令人惊讶的是：这种新技术不仅在功能上超越传统方法，在性能指标上也取得了显著优势，100%的成功率和相对较低的成本显示了其技术成熟度和实用性，这可能会使现有的浏览器自动化解决方案迅速过时。

令人惊讶的是：KV Cache内存占用降低了惊人的10.7倍，这一数字远超普通技术优化的幅度。KV Cache是大模型推理中的主要内存消耗部分，如此大幅度的减少意味着同样的硬件可以处理更长的上下文，或者同时运行更多模型实例。

令人惊讶的是：该模型能够一次性生成最多12张风格一致的图片，并支持最多9张参考图输入。这项功能对于需要保持一致性的创作场景（如系列海报、产品多角度图、故事连续画面）来说极为实用，大大提高了工作效率，解决了传统AI图像生成中难以保持风格一致的问题。

令人惊讶的是，GLM-5V-Turbo集成的'股票分析师'Skill能在短短60秒内从四个不同数据源并行采集信息并生成图文交错的研报。这种速度和效率远超传统金融分析师，展示了AI在专业领域的惊人潜力。

令人惊讶的是：AI训练效率的提升速度令人震惊。在短短6年内，语言模型的训练时间从167分钟缩短到不到4分钟，效率提升了40多倍。这种进步远超摩尔定律预测的5倍改进，展示了AI硬件和算法的飞速发展。

令人惊讶的是，Meta声称他们重建的预训练栈只需要Llama 4 Maverick十分之一的计算量就能达到同等能力。这一效率提升是惊人的，表明AI模型训练可能正在经历一个范式转变，从单纯增加计算资源转向优化算法和架构。这可能会对整个AI行业的成本结构和竞争格局产生深远影响。

令人惊讶的是：仅12亿参数的MinerU2.5模型就能通过粗到细的解析策略达到最先进的文档识别精度，同时保持计算效率。这挑战了'越大越好'的模型规模观念，展示了高效架构设计的重要性。

令人惊讶的是：借助AI代理，原本需要数周才能完成的OKR规划流程可以在两天内完成，效率提升惊人。这展示了AI如何彻底改变传统企业规划流程，从冗长的手动过程转变为快速、智能的自动化系统。

令人惊讶的是：SELFDOUBT方法在处理剩余情况时，不仅显著优于基于采样的语义熵方法，而且计算成本降低了10倍。这一发现表明，通过分析模型推理过程中的自我怀疑和验证行为，可以在极低成本下实现比传统方法更准确的不确定性估计，为实际应用提供了高效解决方案。

令人惊讶的是：SELFDOUBT方法仅需单个推理轨迹就能进行不确定性量化，而传统方法通常需要多次采样或访问模型内部参数。这一突破使得该方法可以在延迟和成本受限的部署环境中使用，特别适用于无法获取模型内部信息的专有API，大大降低了实际应用门槛。

令人惊讶的是：Meta声称他们的新模型Muse Spark在计算效率上取得了突破性进展，仅用前代模型Llama 4 Maverick十分之一的计算量就能达到相同能力。这种数量级的效率提升在AI领域极为罕见，可能代表着训练算法和架构设计的重大革新。

令人惊讶的是，尽管新应用数量激增，苹果声称其应用审核团队能够在48小时内处理90%的提交，并且在过去12周内每周处理超过20万个应用提交，平均审核时间为1.5天。这表明苹果可能已经大幅扩展了其审核能力或提高了自动化程度以应对AI带来的应用激增。

令人惊讶的是：即使是有限需求领域，AI也能通过确定性规则实现显著效率提升。AI记账系统能够自动处理分类、对账和报税等任务，这表明即使在传统上需要人工判断的财务领域，AI也能通过标准化流程创造价值。

3-5 倍的组织效率提升——但这来自 17 倍时间地平线的 AI。效率提升与能力提升之间的换算比率约为 TH^0.39，意味着 AI 能力提升的大部分收益被「组织瓶颈」消耗掉了。令人惊讶的是，当执行速度接近无限时，人类组织的协调摩擦、审查流程、实验等待，成为了主要的速度限制因素——而非 AI 本身的能力。

「手机和 IoT 设备的新智能层级」——这个定位本身就是宣战书。E2B 有效参数仅 2.3B，却能在不足 1.5GB 内存中运行，并支持 128K 上下文窗口。令人震惊的是，E4B 在多项指标上超越了 Gemma 3 27B——一个 4.5B 的边缘模型击败了 27B 的上一代旗舰。参数效率的边界正在被彻底重写。

