108 karma · joined October 8, 2007
I predict that industries in countries that adopt a carbon tax earlier will end up with a competitive advantage.
Electricity and power generated from carbon emitting sources on the other hand have a much more elastic demand curve. E.g. if your energy bill is cheaper with renewables, no one would choose to go with fossil fuels. Likewise with electric vehicles. If the cost of tanking up an EV is significantly lower than an internal combustion vehicle, people will switch for purely economic reasons.
You can look at the lack of a carbon tax as an incentive on fossil fuels which socializes the externalities.
AI has the potential for massive positive effects as well as massive negative effects.
What saddens me is that we have systems and incentives in place which encourage governments and corporations to use powerful technologies to negative ends.
* Obviously there is room to quibble about the positive/negative balance of individual technologies, e.g. gunpowder, bio-weapons, etc., however I am sure a circumspect analysis could find positives even in things developed primarily to improve the efficiency of war.
According to their 2017 annual report [1], Marriot had $22.9bn in worldwide revenue. A 4% penalty on that would be $900M.
[1] https://marriott.gcs-web.com/static-files/057a8e1a-a5c5-4c20...
It is an interesting thought experiment, though, to consider what facebook would look like if its revenue was derived from convincing users that it was worth a monthly subscription.
"The Quantum Cryptography School for Young Students (QCSYS) is a unique, eight-day enrichment program for students hosted by the Institute for Quantum Computing (IQC) at the University of Waterloo. QCSYS will run August 10-17, 2018 with students arriving August 9 and departing August 18.
The school offers an interesting blend of lectures, hands-on experiments and group work focused on quantum cryptography"
https://uwaterloo.ca/institute-for-quantum-computing/program...
You had a perfect storm of brand new, super powerful tools (the internet providing dirt-cheap distribution, cheap computation, beginner friendly programming languages -- php for facebook, java and python for google, etc.). There was so much low-hanging fruit with relatively little competition.
A very similar thing happened in physics in the early 20th century, and led to the same notion that genius is a fleeting trait concentrated in the young. To quote this BBC article: https://www.bbc.com/news/science-environment-37578899
It was like discovering a new toolkit which could quickly yield discoveries. Or, less charitably, as one scientist said: "mediocre physicists could discover great physics".
Some people rent out a spare room now and again for extra cash, and some people have multiple properties that are occupied exclusively by Airbnb renters, essentially running an unlicensed hotel.
The latter can be extremely obnoxious if its your upstairs neighbor, not to mention the effects that being discovered by Airbnb real estate investors can have on a town or neighborhood.
I don't care if Disney gets to keep the rights to Mickey Mouse. The real problem is all the other stuff that gets swept along in the bargain.
The sweet spot for MiniZinc is in investigating a problem and prototyping a solution. I would say it takes 10-20 hours to get a workable understanding of the language and paradigm, plus or minus your previous experience.
However, MiniZinc is built on backtracking, which scales poorly to real world instances of np-hard problems.
My parents have a Frigidaire Flair double oven from the early 1960s. The thing is amazing, and still works perfectly. I think it cost something like $400 originally, which would be north of $3000 today, however in 1963 the median income was $6200 [1], so that would be closer to $4000 for the median person of today.
For that kind of money, you could definitely get some nicer appliances today. Although the switch from simple analog to complex digital electronics probably puts a more modest ceiling on the lifespan of anything made today.
On the other hand, there is also something to be said for being able to have an oven without taking out a loan!
On an individual level, self-pity, even when justified, is not very helpful, and though the two are not exactly the same, one leads to the other pretty easily.
Recently while writing some matlab found a great example of the sort of trouble a decent type checking system will save you. The predict method takes a machine learning model, and applies it to some data. The output however, is up to the model, and not all models return the same data type (e.g. column vector of doubles, or cell array of strings), making it a pain in the butt to do any abstraction over models.
I am excited for languages like lbstanza that let you have your cake and eat it too.
There is also http://gitxiv.com/, which includes source code.
If you are at a university or a company with deep pockets, you can also use http://dl.acm.org/ or http://ieeexplore.ieee.org/Xplore/home.jsp.
I've also heard of certain hubs of science on the internet, but I wouldn't know anything about that.
In general, scientific books are an overview of a field, which can only occur with sufficient time for hindsight and synthesis. Even a thousand page book such as Koller's PGM will be littered with references and suggestions of papers to read for a deeper understanding.
One partial exception might be the Deep Learning book by Goodfellow and Bengio, which was made public only a month or so ago. Even this, however, is just an overview. http://www.deeplearningbook.org/
One quick example, claiming cities in the 1920s that switched to lead pipes saw ~25% increase in homicides vs those that didn't. http://scholar.harvard.edu/files/jfeigenbaum/files/feigenbau...
I wish I could say I didn't forget things when I was was in university, but I still remember the frustration of coming back from summer vacation and having forgotten half of what we learned last semester.
Isn't that more or less what human brains do?
A neural network is just a curve fitting algorithm optimized to fit a bunch of data, that is, a statistical method. NNs are, to the best of my knowledge, a fairly good analogy for what the physical computation process of the brain.
NNs are also very easy to fool. Mislabel the humans in your robot training data as 'kill', and your network will make bad decisions. Garbage in, garbage out.
If you make a probabilistic model and attach a very high confidence to the things that spirits tell little girls down by the river, then sometimes your model will suggest some terrible ideas. Humans are also notoriously bad at sampling data, but that doesn't mean it isn't what they're doing.
Your edit raises a good question, though! I can't say I have a good answer, but would be interested to hear a good idea for such an experiment.
I want to use the phenomenon the inner monologue and the act of convincing oneself of something as a counter example, but on the other hand, language is very easily generated by statistical methods, and the brain apparently will make decisions and then come up with justifications afterward. http://pss.sagepub.com/content/early/2016/04/27/095679761664...
Not log cabins, but wood framed "Fachwerk" houses are everywhere in Germany, or at least Bavaria.
http://www.people.vcu.edu/~bmangum/fitzstories.html
I've also heard that all the 19th century novels were so long because originally they were serialized, and the author was basically paid per chapter.