职业与工作方法wired.com编辑精选
为了记住所学的一切，臣服于这个算法（2008）
To Remember Everything You Learn, Surrender to This Algorithm (2008)
2018 — 2021，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
这篇 2008 年 Wired 文章介绍 Piotr Wozniak 与 SuperMemo：用算法安排不断拉长的复习间隔，让人以较少时间长期记住所学内容。文章也涉及遗忘与记忆的机制，以及把学习交给算法所需的纪律和代价。
为什么经久不衰：间隔重复后来被 Anki 等工具普及，而文中关于记忆并非简单衰退、复习时机决定长期保持的洞见至今仍是高效学习的核心。
HN 评论精选
Anki 插件（图像遮挡、Cloze Overlapper）和共享牌组把间隔重复扩展到医学等复杂学习，作者亲测有效。
很少有人试过 Anki（SuperMemo 的免费替代品），试过它插件的人更少，而插件才是它真正出彩的地方。原版 Anki 主要适合文本卡片，手机应用则有助于利用一天中的碎片时间。Glutanimate 把 Anki 提升到了全新水平：他做了顺手界面，可遮挡图片任意部分并生成卡片（Image Occlusion Enhanced），我用它高效制作并记住了成千上万张解剖学卡片；Cloze Overlapper 对不能漏步骤的有序内容（如医学 OSCE）很好用。Anki 还允许共享牌组，医学生合作制作了高质量牌组备考 STEP。说实话我一直是相当平庸的学生，大局概念没问题，但长期记住零碎信息或顺序性信息很吃力，微积分和有机化学花了我过多时间；现在不再如此。间隔重复加上视觉/文本/听觉学习是成功配方，其可能性不应被低估。
Mbioguy查看英文原文
Few people have tried Anki (a free alternative to SuperMemo). Even fewer have tried its add-ons, which is where it truly shines! Vanilla Anki is mostly good for text flashcarding, with the phone app helpful for making use of those little bits of downtime throughout the day. https://www.youtube.com/watch?v=c-4xOe79epU&list=PL3MozITKTz5YFHDGB19ypxcYfJ1ITk_6o https://www.youtube.com/watch?v=QzBoDe3PgAc&list=PL3MozITKTz5Y9owI163AJMYqKwhFrTKcT Glutanimate has taken Anki to a whole new level. He created a painless UI for occluding any part of an image and making Anki flashcards out of it (Image Occlusion Enhanced). I used it to efficiently create and memorize thousands of anatomy flashcards. Ordered lists can be a real pain to memorize, but when not missing steps is crucial (as it is for medical OSCEs), Cloze Overlapper has worked very well. Anki lets you share your decks with others, and medical students have collaboratively created very high quality study decks for studying for the various STEP exams. To be honest, I was always a fairly mediocre student. Big-picture concepts and figuring things out on the fly, no prob. But I've always struggled to nail down bits of information long-term or learn sequential information, meaning calc and ochem required inordinate amounts of time. No longer the case. Spaced repetition plus visual/text/auditory learning is a recipe for success. The possibilities here should not be underestimated. Folks on Hacker News have talked about the value of information commons, and this right here is the next best example behind Wikipedia I have ever encountered. While quality collaborative decks exist for things like medical school, learning languages, and more, none exist specifically for the program I am in (PA school). I am currently creating my own with the goal of it being the core of a quality collaborative deck. I am using Gephi to spatially organize concept maps for diagnoses complete with incidence and strength of associations, when such information is available. I then export these maps to Anki, use Visual Occlusion Enhanced to block out the information I want to recall, and voila: time-efficient first-time learning and long-term retention.
