But it is scientist approved.
Or are you going to go back on the scientific process and just join the same group as climate change deniers.
Now these guys may not be the best programmers out there. As programming is different for every type of job.
Someone who can compile a nice compiler may not be able to make an OS as well. Or an OS developer may not be able to make a clean User interface for a web site.
There are so many details out there that makes a comparison near impossible. What this list captures are the Most popular programmers. Who's popularity is often due to their personality that makes their program popular.
We as programmers tend to come up with new innovative solutions to problems all the time, and often all this work isn't noticed by anyone, because it works so well that no one ever notices.
The window leads to a lot of mistakes as well, probably far more than a video feed dying.
Cases have been documented when flying over an large body of water pilots can get disinterested and confuse their up from down, and fly their plains upside down, until they crash.
In the rare case where the feed dies, there are a bunch of other instruments available for them.
To much Science Fiction and not enough Science Fact.
A common theme in Science Fiction is the idea that technology will replace humans, which is often true. However most SciFi usually takes this idea and follows the slippery slop to a far more interesting to read, but most likely not possible worst case situation.
SciFi books about say a middle grade analyst having to change careers in his mid 40's because technology had made his current job obsolete. Is rather dull. But if that system some how became the all knowing overlord, picking who lives and who lives on a global scale. Now that is interesting, and allows conflict with a rag tag team of Humans in their seemingly impossible task in out thinking the super computer.
When you read a cautionary tail, it isn't about stopping progress, but opening your mind to other options, if these options are bad, put insurances to protect the bad stuff from happening.
Where their are the rare cases where a kid who doesn't have the mental block on this is how we need to do things can come up with a much more innovative solution. However most of the time, the best they achieve is creating something that other engineers have though of before but had rejected the idea, because of the trade-offs it can bring, being too expensive, doesn't meet quality standards, parts are hard to replace, cannot purchase the right to use a patent, excessively dangerous, etc....
I had invented a lot of crazy stuff as a kid, I was lucky I never started a fire with the designs. (A lot of wire cloth hanger that are not isolated were often my primary material)
Hey stop throwing in facts, that messes up a perfectly good outrage. Every story needs to be 1 paragraph long and at least 2 sentences of editorial in it for it to be legit.
Figuring out the best programming language is just an opening to a flame war.
1. Different languages have chosen a different set of trade offs as to meet the problems they solve. Speed to run vs speed to code. Compiled vs interpreted. Verbose descriptive command vs quick to type but cryptic commands.
2. Different platforms. Are you coding for Windows or Linux perhaps for Apple. How much do you want to take advantaged of the platforms features?
3. You tend to favor what you know. Why do you think most of these top languages are C like. They are just variants on what you know.
Having had the choice to choose a language for a project there are a lot of factors. To say this language is superior then the rest is silly because the other languages were made for a reason.
It's funny because it is true.
Perhaps if I worked for a company that allows some time for me to tinker on my own project for a while, like google, then I may get some use out of it. But for the most part by the end of the day I don't even bother using a computer.
Translation is like predicting the weather. If you want to do an okay job of predicting the weather, predict either the same as this day last year or the same as yesterday. That will get you something like 60-70% success. Modelling local pressure systems will get you another 5-10% fairly easily. Getting from 80% correct to 90% is insanely hard.
For machine translation, building a database of 3-grams or 4-grams and just doing simple pattern matching (which is what Google Translate does) gets you 70% accuracy quite easily (between romance languages, anyway. It really sucks for Japanese or Russian, for example). Extending the n-gram size; however, quickly hits diminishing returns. Your increases in accuracy depend on a corpus and when you get to the size of n-gram where you're really accurate, you're effectively needing a human to have already translated each sentence.
Machine-aided translation can give huge increases in productivity. Completely computerised translation has already got most of the low-hanging fruit and will have a very difficult job of getting to the level of a moderately competent bilingual human.