Fragments, 2023d
https://www-users.tebibyte.io/~yihanwu1024/2023/fragments-2023d/

新年快乐！

似乎解开了美国留学生租车难题

弄个最廉价的 AAA 会员（每年 $50–80 不等），然后开 Hertz 就不收低龄费不收额外添加司机费（每个人都要是会员）

Android 的 Facebook 化

发达社会 in a nutshell

感觉 industry 做的事情就是，雇足够多的人来进行 short-term thinking

https://www.melconway.com/Home/Committees_Paper.html
Organizations, who design systems, are constrained to produce designs which are copies of the communication structures of these organizations.

Ref:

准备下一次网友面基局。这个春假各位都在哪里？

This is an instructive origin story for a field of research. The field begins with a focus on a basic and well-defined underlying mechanism—the activity of a single neuron. Then, as the technology scales, it grows in opacity; as the scope of the field’s success widens, so does the ambition of its claims. The contrast with climate modelling is telling. Climate models have expanded in scale and reach, but at each step the models must hew to a ground truth of historical, measurable fact. Even models of covid or elections need to be measured against external data. The success of deep learning is different. Trillions of parameters are fine-tuned on larger and larger corpora that uncover more and more correlations across a range of phenomena. The success of this data-driven approach isn’t without danger. We run the risk of conflating success on well-defined tasks with an understanding of the underlying phenomenon—thought—that motivated the models in the first place.
Part of the problem is that, in many cases, we actually want to use models as replacements for thinking. That’s the raison d’être of modelling—substitution. It’s useful to recall the story of Icarus. If only he had just done his flying well below the sun. The fact that his wings worked near sea level didn’t mean they were a good design for the upper atmosphere. If we don’t understand how a model works, then we aren’t in a good position to know its limitations until something goes wrong. By then it might be too late.
https://www.newyorker.com/culture/annals-of-inquiry/how-much-of-the-world-is-it-possible-to-model

During employee town hall meetings at GE, some of the employees would express concern that the company was too focused on the short term. Jack Welch, then CEO, was fond of replying, “Long term is just a series of short terms.” When employees express such a concern to a CEO, more likely than not what they are really asking is: “What’s this all for?” What is all our hard work contributing to beyond the metrics and material rewards? Welch’s answer revealed that, to him, there was no higher cause at play. The goal was simply to perform, perform again and perform again

https://twitter.com/ThatGuyPyros/status/1750621477936734484