大多数研究者认为要提升推理模型性能，需要增加计算资源和推理步骤。作者提出的RED框架却表明，通过抑制错误森林的生长和修剪后续推理，可以在大幅减少计算资源消耗的同时获得更好的性能，这一结论挑战了资源投入与性能正相关的基本假设。

大多数人认为实时视频处理需要极高的计算资源和帧率才能有效，但作者仅用两块80G加速器就实现了2 FPS的实时系统，并达到了最先进的性能。这一结果挑战了高性能视频处理需要大量计算资源的共识，暗示通过优化算法和架构可以显著降低实时视频处理的计算门槛。

主流观点认为需要高端GPU才能支持长上下文推理的大语言模型，但作者证明TriAttention仅使用消费级单GPU就能部署原本需要高端GPU才能运行的长上下文模型。这一发现挑战了当前对硬件需求的共识，可能使更广泛的开发者能够访问长上下文推理能力。

大多数人认为在KV缓存压缩中，准确率和效率之间存在不可避免的权衡，但作者提出的TriAttention方法能够在保持全注意力推理准确度的同时，实现2.5倍的吞吐量提升或10.7倍的内存减少。这一结果挑战了当前领域内的效率-准确度权衡范式，表明可以通过创新方法打破这一传统限制。

大多数人认为更复杂的处理流程必然意味着更高的成本和更慢的速度。但作者提出Deep Extract虽然执行更多工作且比标准提取调用更耗时，但在大规模应用中仍然比人工审查更快、更便宜、更一致，这一观点挑战了人们对于复杂性与效率之间关系的传统理解。

大多数人认为高质量的AI评估需要大量预算和大量数据，但作者证明通过优化评估者与项目的比例，即使使用适度的总标注量（约1000个）也能实现高度可复现的结果。这一发现挑战了'越多越好'的普遍观念，为资源有限的研究团队提供了实用的评估路径。

大多数人认为GPT-4级别的性能需要同等规模或更大的模型才能实现，但作者展示了他们的4B模型不仅超过了GPT-4.1和GPT-4o，而且模型规模只有后者的1/50。这一发现挑战了AI领域中对模型规模的依赖，暗示了算法创新可能比单纯扩大模型规模更有效。

大多数人认为AI模型性能提升主要依靠参数数量增加，但作者认为通过算法优化和人才聚集，AI模型可以实现450倍的参数压缩，这挑战了'更大参数等于更好性能'的行业共识。

大多数人认为支持140多种语言的多模态模型需要大量计算资源，无法在单个GPU上运行。但作者声称这些模型可以全部适配在单个H100 GPU上，这挑战了我们对大型多语言模型资源需求的认知，暗示模型效率可能大幅提升。

大多数人可能认为初创公司需要依赖昂贵的第三方API来处理大量图像，但作者通过使用开源SAM模型，实现了大规模图像处理而不产生巨额成本。这一观点挑战了'高质量AI服务必须昂贵'的行业共识，展示了开源模型在成本效益方面的优势。

大多数人认为高性能AI模型必然需要大量计算资源和内存。但作者强调Gemma 4的边缘模型是'从头开始为最大计算和内存效率而设计'，暗示即使在资源受限的环境中也能实现高级AI功能，这与行业对AI资源需求的普遍认知相悖。

大多数人认为AI模型的性能与参数规模直接相关，更大的模型必然更强大。但作者指出Gemma 4能够超越比它大20倍的模型，这挑战了'越大越好'的主流认知，暗示效率优化可能比纯规模更重要。

IRS head says free Direct File tax service is ‘gone’ | The Verge<br /> by [[Emma Roth]]<br /> accessed on 2025-08-05T15:49:42

Shift from selling whole birds to value-added processed products. Demonstrates industrial capitalism’s logic: transform raw goods for higher profit Chicken Nuggets represent value-added capitalist strategies.

for - paper - climate crisis - rebound effect - paper - title - Energy efficiency and economy-wide rebound effects: A review of the evidence and its implications - from - post - LinkedIn - rebound effect - https://hyp.is/yz4m_ldBEfC18Bfg0RPf2w/www.linkedin.com/feed/update/urn:li:activity:7346027213776953344/

for - post - LinkedIn - paper - climate crisis - rebound effect - wipes out efficiency gains - to - paper - rebound effects https://hyp.is/Er5r7FdCEfCa45MudqrqPw/www.sciencedirect.com/science/article/pii/S1364032121000769

Successful Secretary Presented by Royal Office Typewriters. A Thomas Craven Film Corporation Production, 1966. https://www.youtube.com/watch?v=If5b2FiDaLk.

