历史与人物longnow.org编辑精选
费曼与连接机
Richard Feynman and the Connection Machine (1989)
2013 — 2024，它一次次回到首页
黑点是上首页（≥ 50 分）的那次投稿，空心点是没冲上去的投稿，点越大分数越高。
导读
Danny Hillis 在这篇回忆文章中讲述费曼参与 Thinking Machines 公司 Connection Machine 并行计算机设计的经历，重点写到费曼如何用物理学家的连续、可微直觉来处理路由与缓冲等工程问题。文章也记录了他解决难题时的专注和讲解热情，以及这台早期大规模并行计算机诞生过程中的人物轶事。
为什么经久不衰：它把费曼的思考习惯、教学冲动和一台开创性并行计算机的诞生放在同一篇第一手回忆里，既有科学史价值又很好看，所以多年后仍值得读。
HN 评论精选
费曼专注解题、不被打断、解决后热衷讲解的习惯值得学习。
这可能是费曼最重要的习惯，我试着把它融入自己的生活和学习：“然后他会动手，在便笺纸上涂写并盯着结果。在他解这类谜题的过程中，根本没法打断他。‘别烦我，我忙着呢，’他连头都不抬地说。最终他要么认定问题太难（于是失去兴趣），要么找到解法（于是接下来一两天逢人就讲）。他就这样研究过数据库搜索、地球物理建模、蛋白质折叠、图像分析和读保险单等问题。”
W0lf查看英文原文
This is probably the most important habit of Feynman, I tried to incorporate into my own life and studying: "Then he would set to work, scribbling on a pad of paper and staring at the results. While he was in the middle of this kind of puzzle solving he was impossible to interrupt. "Don't bug me. I'm busy," he would say without even looking up. Eventually he would either decide the problem was too hard (in which case he lost interest), or he would find a solution (in which case he spent the next day or two explaining it to anyone who listened). In this way he worked on problems in database searches, geophysical modeling, protein folding, analyzing images, and reading insurance forms."
用“教别人才算完成发现”概括费曼，并推荐 Hillis 的访谈系列。
我认为这篇文章里的这句话很好地概括了费曼的性格：“直到他把发现教给别人，发现的过程对他才算完成。”我会向喜欢这篇文章的人推荐 Hillis 的 Web of Stories 访谈系列。他以视频形式分享了文章中的几个故事（如 105、106、119、127 和 234），还有很多其他轶事和洞见值得听。Hillis 本人就很有趣，但他还接触过其他 HN 读者可能有兴趣听的人：Marvin Minsky、Jeff Bezos、Freeman Dyson、Steve Jobs 等。
JProthero查看英文原文
I think this sentence from the essay does a nice job of summing up Feynman's character: 'The act of discovery was not complete for him until he had taught it to someone else.' I'd recommend Hillis' Web of Stories interview series [1] to anyone who appreciated this piece. He shares several of the stories described in the essay in video form (e.g. 105, 106, 119, 127 & 234), and there are plenty of other anecdotes and insights worth listening to. I think Hillis is pretty interesting in his own right, but he's crossed paths with some other people in addition to Feynman that HN readers might be interested in hearing about: Marvin Minsky, Jeff Bezos, Freeman Dyson, Steve Jobs etc. [1] https://www.youtube.com/playlist?list=PLVV0r6CmEsFzo005LM6PTERy4uxq92sWe
文章值得反复读；Connection Machine 在流行文化和艺术中的影响也很有趣。
这是我每次被贴出来都会停下来读的文章之一。冷知识：在小说《侏罗纪公园》里，公园的超级计算机是 Cray，但斯皮尔伯格选了 Connection Machine 拍电影，因为他觉得它看起来更酷。另外，艺术家 Karl Sims 用 Connection Machine 做了一些当时令人震惊、今天仍很酷的作品。这台计算机本身也是艺术装置的一部分。
gdubs查看英文原文
This is one of those ones I’ll stop and read every time it gets posted. Bit of trivia: in the novel, “Jurassic Park”, the park’s supercomputer is a Cray, but Spielberg picked a Connection Machine for the movie because he thought it looked cooler. Also, the artist Karl Sims did some outstanding work using the Connection Machine that was mind blowing for the time, and still pretty darn cool today. The computer itself was part of the art installation: https://www.karlsims.com/genetic-images.html
对费曼把离散路由问题连续化、微分化的具体方法好奇，希望有人展开解释。
一篇非常有趣且有信息量的文章。也许有人能试着详细解释一下每个芯片需要多少缓冲区是怎么算出来的？引文：对物理学家来说这也许自然，但对计算机设计者来说，把一组布尔电路当作连续、可微的系统有点奇怪。费曼的路由方程用的是连续量变量，比如“消息地址中 1 的平均个数”。我更习惯用归纳证明和情况分析来分析，而不是对“1 的个数”关于时间求导。他概念上和实践中是怎么做到的？
wuschel查看英文原文
A very entertaining and informative essay. Could perhaps someone try to elaborate on the calculation of buffers needed per chip? Quote: To a physicist this may seem natural, but to a computer designer, treating a set of boolean circuits as a continuous, differentiable system is a bit strange. Feynman's router equations were in terms of variables representing continuous quantities such as "the average number of 1 bits in a message address." I was much more accustomed to seeing analysis in terms of inductive proof and case analysis than taking the derivative of "the number of 1's" with respect to time. How did he do it, conceptionally, and in practice?
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