kirillseva

Just as US military satellites take pictures of Russian and Chinese facilities as well. Both can play this game

I'd definitely put John Carmack on the list, probably as #1. And I think antirez should be somewhere up there as well

Right now such currency is USD, with the Fed acting as a trusted third party. That's one of the reasons why other countries are investing in "blockchain technology", whatever that entails

The biggest names in AI technology are the very same advertisement companies. General public can't win in this arms race

Maybe the bot is trying to boost its github commit stats before applying for a job at Oracle?

Could have just used "rockstar" https://github.com/avinassh/rockstar

I'm no saying that HN is bad and Ethereum is good. For one thing, here I am posting on HN, so it's pretty telling :)

I just wanted to highlight the difference and that that HN is not free. It's free as in beer.

As far as inconvenience goes, it's temporary. Give it some time (2-5 years, I'd say) and it's only going to be about paying real money for it.

And if you think that EOS is decentralized, and that it will ever see the light of day, then even paying money won't be a thing for the users as they have a different business model for dApps, where the dApp owner has to stake EOS coins to get a share of EOS network's resources. Which is more similar to existing business model of renting EC2 servers

HN comments are free but the platform is owned by YC and YC enforces certain rules as they see fit. In Ethereum there is no owner, but looks like you have to pay for that

Brakes are fly-by-wire on new cars because slamming the brake is not the most optimal strategy for stopping the car as fast as you can. And it can also damage the car.

So many deaths happening in London. Must be something in the water there.

the thing that he was sentenced for was a white collar crime with no monetary damages. If it were a white collar crime with damage done then sure, prison time might have been appropriate. 7 years seems too harsh, and was most likely the byproduct of Martin behaving like an asshole and the general public being "upset" about the drug price hike

IOTA has a lot of PhD contributors, allegedly

are there more windows PCs that care about running graphics-demanding software, or are there more iphones?

that vision is not dead. google "lightning network" for an answer to how this vision will be realized at scale

this app is just USD <> crypto onboarding + price speculations for those who enjoy gambling on their mobile phones

R, python and Julia are all Turing-complete languages, so of course you can drop any two and get by with just the third.

The real selection happens when you consider what's available in opensource world. What code you don't have to write? What high-quality libraries are available vs which ones you will have to write yourself?

On this topic, R has vast advantage over python in some domains, such as bioinformatics for example, while python definitely shines when it comes to deep learning (and using for loops).

You can't just claim that one shouldn't look at R because you personally know one language better the other, quite likely because in your domain it's not being used as much.

I do prefer the deep learnin, NLP and production serving story in python, but you will have to pry dplyr+ggplot from my cold dead hands for quick analysis and charting. Not to mention that pandas's API is a clusterfuck compared to R's native data frames.

You should try https://github.com/robertzk/lockbox for dependency management

It's like bundler or cargo for R

etherdelta

The US government is not a business, its typical income is taxes. This policy of printing trillions of dollars to, essentially, give a loan to banks, all the while devaluing USD for every holder, sounds like a new form of taxation.

> Why did SpaceX spend resources to get them to safe landing then?

collect data + parts of the booster can be reused

coursera has a great course on self-driving cars. the only prerequisite is a college course in linear algebra and some python knowledge. If you don't have either of the two the course is still very much approachable - you'll just have to learn two (or three) things at the same time, so expect to double (or triple) the time you sink into it.

It's worth it

the tweet you link to is architectural search, or figuring out what the neural network should look like (along with its parameters).

If self-driving car ML is "data scientists replacing a driver with computers", architecture search is computers replacing data scientists. $1.2M is roughly 3-4 data scientists' annual compensations at a company like Google or Uber.

Finding hyperparameters for an existing architecture is much easier because you would typically deal with a much lower cardinality in hyperparameter space. SigOpt is helping with that. Google has an internal solution that is able to take advantage of parameters within their job scheduling infrastructure (they actually have a bunch of them, the one I'm talking about is called hyperband [0]). CERN, as far as I know, was using hyperopt [1]. Avant uses an open-source version of SigOpt that we wrote in 2016 called loop [2].

[0] - https://arxiv.org/pdf/1603.06560.pdf [1] - http://hyperopt.github.io/hyperopt [2] - https://github.com/avantoss/loop

pivotal labs -> pivotal tracker

But can jet fuel melt crushed wood?

I highly recommend that you build out more boring themes. Software engineers need resumes too, and interesting looking ones are treated as an expression of creativity. But target demographic for chrome extensions is not on HN, where people care about their privacy, know of a 1000 different ways to abuse trust online, and are capable of creating a custom LaTeX resume if they have to.

People in, say, finance would love to have an easy tool that generates a resume that looks like a banking resume. Your fancy templates are worthless to them - they do not conform to industry standard. I'm sure a lot of other professions have the same culture and you should do some research in this direction.

Otherwise, great product! Wish you best of luck.

This is the spearmint paper, describes how bayesian search algorithms can be parallelized in practice. There was also a very gentle introduction to bayesian optimization, I think it's one of the referenced papers. Cannot seem to find it right now.

https://arxiv.org/pdf/1206.2944.pdf

I know that's too much to ask, but if you implement simple into a "chooser" in https://github.com/avantoss/loop/tree/master/lib/choosers you'll have at least one company using this method!

We use a solution inspired by Jasper Snoek's Spearmint, which allows to somewhat parallelize bayesian search through a concept called "fantasies". If you've never read his paper I encourage you to find it on arxiv. The most gentle and thorough introduction to this topic that I've seen.

Assuming we want to exchange two tokens, let's say, FBI and NSA.

Centralized exchange: send your FBI to exchange's wallet -> exchange updates your balance in its database, i.e. postgres -> trade for NSA -> withdraw NSA, which causes the exchange to send you NSA tokens (if they have them) and update another record in its DB.

The problem is in "if they have them". While normal banks are FDIC insured and a run on the bank won't prevent them from giving you your money, crypto exchanges provide no such guarantees. If the money is stolen from the exchange, like in the case of the OP, then you are SOL. Basically, you have to trust the exchange as much as you trust your bank. And clearly one entity is way more trustworthy than another.

In the decentralized exchange case, instead of trusting an organization to keep money safe through operational processes and tight regulation, you trust a smart contract. Provided that the smart contract has no bugs, this pretty much eliminates the need to trust the exchange. You trust it just as much as you trust mathematics.

Hope my explanation is not too verbose and makes sense.

That's because people should stop using centralized exchanges that don't have their funds insured, and should instead investigate using decentralized exchanges. Cross-blockchain ones are currently being developed, with OmiseGO and KyberNetwork competing to be the first to launch.

On Ethereum this ecosystem is much more developed, and you can choose between EtherDelta, IDEX, 0xProject and Radex.

These exchanges eliminate counterparty risk because you control your funds at all times. They essentially act as matchmakers between those creating buy/sell orders and those who fill them.

not trying to assume any position here, just want to point out that you're looking at the world through the gucci glasses of someone who lives in a 1st world country with functional financial and legal systems.

There are plenty of people in the world who live in countries where the legal system doesn't work, the do not have access to banks, their fiat currency gets manipulated by the corrupt government. And these people now have smartphones and Internet.

You could have just said J.P. Morgan

I'd speculate that top management was aware of the physics limitations to their biggest market advantage, and they probably even had a timeline for when the competition is going to inevitably catch up. So they must have been spending their billions on something that's going to keep the company afloat in XXI century.

Maybe quantum computing, neuromorphic chips, GPGPU and 3D NAND are where it's at for them in the future, and traditional CPUs will be more or less commoditized.