Script: Lee Thuna<br /> Educational Consultant: Catharine Stevens<br /> Assistant Director: Willis F. Briley<br /> Design: Francisco Reynders<br /> Director & Producer: Carl A. Carbone<br /> A Thomas Craven Film Corporation Production

"Mother the mail"

gendered subservience

"coding boobytraps"

"I think you'll like the half sheet better. It is faster." —Mr. Typewriter, timestamp

A little bit of the tone of "HAL" from 2001: A Space Odyssey (1968). This is particularly suggestive as H.A.L. was a one letter increment from I.B.M. and the 1966 Royal 660 was designed to compete with IBM's Selectric

This calm voice makes suggestions to a secretary while H.A.L. does it for a male astronaut (a heroic figure of the time period). Suddenly the populace feels the computer might be a bad actor.

"We're living in an electric world, more speed and less effort."—Mr. Typewriter<br /> (techno-utopianism)

Correcting Bad Typing Habits with the Smith Corona Electric Typewriter 63024 by [[PeriscopeFilm]]

Motion should happen only at the level of the fingers and not at the wrist or even the arms. Type only with your fingers and not your wrists or arms.

Allow the carriage to glide to complete the carriage return rather than wasting addition time and energy on pushing it all the way. Let the momentum do the work.

Use the paper release when removing letters to reduce wear on your rollers and prevent ripping of the paper.

See also at https://stock.periscopefilm.com/63024-correcting-bad-typing-habits-with-the-smith-corona-electric-typewriter/

Drop the paper into the top of the platen and against the paper guide to improve alignment can save time.

Setting the right hand margin will help save huge amounts of time from the transcriptionist looking back and forth to get proper margins otherwise.

Using correct typing for numerals will speed up typing numbers as well.

For the top tabulator, use your index fingers alternately instead of hitting it with your entire hand.

Hugging the keys with your fingers allows you to type faster, much like a drummer keeps the sticks closer to the drumhead when drumming quickly.

for - stats - 27% of the gap can be reduced by wind and solar deployment and 20% by action on forests, while efficiency, electrification, fuel switching in buildings, transport and industry sectors can also contribute - UN Emissions Gap Report 2024 - Key Messages

"Well, I already gave him an estimate," he says with a chuckle. "I'm not gonna change that quote, I've been here too long to do that."

It seems like an unwritten rule for typewriter repair shops to go way over on time versus pay to repair a typewriter based on an initial quote.

I've seen at least one other quote like this, but don't think I collected it.

By abstracting and concatenating portions of material, one can more efficiently learn material that would otherwise take more time.

I wonder if you can share libraries of comments. or if that is counter productive b/c it's someone else's voice.

value of peer reviewing

Which study?

Was it mentioned by Robert Caro in his Johnson biography which has a chapter laying out some of this work before electrification?

While the idea of a common user interface on computers may have felt like a selling point when facing a new scary machine with a variety of functionalities, did it really save that much time, effort, and learning curve? Particularly with respect to the common office tools it was replacing?

The common user interface was really more a benefit to the company and all the companies which programmed for it at scale. The benefits are like Melvil Dewey's standardization of the Dewey Decimal Classification which allowed libraries everywhere to work on the same system rather than needing to reinvent their own individually.

This sort of innovation with scalability is helpful as humans are far better at imitation than innovation.

Setting up and learning a note taking or card index system has a reasonably large up-front cost, but learning it well and being able to rely on it over long periods of time will eventually reap larger and cheaper long-term outcomes and benefits.

Unless changing systems creates dramatically larger improvements, the cost of change will surely swamp the benefits making the switch useless. This advice given by Kaiser is still as true today as it was in 1908, we tend not to think about the efficiency as much now as he may have then however and fall trap to shiny object syndrome.

In modern, digital settings, the work of approapriately indexing content is lost in exchange for other forms of organization (tagging, for example), this means one is less reliant on an index for looking up material and more reliant on concordance search of particular words within an ever-growing corpus of collected knowledge.

Over time and with scale, simple tagging may become overwhelming as a search method for finding the requisite material, even when one knows it exists.

As a result a repository may do better in the long run with a small handful of carefully applied rules from the start.

