970 karma · joined April 19, 2014
https://amirmasoudabdol.name
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Again, I’m not saying that it will happen, but it could. Dependent of R on third party packages and a company to push it forward it’s not necessarily a good thing.
P.S. Python IDEs are crappy too!
Now, if I want to address your comment. I don’t think “this was the way things have been done here, let’s do it like that from now on” is a good approach. If there is a better way, even if it’s more complicated, at least it has to be tried and tested. If a more “sophisticated” tool proves to be useful, let it be. Not everyone in a team has to use the same set of tools, and if they see the benefit in something more “sophisticated”, they might want to try it, even if it was not explored before. People can learn, there is always a better way/tool and one tool cannot do it all.
R by itself is a mess, and I don’t think I have to say much about that. R community is big and that’s good and bad. It’s good because amazing people are developing amazing packages for it. It’s bad because there is a lot of bad packages. It’s a lot like JavaScript community. I have a feeling the community has started to reward “having a package”, and everyone has a package.
Besides the quality of R packages and R being a strange programming language, R gets the job done. However, if your job is anything beyond some statistics and data processing, then good luck. I’m not saying that you cannot achieve what you want to achieve using R, however, good luck reading R code. I found it extremely hard to read R codes and so far 90% of codes that I’ve encountered have little to no comments.
If you like DDG, recommend it to friends and coworkers. I usually put a link in newsletter if appropriate.
Machine Learning will (have) the same issue if the only thing that matters is hitting a certain level of accuracy given your model and data. This has been observed in Kaggle competitions over and over, you ask a group of people to find the best fit, and they'll, by learning your train, validation and test datasets.
As mentioned, problem is not p-value, or null hypothesis testing, the problem is journals who promoted the wrong incentive, and educators who were not aware of the consequences and propagated the wrong incentive (interpretation) to students.
It was a few weeks ago that someone shared “The Dark Age of AI” on HN [1]. I think we are promising way over what Drew McDermott thought we would not going to promise. This is to the extend that we are applying AI on assessing Art, Creativity and even quality and novelty of Science, something that in a way we don’t even understand (or trying to understand) ourselves at the time that we are publishing it.
That’s how it should be. WhatsApp’s desktop apps are technically another front-end to your secured database on your phone. I’m searching for the tweet of one of iOS security researcher that confirmed this. That’s also the reason that your WhatsApp desktop client stops working when you are out of range. That’s being said, I’ve noticed that recently this is changing and somehow the desktop app maintains the data a bit longer. It’s still not completely independent but I think it’s in the transition period. If that happened, then their E2E has to be different.
By the way, I think the security code from one of your devices, probably your phone, can be encoded to the QR code and transfer to the client.
I assume WhatsApp implementation is a hybrid between mirroring the information and some sort of secure handshake via the QR code.
[1]: https://www.theatlantic.com/family/archive/2018/06/marshmall...
If you use them occasionally you think they are amazing and much better than most other networks but if you rely on them everyday then you quickly realize how bad they are. Lots of random delays and unpredictable behaviors. Smallest change in weather causes disruption. And they are actually expensive even in comparison. (I cannot find the EU report that showed that, I’ll update the comment with it)