this, so let's look at something easier". Don't use this as an excuse. Start making intelligent stuff. There are 16-year-olds on Kaggle routinely beating maths PhD's.

Also remember that, despite the current trend of calling everything "AI", that AI is a very wide field, of which mathematics is only a small part. There is philosophy, linguistics, cognitive science, physics, neuroscience, psychology, computer science, robotics, logic, ... all these parts vary wildly in their prerequisite maths knowledge.

Just wondering: If you got so rich from crypto currency that you could retire, would you retire? Start your own company? Just do fun stuff? Or keep working?

I myself work, to occupy myself with interesting problems, so I would keep doing this, regardless of my wealth.

For a fair comparison we should look at "energy" in an abstract manner. Time and money is energy too. Every time gold exchanges hands, it also costs energy.

> compare the cost of Bitcoin to U.S. dollars or gold

All-in sustaining costs for mining an ounce of gold (worth $1,293.70) is between $1,100 and $1,200.

GP: Maybe you are just crazy.

M2: Indeed! But do not reject these teaching as false because I am crazy. The reason that I am crazy is because they are true.

GP: Is Eris true?

M2: Everything is true.

GP: Even false things?

M2: Even false things are true.

GP: How can that be?

M2: I don't know man, I didn't do it.

And if I may be so bold to add a fourth reason, gossip has always been a form of social currency. It feels good to be privy to secrets and have information that other people do not have. Gossip on the internet is a supercharged version of this, the best gossip going viral. Couple this with an increased access to information and gossip by the middle and lower class: Old governments were much more able to keep their secrets from the middle and lower class. The media was much more controlled by those in power. Journalists in my country still refuse to write about certain secrets and conspiracies concerning politicians and royalty. But plenty of bloggers do. This reinforces the beliefs in conspiracies, especially if it later turns out to be validated by the old media.

In an interview RAW was asked what could be the cause of the popularity of the Illuminati conspiracy. His answer was three-fold:

There is too much information nowadays. Life's truths used to be simple: USA good, Russia bad. You adopted the political views of your parents. Men worked and women stayed at home. Your favorite news station was always right. Too much information and fast change leads to a cognitive overload. One protection mechanism to not lose touch with reality and filter the large amounts of information, is to create very simple truths. One of these truths is that there are rich powerful people behind the curtain controlling everything.

Second, with the rise of the internet and search engines, it means that if you have an idea of a conspiracy, no matter how far out, there is likely a website already documenting it. Everyone can feel like an expert after a few hours of internet research. The barriers to publish your views on a conspiracy have vanished: always resulting in a few websites out there that confirm your hunches. For instance, if you perform research on vaccines, and start out as biased against them, you will likely stumble on a lot of a websites that tell you exactly what you want to hear: vaccines are bad and used by the governments to control their people.

Finally, there simply are a lot of rich and powerful people conspiring behind the scenes to move society in a certain direction. Just one example was the P2 lodge [1] in Italy, also called a "state within a state". It is unlikely that the queens of this giant collection of ant hills we call humanity have stopped conspiring. It just happens under a different name than the Illuminati. Symbolically, the Illuminati stood for rebellion against the church and royalty, in favor of monetary power and reason. That's a role for capitalists and scientists now.

[1] https://en.wikipedia.org/wiki/Propaganda_Due

Old vs. new money. It's a lot easier to get money from 15.000 people who got so rich with BTC and ETH, they have money to spare, than to find and convince 15 Venture Capitalists to put up 1.4 million.

> Why are people throwing money at these?

Futures for Tezos are already trading at 6x the amount people invested during ICO.

> It makes no sense.

In the short term it makes a lot of sense (600% ROI). In the long term: An Ethereum based on OCaml has an interesting potential.

> You have no guarantee that they won't just run off with the money

If the developers are not anonymous, while no guarantee, it makes it less likely. When you cross the road you also have no guarantee that the cars won't run you over. Some amount of trust is needed, whether for money or your entire life. Benefit of crypto is that you don't necessarily need to rely on trust. I doubt Tezos has contractual access to all the money they received, or are allowed to dump their shares as soon as it starts trading for real.

Maybe you are right. Couldn't quite gather it from your post.

Do you think neural encryption is closer to encryption? GAN-style: One network encrypts while preserving structure, another network tries to reverse engineer to the original features.

Edit: No specific sources for what Numerai is using, but in general: https://arxiv.org/abs/1610.06918 "Learning to Protect Communications with Adversarial Neural Cryptography".

Edit2: Yes, in general. I would say "yes, this is a valid form of encryption". But I do agree that their marketing was perhaps a bit too optimistic. I have no problem calling it "obfuscation" either (I just think their method of "obfuscation" is way more advanced than removing headers and normalizing within 0-1).

They switched from structure-preserving encryption to neural encryption (using a neural net's layer activations).

> Just a few months ago this package was released by Louis Aslett at Oxford http://www.louisaslett.com/HomomorphicEncryption/. Louis helped me use his package to do Fan and Vercauteren homomorphic encryption on my dataset. Because the ciphertexts are polynomials it's not too easy for an average data scientist to use the data. That's why I came up with more chill ways of encrypting Numerai's data that the article mentions like order-preserving encryption. There's a security vs easy of use trade off, for sure. But homomorphic encryption is a real thing.

https://www.reddit.com/r/MachineLearning/comments/3zvuge/enc...

Louis Aslett authored https://arxiv.org/abs/1508.06574

> This work leaves much room for improvement, however. For example, the throughput and latency can be significantly improved by using GPUs and FPGAs to accelerate the computation.

https://www.microsoft.com/en-us/research/wp-content/uploads/...

> We demonstrate CryptoNets on the MNIST optical character recognition tasks. CryptoNets achieve 99% accuracy and can make more than 51000 predictions per hour on a single PC. Therefore, they allow high throughput, accurate, and private predictions.

Yes, but not to the same degree. Numerai uses structure-preserving encryption / neural encryption. This allows people to use any existing machine learning algorithm on the data. For fully homomorphic encryption you would need specialized algorithms. These are way more difficult to design. They also run slower.

https://www.youtube.com/watch?v=xsaXMUelOEA "CryptDB: Processing Queries on an Encrypted Database - Microsoft Research"

Do you mean by "the real world" that Bitcoin price prediction does not work in the real world? Or that stock market prediction/strategies do not work in the real world?

https://pdfs.semanticscholar.org/db15/1836543d8a70db1dabef3d... "Bayesian regression and Bitcoin"

> The strategy is able to nearly double the investment in less than 60 day period when run against real data trace.

http://cs229.stanford.edu/proj2015/029_report.pdf "Algorithmic Trading of Cryptocurrency Based on Twitter Sentiment Analysis"

http://journals.plos.org/plosone/article?id=10.1371/journal.... "When Bitcoin encounters information in an online forum: Using text mining to analyse user opinions and predict value fluctuation"

https://pdfs.semanticscholar.org/e065/3631b4a476abf5276a264f... "Automated Bitcoin Trading via Machine Learning Algorithms"