To illustrate the power of the atomic idea, suppose that we have a drop of water a quarter of an inch on the side. If we look at it very closely we see nothing but water—smooth, continuous water. Even if we magnify it with the best optical microscope available—roughly two thousand times—then the water drop will be roughly forty feet across, about as big as a large room, and if we looked rather closely, we would still see relatively smooth water—but here and there small football-shaped things swimming back and forth. Very interesting. These are paramecia. [...] This, of course, is a subject for biology, but for the present we pass on and look still more closely at the water material itself, magnifying it two thousand times again.
这个笑点真是 very interesting
#TheFeynmanLecturesOnPhysics #读书
What’s that? Have over 220 people, projects, and organisations signed the web0 manifesto since last night?
They sure have! 🎉
读过《Explaining Humans》
https://neodb.social/books/252251/
这本书我没读完,只读了三分之一,我觉得很不值得一读。。
标题太误导人了,这本书 by no means 在 explain humans,而是拿一些科学知识强行类比作者自己的生活体验。从科学知识里悟做人的道理根本就是扯淡,本身毫无科学性可言,甚至毫无新意,她做的这些类比就是教科书上帮助理解以及同学们课间自己开玩笑也会讲的内容,最多幽默一下而已,我很难相信作者是认真的在用这些东西来理解人类。作者是计算生物学家,但这不代表她对心理学以及目录里那些广泛的学科有任何发言权,有的内容扯淡到了伪科学的地步。
#ExplainingHumans
In the classic prism example, like my mum’s crystal, the light then disperses into its seven visible wavelengths: red, orange, yellow, green, blue, indigo, violet (plus the invisible: infrared and ultraviolet).
seven visible wavelengths...这个作者在说什么胡话...wavelength 是连续的啊,这真的是一个 Ph.D 会说的话吗。
Then there are people like me, who have had to ask how long you should hug someone to offer comfort (two to three seconds since you’re asking, four if it was a really bad break-up).
啊??怎么也得抱个一分钟吧,一边抱一边拍一边讲安慰的话直到对面觉得好一点了。。作者生活中的经验怎么跟我完全不一样啊。
my difference actually held one considerable advantage. Unlike pretty much any neurotypical teenager on the planet, I was immune from peer pressure.
我!!完全没有 peer !!
Because kids like nothing better than to gang up on the outsider it was often open season on me. ‘You’re nuts’, ‘She’s an alien’, ‘You should be in a zoo.’ (The last was a personal favourite.)
[...] it usually took me a few hours to actually understand why the comment was hostile
我赞同最后一句,我认为我目前没怎么被骂过是因为我看不出来对面在骂我,我会很高兴地表示感谢。
第一章读完了,感觉很怪,我的设想是它会对比 machine learning 和 human learning 的相似性,类似于“智慧背囊”那种通过生活中一个可以做类比的事件来讲道理,只不过类比的对象是科学研究的内容。但看起来 machine learning 只是一个发散点而已,作者最后讲到的内容其实关联性并没有那么大,而且结构松散,一个话题没讲清楚就又跳到别的内容去了,过一会儿又跳回来。。莫非这就是 ADHD 写作法??
不过如果自己主动 interpret 一下就还是有所启发的,比如我的理解就是“要有计划地行事,但同时也要把错误和可能出的状况计划进去”。
It’s why statistics uses standard error as a basic principle, building in an assumption that there will always be things that don’t accord with expectations and predictions. [...]
People, on the other hand, can be less sanguine when things don’t go according to plan. You won’t find many commuters cheerfully quoting standard error when their train gets delayed or cancelled.
这和我前两天读到的 #TheDemonHauntedWorld 是一样的思路呀!https://rhabarberbarbara.bar/@unagi/107544607279401820
但我认为没有人 cheerfully quoting standard error when their train gets delayed or cancelled 是因为 no one likes seeing their train gets delayed or cancelled, but I strongly suggest that 德铁在列车时刻表的晚点时间旁边加上置信区间 to get people mentally prepared, otherwise 我打算自己统计一下我上班途中的晚点规律。