Parallel Experiments
https://www.casticle.fm/baleen-1/ 推荐一下糊糊的新邮件通讯。
I especially liked: https://www.youtube.com/watch?v=HeQX2HjkcNo
Great explanation of Gödel’s incompleteness theorem
Great explanation of Gödel’s incompleteness theorem
YouTube
Math's Fundamental Flaw
Not everything that is true can be proven. This discovery transformed infinity, changed the course of a world war and led to the modern computer. This video is sponsored by Brilliant. The first 200 people to sign up via https://brilliant.org/veritasium get…
Parallel Experiments
https://club.q24.io/membership/ 赶在最新一期解散派对 [1] 之前,推荐一下傅丰元(Bob Fu)的「灵感买家俱乐部」。加入有半年了,很喜欢会员通讯、业余公司和解散派对等项目,也从中获取了很多「灵感」。 至今觉得认识 Bob 是一件很神奇的事情:我曾经先后在偶然的情况下了解到他主催的《离线》杂志 [2] 和利器社区 [3],但直到后来才发现它们是同一个人做的,并且好几个朋友也跟这两个项目或 Bob 本人有着各种联系。有一种世界线收束的感觉 : ) 也正是这样的社区,才让…
再次推荐,这篇是非常好的了解灵感买家俱乐部的方式。https://bobfu.zhubai.love/posts/2201061462389899264
野鱼志
不管肉身是否移民,先为自己选一个喜欢的线上居所
Hi,《野鱼志》的读者们,今天的文章算是一个番外吧,是近期在灵感买家俱乐部公众号发布的文章合集。文章改编自八月份「谈谈心:动用你的想象力」社群交流会的对话。上篇是俱乐部内容和变化,适合新人了解;下篇是提问与交流,谈到了一些俱乐部建造的机制。虽然很长,但已是目前最容易了解灵感买家俱乐部的方式了 :)-丰元Hi 我是灵感买家俱乐部的傅丰元 aka 鲍勃。很多人吐槽一直不知道灵感买家俱乐部到底做点啥,这...
Very interesting film, recommended: https://www.imdb.com/title/tt9764362/
IMDb
The Menu (2022) ⭐ 7.2 | Comedy, Horror, Thriller
1h 47m | R
https://coke.do/issues/115-1468280
推荐可乐周报,质量很棒,比如最新这期就有两个非常好的 insight:
- 免费贡献99%的部分,对剩下的1%收费。https://dailywritinghabits.substack.com/p/give-away-99-for-free-monetize-the
- 四种作者,你想成为哪一种?https://qr.ae/pvux48
推荐可乐周报,质量很棒,比如最新这期就有两个非常好的 insight:
- 免费贡献99%的部分,对剩下的1%收费。https://dailywritinghabits.substack.com/p/give-away-99-for-free-monetize-the
- 四种作者,你想成为哪一种?https://qr.ae/pvux48
https://evantravers.com/articles/2022/06/30/dating-other-task-managers/
Great insights. The main takeaway for me is to have "the List" and "the Brain", where "the List" is things you committed to do soon (say today).
I have been using a similar system where there is a list of "immediate todos" and a backlog. The difference is my "immediate todos" are not actually what I committed to do soon. And that sometimes leads to procrastination. I will be trying out this new "the List vs. the Brain" approach to see if it helps.
> Still more intriguing: Brain and List could be separate systems.
E.g. copy items from the List to a piece of paper first thing in the morning.
Great insights. The main takeaway for me is to have "the List" and "the Brain", where "the List" is things you committed to do soon (say today).
I have been using a similar system where there is a list of "immediate todos" and a backlog. The difference is my "immediate todos" are not actually what I committed to do soon. And that sometimes leads to procrastination. I will be trying out this new "the List vs. the Brain" approach to see if it helps.
> Still more intriguing: Brain and List could be separate systems.
E.g. copy items from the List to a piece of paper first thing in the morning.
evantravers.com
Dating Other Task Managers
I've a confession… I've been seeing other todo lists.
I don't have great reasons. It started because I wanted to have the option of freedom from Apple despite having invested a ridiculous amount of time and automation capital into the ecosystem.
...
I don't have great reasons. It started because I wanted to have the option of freedom from Apple despite having invested a ridiculous amount of time and automation capital into the ecosystem.
