794 karma · joined June 23, 2014
Yes, I'm aware that India is a single country, while Europe wasn't. But with the right amount of autonomy, you end up with the same conditions, and it's not too different in practice.
But, on the other hand, his counterargument for the existence of other potential factors seems to me to be quite weak and lacking the same rigor. The existence of "basic sex differences" is not discussed in detail, with only a couple of references. And a lot of his counterargument seems to be based on a few example countries with high gender equality rankings and low STEM participation.
Is there any validation that these gender equality rankings are a useful indicator of gender equality? What about factors that surface only after school/college in these countries? What about network effects in various fields?
Not that I'm saying such factors do exist. But the author makes a somewhat strong (IMO) argument against stereotype threat, implicit bias etc. and a very weak argument for the existence of other factors.
But compared to China, (a) the frequency of an encounter with a random person on the street as a pedestrian is significantly lower in US cities and (b) I imagine the levels of poverty in China were/are much higher, which might be a factor why scams are frequent?
It is designed exactly for this use-case -- visualizing results of an ongoing simulation. It does best effort plotting, but doesn't block computation for plotting. I would be happy to receive feedback on the package.
I think (IMHO) it has the most usable UI and apparent performance. It has nice built-in features like ad-blocking, mouse gestures (including rocker gestures), some nice single key shortcuts for moving around tabs. The V7 tabs extension [1] provides a really good experience for vertical tabs. It has also sufficient customizability, full compatibility with Chrome extensions.
I am aware that all of these are possible in other browsers, and I do use Chrome/Firefox for non-trivial amounts of time for various reasons with all equivalent customizations, but Opera just seems so much more usable and performant for me across platforms, although I can't put my finger down on one single thing that makes it so.
Edit: I have to say I'm really liking the vertical tabs on the new Vivaldi and their new features. Maybe I'll try making it my primary browser for a while.
https://blog.openhatch.org/2017/celebrating-our-successes-an...
[1] https://support.cloudflare.com/hc/en-us/articles/203349264-A...
https://github.com/Laverna/laverna/issues/547
https://github.com/Laverna/laverna/issues/683
https://github.com/Laverna/laverna/issues/678
https://github.com/Laverna/laverna/issues/675
https://github.com/Laverna/laverna/issues/770
https://github.com/Laverna/laverna/issues/747
Edit: Formatting
Can you elaborate on how it is wrong at this point?
One thing that I miss though is a nice web interface for calendar and contacts. Especially if I want to do some sort of cleanup of data. Is this functionality planned? Or is there some open source web calendaring software that you would recommend?
[1] https://en.wikipedia.org/w/index.php?title=Tobermorite&actio...
The paper which showed that the general case of Sudoku is NP-complete was apparently this one [1] (Linked from wikipedia)
[1] http://www-imai.is.s.u-tokyo.ac.jp/~yato/data2/SIGAL87-2.pdf
There was some interesting work a while ago that solved sudoku using spiking neural networks too [1] (Fig. 5) with some nice associated theory.
[1] http://journals.plos.org/ploscompbiol/article?id=10.1371/jou...
I wouldn't really say that. There's a lot of progress being made in using and understanding biological processes for useful tasks. Not surprisingly, the biological mechanisms are surprisingly complex and rich and vary a lot through the brain (like you mentioned with the dendrites. Dendrites also work like coincidence detection mechanisms sometimes in some layers of the cortex [1] for instance)
[2] gives a very nice overview of what is needed from both machine learning and computational neuroscience to solve the entire problem of understanding the human brain.
There was the liquid state computing paper [3] in 2002 which showed that random networks of spiking neurons can perform some computations and have memory even in the absence of special learning rules.
There has also been quite some work on understanding e.g. the role of assemblies of neurons (groups of neurons firing), assembly sequences, plasticity rules, theory formulating neural activity in a probabilistic manner, a better understanding of the role of inhibition, dendrites etc.
And lastly, there have been huge advances in neuromorphic computing, both digital and analog. In some cases, the performance on these chips (that use spiking neurons) approaches that of state of the art machine learning. e.g. [4]
[1] http://www.sciencedirect.com/science/article/pii/S0166223612...
[2] https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5021692/
[3] http://www.mitpressjournals.org/doi/abs/10.1162/089976602760...
The Neuroscience book by Mark Bear gives a nice introductory overview of the biology behind a lot of neural processes: https://www.amazon.com/Neuroscience-Exploring-Mark-F-Bear/dp...
If you're interested in computational neural models, I would highly recommend Wolfgram Gerstner's recent book (available for free online): http://neuronaldynamics.epfl.ch
The book by Dayan and Abbot on theoretical neuroscience is quite nice too: https://mitpress.mit.edu/books/theoretical-neuroscience
After this, you'll probably want to read new review papers, since it's a field that's moving quite fast now. (Especially with new measurement techniques in the past few years)
It would also be nice to have some data about which company the hosting belongs too, since as a general rule I try to avoid hosts from the Endurance International Group [1]
[1] https://en.wikipedia.org/wiki/Endurance_International_Group
[1] http://www.npr.org/sections/goatsandsoda/2016/07/29/48736009...