Be careful. The indexers might hear this and reassure you that the S&P is only optimal with Uber included at exactly the date it did and the fund will fail otherwise.
I understand that there is a lot of hype around ML/DL, but that is not really my field of expertise, and I don't want to oversell my skills :) Optimization solves tons of really interesting real-world problems, though.
After seeing that academics still have to take a “two job” approach with serious research and fun research I’m not convinced of this. Not to mention the very protracted timelines to get to that stage of freedom.
That depends on whether you accept the risk of having to find another line of work. Depending on the place, you can do almost anything you want even at PhD level. I've been on a chain of grants, doing quite freely what I want, for over a decade. But I accept it may break at any point and then I'll just go do something else.
After PhD there will be nobody telling, and often not even caring, what to do. But that may mean that you don't get your PhD or you don't get another grant to live on. If you get a tenure it almost literally means that you can't be fired even if you do nothing at all. What is surprising is that almost all with tenure keep running the rat race even though they don't really get anything at least material out of it.
(Nitpick: I think serious research is the fun one. The one churned to get another grant is neither serious nor fun.)
I am a postdoc, just have been for quite a while (on four different grants at least). In Finnish academia it's not that uncommon to stay a postdoc even until retirement.
> That’s not true. If you make the hiring cut in you’re in for about 5 years of grunt work as an assistant prof.
For teaching and admin yes. But at least in fields I know, what research you do or whether you do at all is all up to you. Of course the risk is that you'll be unemployed after the assistant prof. term ends. My point is that if you don't care about that, you're quite free to do whatever research-wise.
Maybe, but it's probably a relatively small circle that elevates someone's status by being in academia. (Not to say that isn't the circle whose opinions matter to them, though).
EuroNCAP has a standardized 'Vulnerable Road User' (VRU) test protocol since at least 2012. [0]
This vehicle will absolutely fail every single specified test.
Anyone buying this should first come to terms with the fact that it is not a rational purchase, rather than trying to post-rationalize reasons to do so.
If the “Lindy effect” holds true for the 911, it might be quite a long time before the 911 and its variants go out of style.
The same cannot be said for the cyber truck, and all of the other short lived prototype cars that have very harsh angular lines.
The 911 has the highest average resale value, relative to the original price, of any car on Earth. It depreciates less than any other vehicle. I don't think you're going to be correct.
I don’t think that’s how the end of ICE vehicles will happen.
It’ll be death by a thousand cuts. New ICE vehicles will be increasingly rare in showrooms. There will be bans in city centres. Gas stations will start to disappear. Those that remain will be required to sell blends with increasing amounts of non-fossil derived gasoline, which will be considerably more expensive than current prices, and far more expensive to run.
Eventually, driving ICE vehicles will be like horse riding today - a niche, expensive, smelly hobby that is conducted well outside city limits.
Let's imagine there was a 20 year old who dropped out of CS and spent the next 2 years reading Knuth and entered the work force at 22. Can you see any way that student would not be succesful?
I know someone who did something very similar (but in math) and jumped into a grad math program at age 17.
They would be at a significant disadvantage over students that completed their degree.
Reading TAOCP is the least efficient way to learn about algorithms. Just because something is harder doesn't mean it's better. Can't even put TAOCP in resume without appearing cringe.
>I know someone who did something very similar (but in math) and jumped into a grad math program at age 17.
Can you share more about this, even IMO medalists go to undergrad first.
> Reading TAOCP is the least efficient way to learn about algorithms
"Learning the algorithms" isn't a binary checkbox. It's a gradient of thinking and math skills, ranging up to a researcher in the field. TAOCP is the only book I know if that will give you that depth.
Learning those skills is not for everyone, but can be extremely valuable, and open a lot more doors than graduating with a class of 10,000 other CS students.
> Can you share more about this, even IMO medalists go to undergrad first.
He was an "undergrad" whose first math class was graduate real analysis.
I am asking you how will you tell the HR person overseeing your application that you have "mastered" Knuth's TAOCP. On paper, you have candidate A with university degree and 2 internships and B that sat in his basement and did TAOCP.
Which would you think they'd choose?
>He was an "undergrad" whose first math class was graduate real analysis.
This is unlikely, he'd still have to pass undergrad Math exams. I'd wager there are plenty of those for a 4 year degree.
> but can be extremely valuable, and open a lot more doors than graduating with a class of 10,000 other CS students.
You need to convince the hiring manager that the skills are extremely valuable. No one is going to take the word for it. Deep theoretical CS doesn't always translate to industry success. The flaw in your reasoning is that you'd try to impress some hardcore CS guy from super-duper company with TAOCP. But they already get 10s of thousands of applications. It won't even get the resume read without a BsC. All the companies which talk like broken records that they don't care about degrees, actually do care about them a *lot* and in your first intro call they'd ask about it if you even get that far.
Keep in mind during interview you have to implement the algorithm fast in a common language Java, C++ or Python. Just being theoretical about it isn't enough.
