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danschmitt

Ask HN: Learning the Basics of Astronomy

Since I finished my PhD and left the university, I have been trying to learn new subjects besides work, whenever wife and child leave a few hours of free time per week. I have always been interested in anything to do with planets, stars, etc. The new pictures of black holes and the James Webb telescope have put me under a new spell. So I decided to invest some time in learning the basics of...

( Read More... | 1 comment | 4 points | on HN )
> capital is what makes future productivity improvements possible. If you took a risk investing your capital, but that return is taxed the same as wage income (which has zero risk associated with it), you would be discouraged from investing that capital, and instead consume more of it (ala, why invest in your business buying plant and equipment, when you could just go on a lavish vacation!).

The fairy tale that no one would invest if, instead of 100%, they were only allowed to keep, say, 50% of the profits is far-fetched. The game would go on, only with more (in the optimal case) redistribution and less accumulation among the already well-off. The issue here is the relative inequality caused by capital gains, which in the long run tears societies apart, because the middle class can no longer afford apartments/houses and vacations, and the lower class can no longer afford basic needs (food, health care, mobility).

Could you explain this in more detail? I am not very familiar with analog hybrid circuits for ML.
As much as I agree, I also wonder if we can switch to sustainable energy sources fast enough. Efficiency of training and inference may be able to make at least a small saving here and thus gain valuable time.

Ask HN: What is your take on carbon emissions of Machine Learning

At the latest since the widely cited article on Green AI [1], there has been increased discussion about the energy consumption of ML. Whenever I talk to colleagues about this, we always agree that there is a dangerous potential lying dormant here, but somehow it cannot be properly grasped. There is simply a lack of really good data. Calculators for emission like from Victor Schmidt and the...

( Read More... | 10 comments | 11 points | on HN )
Re:The history of the end of poverty has just begun on Tuesday January 25, 2022 @04:11PM (#30078083)
It is always nice to see such narratives based on robust data. For similar stories backed by data I can also recommend the book "Factfulnes" by Hans Rosling [1].

When we talk about basic needs, our global community is making tremendous progress. At the same time, we should not forget that the same system that abolishes poverty also creates enormous inequality, which not only makes people unhappier, but also leads to enormous social tensions within whole societies. So while we should be celebrating the decline in poverty, we are somewhat also left with a sour taste about the side effects that occur.

[1] https://www.goodreads.com/book/show/34890015-factfulness

Ask HN: What is your take on carbon emissions of Machine Learning

At the latest since the widely cited article on Green AI [1], there has been increased discussion about the energy consumption of ML. Whenever I talk to colleagues about this, we always agree that there is a dangerous potential lying dormant here, but somehow it cannot be properly grasped. There is simply a lack of really good data. Calculators for emission like from Victor Schmidt and the...

( Read More... | no comments | 2 points | on HN )