He also now has a strong incentive to stick to what he said. Complying with China after publicly saying he wouldn't would be an even bigger PR disaster than what Blizzard is facing right now.
Yep they are two very different languages. However with the possible exception of the build times argument, the points for choosing Go over C++ also apply to Go over C.
They touched on this in the article, but I'll go into more detail here since it's been fashionable for years to bash on "Blub" languages like Java or Go. I myself was guilty of this for a long time until I started using these languages in settings where they shine, and developed an appreciation for them.
The argument is nothing to do with machine chugging time, and is entirely towards developer time. The problem with expressive languages like Lisp, Ruby, Python, etc. is that the language ends up varying from person to person - the more expressive the language, the more variance there is. This is a feature when you're a small team because the abstractions you build let you move quickly, but it is a bug when you're a large team maintaining a piece of software over years, where developers have come and gone. The ramp-up time to learn and understand the various abstractions that people have built over the years ends up accumulating and cancelling out the gains that those abstractions gave earlier on.
Blub languages on the other hand tend to be more uniform, so it's easier for someone who isn't very familiar with the code to dive in and understand what is going on.
What I meant was the machine learning systems that have developed in the last decade since the 2008 crash. Many of these are black boxes with thousands to millions of variables, and it's very difficult to understand exactly why a ML algorithm made a decision that it did.
> "Machines are taking control of investing..... Funds run by computers that follow rules set by humans"
One of the points that the article makes is that this statement is changing, that computers are increasingly creating their own rules. The literal next sentence:
"New artificial-intelligence programs are also writing their own investing rules, in ways their human masters only partly understand."
You're right though, that the responsibility still falls on the humans. Anybody running algos that they don't understand should ensure that they are covered from a legal/ethical perspective.
Speaking for Canada rather than Europe but I imagine the argument is mostly the same. The supply and demand ratios are different. Canada has very few pure software firms like Google or Amazon compared to the US, so there is significantly less competition for the engineers that work there. This drives prices down - or rather, prevents prices from being driven up.
77 is a large enough sample size to produce statistically significant results in a lot of cases, depending on the problem. For example, using 77 men and women, you could easily see a statistically significant difference in height between genders.
This paper is pretty simple, it's just a straight-forward before-and-after test. They are holding a lot of factors constant and not doing an observational study, so 77 is actually a fine sample size for something like this.
> most of us have seen managers try to improve quarterly numbers at the expense of company health
Yep, this does happen. The point though, is to let shareholders rather than managers decide if this is a good choice. If managers are sacrificing the long-term health of the company, shareholders can vote them out or choose to sell their stake.
This is one of the downsides of the rise of passive investing and ETFs based on market cap - less votes are going into the system and holding people accountable.
> In this study, we tested 77 undergraduates who were randomly assigned to play either a popular video game (Portal 2) or a popular brain training game (Lumosity) for 8 h.
This is exactly the reason why Typescript took off and none of the other compile-to-JS languages did (other than a brief flash by CoffeeScript). Dart had a very similar problem as Reason - it wasn't Javascript. The interop between Dart and JS libraries was just too much of a pain to deal with, where in Typescript everything just worked.
Since building your own ecosystem that rivals the JS ecosystem for libraries is an extremely difficult task, any candidate to replace JS must have good interop with its libraries to be successful.
Not that I've worked in a lot of places, but everywhere that I've worked that uses C at all treats it this way. Writing new C code is considered a no-no.
From my experience hiring in startups (and personal life experience, having left the startup world at 28), over-30s have higher salary requirements than startups can afford. It's not even just a Bay Area thing; in pretty much all markets you pay a premium for experience.
They do set up shop elsewhere. The problem is that the BigCos are also doing the same (NYC, Seattle, Austin, Boulder, etc.) and bringing their high salaries with them.
BigCos like Google and Microsoft can afford to pay big bucks and collude together. Startups on the other hand can't always afford to pay $100k+ for a junior engineer.
"Don't Tread on Me" is pretty light as far as Metallica goes. I wonder what the cougar would have done if she had unloaded "Battery" or "Dyer's Eve" on it.
Does anybody know how hard it is for non-Chinese citizens to live and work in China?
One of the competitive advantages of the US has been its ability to draw top talent from all over the world and not just its own citizens. Chinese citizens leaving the US is not a good thing, but it is just one nationality. If China manages to draw talent from everywhere, then the US has a real problem ahead of it.
For example, my team in the US only has a few US citizens on it, most of us are foreigners who moved here for the opportunities. While a few are Chinese, the majority are from countries other than China and the US.