...
https://lloydtabb.substack.com/p/data-is-rectangular-and-other-limiting
A primer on where SQL falls short especially with hierarchical / nested repeated data and an attempt to solve it.
Two things that are particularly interesting:
- Malloy introduces the concept of aggregate locality [1] to make it much easier and less error-prone to express query intent with nested repeated data. See also symmetric aggregates [2].
- Malloy not only understands nested data, but also writes nested data.
There are also the VS Code Extension [3], native DuckDB support, ... that makes it easy to work with Malloy.
[1] https://malloydata.github.io/documentation/language/aggregates.html#aggregate-locality
[2] https://cloud.google.com/looker/docs/best-practices/understanding-symmetric-aggregates
[3] https://marketplace.visualstudio.com/items?itemName=malloydata.malloy-vscode
Disclaimer: Malloy is an experimental project created by lloyd tabb, the co-founder of Looker which was acquired by Google. I currently work in the Looker organization but don't directly work on or with Malloy. Opinions are my own.
A primer on where SQL falls short especially with hierarchical / nested repeated data and an attempt to solve it.
Two things that are particularly interesting:
- Malloy introduces the concept of aggregate locality [1] to make it much easier and less error-prone to express query intent with nested repeated data. See also symmetric aggregates [2].
- Malloy not only understands nested data, but also writes nested data.
There are also the VS Code Extension [3], native DuckDB support, ... that makes it easy to work with Malloy.
[1] https://malloydata.github.io/documentation/language/aggregates.html#aggregate-locality
[2] https://cloud.google.com/looker/docs/best-practices/understanding-symmetric-aggregates
[3] https://marketplace.visualstudio.com/items?itemName=malloydata.malloy-vscode
Disclaimer: Malloy is an experimental project created by lloyd tabb, the co-founder of Looker which was acquired by Google. I currently work in the Looker organization but don't directly work on or with Malloy. Opinions are my own.
Making Things
Data is Rectangular and other Limiting Misconceptions
Malloy breaks data's rectangular strangle hold.
The annual must-watch: https://www.youtube.com/watch?v=c0Eo7fwGBJ4
YouTube
20(22) Games You Should Have Played
Support the channel on Patreon!: https://www.patreon.com/ArchitectofGames
Follow me on twitter!: https://twitter.com/Thefearalcarrot
As 2022 comes to a close, it's time to look back and reflect on a jam-packed year in videogaming - so many great games got…
Follow me on twitter!: https://twitter.com/Thefearalcarrot
As 2022 comes to a close, it's time to look back and reflect on a jam-packed year in videogaming - so many great games got…
Forwarded from 啰哩啰嗦分享频道
The problem with stupidity, though, is that it often goes hand-in-hand with power. Bonhoeffer writes, “Upon closer observation, it becomes apparent that every strong upsurge of power in the public sphere, be it of a political or of a religious nature, infects a large part of humankind with stupidity.”
This works in two ways. The first is that stupidity does not disbar you from holding office or authority. History and politics are swimming with examples of when the stupid have risen to the top (and where the smart are excluded or killed). Second, the nature of power requires that people surrender certain faculties necessary for intelligent thought — faculties like independence, critical thinking, and reflection.
https://bigthink.com/thinking/bonhoeffers-theory-stupidity-evil/
This works in two ways. The first is that stupidity does not disbar you from holding office or authority. History and politics are swimming with examples of when the stupid have risen to the top (and where the smart are excluded or killed). Second, the nature of power requires that people surrender certain faculties necessary for intelligent thought — faculties like independence, critical thinking, and reflection.
https://bigthink.com/thinking/bonhoeffers-theory-stupidity-evil/
Big Think
Bonhoeffer's "theory of stupidity": We have more to fear from stupid people than evil ones
Bonhoeffer's "theory of stupidity" posits that we have more to fear from stupidity than evil. The latter is easier to defeat than the former.
A great overview/analysis piece
https://a16z.com/2023/01/19/who-owns-the-generative-ai-platform/
https://a16z.com/2023/01/19/who-owns-the-generative-ai-platform/
Andreessen Horowitz
Who Owns the Generative AI Platform?
