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g9yuayon

1,327 karmajoined vor 19 Jahren

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g9yuayon
·vor 2 Monaten·discuss
And in developing countries too. People may not realize that when there's no industrialization, people still need fuel. So they cut down tree that they could walk to. Just look at the pictures missionaries and travelers took in China a hundred years ago. Wherever there were people, there were only barren land. Heck, it was like that even in the early 80s in some places.
g9yuayon
·vor 3 Monaten·discuss
> How much of the job is a structured set of tasks vs. taking accountability?

More accurately, how many jobs are probabilistically mechanical. That is, how many jobs are really the execution of a serious Bayesian decisions with a strong prior. LLMs are really great at displacing such jobs.
g9yuayon
·vor 4 Monaten·discuss
> Lattner found nothing innovative in the code generated by AI

I don't think the replacement is binary. Instead, it’s a spectrum. The real concern for many software engineers is whether AI reduces demand enough to leave the field oversupplied. And that should be a question of economy: are we going to have enough new business problems to solve? If we do, AI will help us but will not replace us. If not, well, we are going to do a lot of bike-shedding work anyway, which means many of us will lose our jobs, with or without AI.
g9yuayon
·vor 4 Monaten·discuss
I like the Chinese alternative better: 古法编程. It feels like playful self-deprecation, suggesting old-school, handcrafted coding with a wink.

Ape coding sounds harsher and more insulting, implying mindless or sloppy work rather than humor.
g9yuayon
·vor 5 Monaten·discuss
Honest question: why are we so afraid of population decline? For people on the left, it means less consumption, less environment impact, less carbon footprint, and in general fewer damn evil people who are destroying the mother earth. For the right, everyone is responsible for their own destiny including their retirement life so they worry about their retirement spending solely on their own anyway. In practice, Japan seems to be fine. In particular their young people have so many job openings to fill.

So, what exactly are we worrying about? The social security is not sustainable? The medical cost will go through the roof? There's no enough military power? There won't be enough consumption to support the growth (in that case, why do we have to keep growing? Why can't we just stay where we are? Again, not rhetorical questions but honestly curious about the answers)?
g9yuayon
·vor 8 Monaten·discuss
https://stanfordreview.org/jo-boaler-and-the-woke-math-death..., and wikipedia on Math Wars: https://en.wikipedia.org/wiki/Math_wars

Personally, I find Boaler's advocacy extreme. Her famous quote: "Every student is capable of understanding every theorem in mathematics – and beyond – the mathematics curriculum. They just need the opportunity to struggle with rich tasks and see mathematics as a conceptual, creative subject.” This sounds inspiring, but in practice she advocated the policy of truly dumbing down math curriculums and text books. To say the least, shouldn't she at least demonstrate that she could understand any theorem? But instead, she advocated that SFUSD eliminate algebra from 8th Grade . Another example was that the curriculum that she advocated, College Preparatory Mathematics, was so boring and trivial. She also said something along the line "Traditional mathematics teaching is repetitive and uninspiring. We give students 30 similar problems to do over and over again, and it bores them and turns them off math for life.” What's funny is that the alternatives that Boaler prescribed were quite uninspiring and low level: https://www.youcubed.org/tasks/. All I can derive from her policies and complaints is that she couldn't do math. Why people would listen to someone who sucked at math about math education is beyond me.
g9yuayon
·vor 8 Monaten·discuss
> so we have been unwilling to invest in our own children.

The school districts like SFUSD are actually sabotaging the growth of our kids in the name of equity. They're committed to ideas from people like Jo Boaler, and they tried very hard to dumb down the curriculum. The real tragedy is that kids from wealthy families will just get other means of education to make up the difference. It's the kids who desperately need the quality education who are going to be left behind.

If it were up to me, I'd send those people to jail (yes yes, I know. I'm just angry and lashing out)
g9yuayon
·vor 8 Monaten·discuss
I'm curious why Lisp didn't gain mass popularity despite its advantages. In fact, I was wondering if it's popularity has event decreased in the past decade or so. I remember in the 2000s and even early 2010s, there were active discussion on Clojure, Scheme, and functional/logic programming in general. There seems much less discussion or usage nowadays. One theory is that popular languages have absorbed many features of functional programming, so the mainstream programmers do not feel the need to switch. My pet theory is that many of us mortals get the productivity boost from the ecosystem, in particular powerful libraries and frameworks. Given that, the amazing features of lisp, such as its s-expression, may not be powerful enough to sway users to switch.
g9yuayon
·vor 9 Monaten·discuss
I think both can true. I learned a lot in my university, and my learning has been carrying me ever since. Case in point, it was never a problem for me to pick up functional programming or programming-language concepts in general because the courses on programming languages were so wonderful. I had no problem tap into formal verifications or data science or distributed systems because my universities gave me solid fundamentals. Heck, I was not even a good student back then. It was Sam Toueg of the failure detector fame who taught us distributed systems, yet I was lost most of the time and I thought he was talking some abstract nonsense. Only after I graduated could I appreciate the framework of analyzing distributed systems that he taught us.