用 Anki 备考博士资格和测度论，并建议把卡片做成定义、问题、证明等层次，像单元测试和集成测试。
我用 Anki（类似 SuperMemo）准备博士资格考试，它确实有帮助。之后我又坚持了一阵，不断加卡片。我确信，如果没有间隔重复软件，我无法通过测度论概率课。当我有技术想法而手边没有参考资料时，这软件也非常有用，因为我能记住许多结果的细节；它似乎还通过消除查资料的延迟而加速了我的思考。最终我没时间或需要继续复习就停了，但打算博士毕业后清理卡片再重新开始。我强烈推荐它。一条建议：我把卡片当作快速测试，失败就触发复习；很多人以为卡片只能是定义，但我有些卡片是定义，有些是短问题，有些是证明。定义是单元测试，问题和证明是集成测试，两者都需要。
btrettel查看英文原文
I used Anki (similar to SuperMemo) to study for my PhD qualifiers and it definitely helped. I kept up the cards for a while after that, adding more and more. I'm convinced I would have not passed the measure theoretic probability theory class I took without spaced repetition software. The software also proved very useful when I would have a technical idea and had no reference on me as I could remember the details of many results. It seemed to accelerate my thoughts in a way too by removing the delay to look up some information. Eventually, I did not have the time or need to keep reviewing the cards, so I stopped. But I intend to pick it up again after cleaning up the cards after my PhD. I highly recommend the software. One piece of advice: I treat these flash cards as basically fast tests that trigger a review if you fail. I recommend this approach as many people seem to think flash cards can only be definitions. Some of my cards are definitions, some are short problems, some are proofs, etc. The definitions are unit tests. Problems and proofs are integration tests. Both are necessary.
遗忘不是记忆消失而是提取失败，回忆是重建过程，长期记忆容量近乎无限。
“直到今天，”Bjork 说，“大多数人认为遗忘就是衰退，记忆像沙滩上的脚印逐渐淡去。但大量研究已经否定了这一点。记忆似乎消失了，是因为你无法回忆它，但我们可以证明它仍然在那里。例如，你仍然能在一组项目中认出某个‘被遗忘’的项目。是的，如果不持续使用，东西会变得无法访问，但它们并没有消失。”我第一次听到时觉得非常开眼界。显然，我们的长期记忆几乎是无限的，你一旦学好某样东西，就永远不会真正失去它。另一个同样有趣的记忆事实：记忆不是一种‘东西’，而是一个过程。当你回忆某事时，你实际上是在根据与它相关的各种因素重建记忆，很像古生物学家根据化石残骸重建恐龙图像。
Arun2009查看英文原文
> "To this day," Bjork says, "most people think about forgetting as decay, that memories are like footprints in the sand that gradually fade away. But that has been disproved by a lot of research. The memory appears to be gone because you can't recall it, but we can prove that it's still there. For instance, you can still recognize a 'forgotten' item in a group. Yes, without continued use, things become inaccessible. But they are not gone." This was quite eye opening to me when I first heard of it. Apparently, our long term memory is virtually limitless. You never truly lose something you once had learned well. Another fact about memory that I found equally interesting: memory is not a "thing" but a process. When you recall something, you are actually reconstructing the memory from various factors associated with it, pretty much like how a paleontologist might reconstruct the image of a dinosaur from fossil remains.
SuperMemo 算法在漏复习时更宽容，但界面难用；作者希望开源 SM18 并推荐 supermemo.guru。
对我来说，SuperMemo 的排程算法比 Anki 好处理得多：如果我漏了几天，它不会用惩罚性的复习安排把我淹没。因此，我真希望 Woz 能开源 SM18 算法；用 SM 的界面真的很痛苦。我也不喜欢 Anki 的界面，但在这方面它远远好于 SM。另外，顺便说一句：我很喜欢 Woz 的 wiki，里面充满了关于学习的有趣洞见：https://supermemo.guru
SirensOfTitan查看英文原文
The SuperMemo scheduling algorithm is a lot easier for me to deal with than Anki: if I miss a couple days, it doesn't overwhelm me with a punishing review schedule. With that, I really wish Woz would open source the SM18 algorithm, dealing with the SM UI is really painful. I don't love the Anki UI either, but it's streets ahead of SM in that dimension. Also, tangentially related: I really love Woz's wiki, which is filled with interesting insights on learning: https://supermemo.guru
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