Generative AI will have a massive impact in the software industry and beyond. The goal of this postGenerative AI will have a massive impact on the software industry. Learn about who owns generative AI platforms, market dynamics, and business models. is to…
https://motherduck.com/blog/big-data-is-dead/
> MOST PEOPLE DON’T HAVE THAT MUCH DATA: In order to understand why large data sizes are rare, it is helpful to think about where the data actually comes from. Imagine you’re a medium sized business, with a thousand customers. Let’s say each one of your customers places a new order every day with a hundred line items. This is relatively frequent, but it is still probably less than a megabyte of data generated per day. In three years you would still only have a gigabyte, and it would take millenia to generate a terabyte.
> WORKLOAD SIZES ARE SMALLER THAN OVERALL DATA SIZES: There are acute economic pressures incentivizing people to reduce the amount of data they process. Just because you can scale out and process something very fast doesn’t mean you can do so inexpensively. If you use a thousand nodes to get a result, that is probably going to cost you an arm and a leg. The Petabyte query I used to run on stage to show off BigQuery cost $5,000 at retail prices. Very few people would want to run something so expensive.
> DATA IS A LIABILITY: An alternate definition of Big Data is “when the cost of keeping data around is less than the cost of figuring out what to throw away.” I like this definition because it encapsulates why people end up with Big Data. It isn’t because they need it; they just haven’t bothered to delete it.
> MOST PEOPLE DON’T HAVE THAT MUCH DATA: In order to understand why large data sizes are rare, it is helpful to think about where the data actually comes from. Imagine you’re a medium sized business, with a thousand customers. Let’s say each one of your customers places a new order every day with a hundred line items. This is relatively frequent, but it is still probably less than a megabyte of data generated per day. In three years you would still only have a gigabyte, and it would take millenia to generate a terabyte.
> WORKLOAD SIZES ARE SMALLER THAN OVERALL DATA SIZES: There are acute economic pressures incentivizing people to reduce the amount of data they process. Just because you can scale out and process something very fast doesn’t mean you can do so inexpensively. If you use a thousand nodes to get a result, that is probably going to cost you an arm and a leg. The Petabyte query I used to run on stage to show off BigQuery cost $5,000 at retail prices. Very few people would want to run something so expensive.
> DATA IS A LIABILITY: An alternate definition of Big Data is “when the cost of keeping data around is less than the cost of figuring out what to throw away.” I like this definition because it encapsulates why people end up with Big Data. It isn’t because they need it; they just haven’t bothered to delete it.
MotherDuck
Big Data is Dead
Big data is dead. Long live easy data.
Forwarded from 推特翻译
反乌托邦文学的想象并不是凭空而来的。实际上,反乌托邦文学中想象的部分,恰恰来源于我们当今的种族主义资本主义现实中。
如果我刻薄一点,我会直接说:历史以来,反乌托邦文学就是把被边缘被歧视被压迫的人的现实生活拿过来,移到有特权的人的身上,写成的“恐怖”小说:
假如所有人都不得不移民流浪到别的的地方,不仅仅是那些第三世界的人...
假如所有人都没有生育自由,连中产白人女性都没有了生育自由...
从正面说,反乌托邦文学让那些想象力缺乏的人至少看到了被压迫的人的生活。从反面来说,被压迫的人的真实生活被虚构成了“科幻小说”,让真实的压迫反而隐身了。
这也就是为什么这本书中我选择了不去设想过度可怕的未来。因为可怕的事情在过去发生过,可怕的事情在现今还在继续发生。
—— 诗集《世界不断终结,世界继续前行》。美国作家弗兰妮·蔡。 source
如果我刻薄一点,我会直接说:历史以来,反乌托邦文学就是把被边缘被歧视被压迫的人的现实生活拿过来,移到有特权的人的身上,写成的“恐怖”小说:
假如所有人都不得不移民流浪到别的的地方,不仅仅是那些第三世界的人...
假如所有人都没有生育自由,连中产白人女性都没有了生育自由...
从正面说,反乌托邦文学让那些想象力缺乏的人至少看到了被压迫的人的生活。从反面来说,被压迫的人的真实生活被虚构成了“科幻小说”,让真实的压迫反而隐身了。
这也就是为什么这本书中我选择了不去设想过度可怕的未来。因为可怕的事情在过去发生过,可怕的事情在现今还在继续发生。
—— 诗集《世界不断终结,世界继续前行》。美国作家弗兰妮·蔡。 source