On the other hand, we certainly learned more after graduation (or something is wrong, right?). When I was in the AI course, the CS department was all about symbolic reasoning I didn't even know that Hinton was in the same department. I think what matters is the core training stayed with me and helped me learn new stuff year after year.
g9yuayon
·vor 9 Monaten·discuss
My own experience: https://www.quora.com/Could-online-coding-programs-and-codin...

And my wife's experience: https://www.quora.com/What-is-it-like-to-learn-computer-scie...

In short, the training that we got from our universities was invaluable, and I always feel fortunate and grateful to my CS department.
g9yuayon
·vor 10 Monaten·discuss
I guess I have a different philosophy: whoever owns the problem should learn everything necessary to solve the problem. In my case, the engineers showed no interests in learning the algorithm and the math behind it. For instance, when they built the dashboard for the testing, they omitted a few important columns and got the column names wrong. When I tested them on their understanding of the method, there was none. To say the least, my team should know enough to challenge me in case I made any mistake, or so I assume.

On a side note, I believe it is an individual's responsibility to find the coolness in their project. What's the fun of building a dashboard that I have done a thousand times? What's the fun of carrying out a routine that does not challenge me? But solving a problem in a most rigorous and generalized way? That is something in which an engineer can find some fun. Or maybe it's just me.
g9yuayon
·vor 10 Monaten·discuss
I can attest how useful Bayesian analysis is. My team recently needed to sample from many millions of items to test their qualities. The question is that given a certain budget and expectation, what's the minimum or maximum number of items that we need to sample. There was an elegant solution to this problem.

What was surprising, though, was how reluctant the engineers are to learn such basic techniques. It's not like the math was hard. They all went through the first-year college math and I'm sure they did reasonably well.
g9yuayon
·vor 2 Jahren·discuss
When I grew up in China, students in a school were divided into fixed classes. Those classes formed great communities, as we spent hours every day for at least three years and some for 6 years. Each class had a head teacher, who fostered the sense of community too. No one would mock people for geeking out. No one would mock people for not being good at sports. No one would mock those who struggled at academics. At least not openly. We loved each other and still do. Our bond was so strong that we had regular reunions every few years, and most of my classmates would make it. We had multiple couples who were high-school sweat hearts, even though dating in high school was a taboo in China then. The concepts like nerds, like queen bees, like sports jockeys, like that those who can get drugs and drinks are popular... They were all new and parts of the culture shock to me when I moved to the US.
g9yuayon
·vor 5 Jahren·discuss
I'm not sure if the calculation is correct. 2000 people winning lotteries out of at least millions of people, right? Yet in the startup word, it is thousands of people out a few hundreds of thousands? Another factor to consider is that your equity keeps giving, while lottery is a one-off deal.
g9yuayon
·vor 5 Jahren·discuss
Many comments below focus on failures with a single startup. I think it misses the point. Working for startups is risky, but the key is to build a system that increases your accumulated probability of success -- this is exactly why it's important to live in the bay area and work for some startups there, at least before the Covid-19. You get to see a large number of people who didn't fund any company, but still became financially independent by choosing to join the right companies at the right time. You get to see how those people make their choices. You get to see how those people decide to jump ship. You get to build a social circle where you learn lots of first-hand information about startups. There are a few simple steps that worked well for many people (again, no guarantee of success, but they do increase accumulated probability of finding the right company).

- You bet on product you love. Airbnb/Pinterest/Uber before 2013, Netflix before 2010, FB before 2009, Google before 2003, Databriks before 2017, Tesla before 2017.

- You bet on sectors. SDN, gig economy, search, big data, and etc.

- You bet on company's productivity - the customers/engineer grows exponentially without Uber-style marketing cost - Instagram/WhatsApp; the company releases features faster than they hire - Google; people deliver without working like a dog - Netflix

- You bet on people you know or you admire

- You bet on the leaders in each sector
g9yuayon
·vor 5 Jahren·discuss
Startup is not a lottery. Working for startup is risky, but the key is to build a system that increases your accumulated probability of success -- this is exactly why it's important to live in the bay area and work for some startups there, at least before the Covid-19. You get to see a large number of people who didn't fund any company, but still became financially independent or built an explosive career by choosing to join the right companies at the right time. You get to see how those people make their choices. You get to see how those people decide to jump ship. You get to build a social circle where you learn lots of first-hand information about startups.

Yes, it's still risky to join a startup, but no it's not a lottery. The chance of being rewarded handsomely is orders of magnitude higher than buying lottery.
g9yuayon
·vor 5 Jahren·discuss
Is there any evidence that people criticized Yellen because she is a woman?