As an experienced programmer, I have spent enough time trying to understand and make sense of some aspects of pure/higher math, specifically logic, that I feel qualified to say this:
- Experienced programmers are better trained at formality and precision than mathematicians, in some respects, and are able to ask questions that make experienced mathematicians go "why are you asking this question?" or "just get used to the idea (because that's what everyone does)"
- Much of higher math study advice (such as the one posted here) is aimed at laymen. And experienced programmers are no laymen.
- Mathematicians are laymen in many aspects compared to experienced programmers. An experienced programmer will have an easier time learning and using a proof assistant. Mathematicians (most of them) run away as fast as they can the moment they hear the phrase 'proof assistant.'
Touch typing is not only about typing faster. It gives you this other ability of "running your control panel" out of the home keys only (four fings on each hand resting on a,s,d,f and j,k,l,;). When you have to lift one of the hands off the home keys and move it to the mouse to do anything, and I mean anything, it's super annoying and frustrating.
Those who never learned to touch type are not likely to grok the appeal of mouseless work.
> Is there a reason to make this distinction here?
The original method, by Whitted, that looked much better than any previous methods, and yet looks horrible by today's standards, is ray tracing. It had no global illumination.
The method based on solving, explicitly or implicitly, the rendering equation by James Kajiya, and one that has built-in global illumination, is path tracing.
The distinction is not important for buzzword hijacking hacks, marketing gimmickers, and snake oil salesmen.
Machine learning is nowhere close to replacing the human coding activity.
Nonetheless, machine learning is creeping up into newer and newer areas of application in surprising, unpredictable, and unprecedented ways, and ignoring it would put you at peril as a tech worker. This is what I mean when I use the term 'software 2.0'.
I just want to point out one thing, for the record.
I'm sorry "Stop Monday Morning Quarterbacking (MMQ)" isn't directed at you per se, but the general direction of whoever is reading my comment.
MMQ is, unfortunately, practiced widely in many prediction/retrospection circles like startups, finance, economics, politics.
I'm speaking from a the point of view of scientific rigor, or at least quantitative data analysis. No one does that when it comes to opining about the cause-and-effect of an event in the past. If you're "the winner", anything you say about why you won, would be taken as gospel. "Winner is always right". Rigorous analysis is very hard, and costly, and to what end? Just so you could say "my reasoning is based on analysis"? That's a very boring thing to say. Unless rigorous-analysis finds utility in applications like decision-making for future startups, and is shown to work over and over again (maybe we'll need AI for that), no one is going to bother with it.
MySpace was massive when Facebook was a year or two old. I had accounts on both and MySpace looked way more attractive compared to FB (it had the feel of Instagram).
So no, FB did not take over overnight. And even a few years into FB, no one (yes, no one) knew that FB will go past MySpace and there will simply be no comparison between the two 10 or 15 years down the road.
When FB took over MySpace a full FOUR years in [0], investors knew FB had momentum, but no one (yes, no one) had any idea why.
Not only that, many investors had no second thoughts about MySpace, and it felt like a competition space, instead of a winner take all. There was still an opinion that MySpace will retake the top spot again 'any minute now.'
So why FB took over MySpace? We don't know. Yes, we don't know in 2020, 16 years later.
(I'm not dismissing hard work, marketing, execution, commitment. But it was there for both FB and MySpace. It's a pre-requisite. You think MySpace folks slacked off and that's why FB got ahead? think again).
Homebrew is 11 years old. I'm willing to bet there are as many people (likely fewer) people who knew Guido in 2002, when Python was 11 years old, or even 2005, when Google hired Guido.
And I'm willing to bet when Google hired Guido in 2005, they didn't put him through a coding challenge humiliation clown show day.
> This is Guido van Rossum. If I were him and asked to solve puzzles, I'd tell the hiring company to fuck off.
Not sure what you're trying to get at:
MacOS homebrew creator is an effin nobody compared to Guido, therefore he should "know his place", "get in line" and invert a binary tree on the whiteboard and act like an obedient tech interview candidate that he really is?
OR
MacOS homebrew creator should've told Google to fuck off?
I agree what you say while also pointing out that unix home directory has become a complete mess. Anyone (any installed software) can do whatever they like, there is no mechanism of enforcement, and advice in the form of constructive critque or comment is not even a drop in the bucket towards fixing the problem.
> YC application needs one to clearly articulate who ones target customers are, what they do today, why is it such a pain, and what one is building to solve that pain-point ...
Which in my opinion is the hardest part. If you don't know what you're doing, it doesn't matter if you're selling or not, it doesn't matter if you're building or not. That comes later.
But that's not it. How do you know what you're doing, or going to do? It doesn't happen by sitting down with buddies or co-founders and having a brainstorming session. This is where 'you have to be at the right place and the right time' but also 'you have to have spent the right amount of time thinking about it'
The right amount of time could be 1 week, or could be 10 years. Yes sometimes you need 10 years to get to the point where when you found a company, you start generating sales within a matter of months.
On their reddit AMA thread [0], can you point me to a single of their over a hundred answers which expresses concerns that media is overhyping and running away with the story?
On the contrary, how would you 'nudge' the laymen's thought to be directed a certain way? would saying things like "So it's a big deal" and then putting a question mark at the end work? [1]. Does that ring a bell, or are you daft enough that you would need data to be convinced that doing so is a sign of wanting attention, and wanting the story to get sensationalized?
And why would you do a public forum AMA and then go through the effort to post over a hundred answers to begin with, if you didn't want the story to blow up?
I don't know if you're associated with any research or academic body or not, but here's a news flash for you: stories don't get big on their own, not in today's short-attention-span world. The researchers take the just-published work to their organization's news outlet and ask them to cover it. The unspoken, and often spoken, reasoning being "this is significant". If a researcher wants to practice caution, it is super easy these days to do so, just don't make a mountain out of a mole hill.
Also you and the other downvote sheep, go eff yourself and do your own research about what really happened a month ago (I was there and was telling everyone that these researchers are bullshitters taking everyone for a ride).
> ... scientists themselves weren't sensationalizing their findings ...
Yeah right.
They were saying things like "please prove us wrong" while doing interview rounds, and (I'm sure) celebrating, loving and looking forward to more and more limelight, so strictly speaking they were not "sensationalizing their findings".
In a related story, OJ and Casey Anthony did not kill anyone.
- Experienced programmers are better trained at formality and precision than mathematicians, in some respects, and are able to ask questions that make experienced mathematicians go "why are you asking this question?" or "just get used to the idea (because that's what everyone does)"
- Much of higher math study advice (such as the one posted here) is aimed at laymen. And experienced programmers are no laymen.
- Mathematicians are laymen in many aspects compared to experienced programmers. An experienced programmer will have an easier time learning and using a proof assistant. Mathematicians (most of them) run away as fast as they can the moment they hear the phrase 'proof assistant.'