This quote is broadly recognized in economic settings as true, but few in the knowledge management space place emphasis or focus on designing both simple systems which are easy to master and use on a regular, ongoing basis. This allows the knowledge worker the ability to more quickly (almost blindly) handle their indexing and filing operations so that things are precisely where they need them when required for use.

Poor design will not only decrease the ease of use, but also discourage the user from both efficiently using and benefiting from their systems.

Even simple and efficient filing systems require familiarity and expertise for them to effect useful gains to their users, and prove their effectiveness over time. If a user can't get to a basic level of functionality in short time, they're likely to give up on it and never see the ultimate benefits.

Julius Kaiser contemporaneously posits that mass manufacture and maximizing efficiency (greater output for minimum input) are the primary drivers of card index system use in the early 20th century. These also improve both precision and accuracy in handling information which allow for better company or factory operation, which would have been rising concerns for businesses and manufacturing operations at the rise of scientific management during the time period.

This quote is a feature of toxic capitalism, which should be efficient enough to allow a person to quickly obtain another job to thereby make the issue moot.

Part of it is tied into identity as well.

https://en.wikipedia.org/wiki/Jevons_paradox

The increased efficiency in the use of a resource doesn't imply a decrease in the usage of that resource, but rather may cause in incommensurate increase in use because of decrease in cost.

The increased efficiency of the use of a resource may act as a catalyst for increasing usage.

The author, Rediscovering Analog, reads a book at least twice, usually. He first reads it mainly for pleasure, just to enjoy it and to see what's in it. During the second time, if applicable, he goes through the book using intellectual (or learning) systems and methodologies to extract value from the book.

The first pass, which the author terms Scouting, is thus namely for enjoyment, but keeping in mind what might be valuable or interesting that will be valuable in the future, basically an unguided open ear. He has a list of scouted books in each section of the Zettelkasten that might be relevant to the section. What he does is have a stack of physical cards there with just the name of the book and the author, without anything else. Then when author proceeds to extract value from the book, he takes the card out and puts it in the respective book. Afterwards throwing this particular card into the trash. It's a form of the Anti-Library.

( Personally, I would include an appropriate reading cost and a level on Adler's hierarchy of books. In addition, I would make sure that my process of orientation, in the Inquiry-Based Learning framework, has been completed before I put it as a book within the Anti-Library. )

This may not be the most efficient for the purpose of acquiring value, but efficiency is not all there is. Enjoyment is a big part of intellectual work as well, as Antonin Sertillanges argues in his book The Intellectual Life: Its spirit, methods, conditions, as well as Mihaly Csikszentmihaliy in his book Flow.

This points to AI providing the best time savings in draft generation, which fits with the idea of having the AI generate the drafts based on the professional's queries.

For UX designers, this points to AI in a design tool being most useful when it generates drafts (sketches) that the designer then revises. Where UX deliverables don't compare easily to written deliverables is the contextual factors that influence the design, like style guides or design systems. Design too AI assistants don't yet factor those in, though it seems likely it will, if provided style guides and design systems in a format it can read.

Given a draft of sufficient quality that it doesn't require longer to revise than a draft the designer would create on their own, getting additional time to refine sounds great.

I'm not sure what to make of the reduced time to brainstorm when using AI. Without additional information, it's hard not to assume that the AI tool may be influencing the direction of brainstorming as professionals think through the queries they'll use to get the AI to generate the most useful draft possible.

Efficiency and effectiveness measures for specific mnemonic systems may vary from person to person, so one should consider them with respect to their own practices. There may not be a single "right" or "correct" practice universally, but there could be one for everyone individually based on their own choices or preferences.

https://en.wikipedia.org/wiki/Stakhanovite_movement

How much of the 1935 Stakhanovite movement was propaganda vs. reality and how much of it used the ideas of scientific management from the late 1800s/early 1900s?

session平替

<small><cite class='h-cite via'>ᔥ <span class='p-author h-card'>John Mount</span> in Good Stationery as a Tool of Thought | MZLabs (<time class='dt-published'>11/30/2022 13:11:31</time>)</cite></small>

Read 2022-12-31

Cleaned up quote:

I think one of the [the] things that really separates us from the high primates is that [uh] we're tool builders. And I read a [uh] study that measured the efficiency of locomotion for various species on the planet. The Condor used the least energy to move a kilometer and [uh] humans came in with a rather unimpressive showing about a third of the way down the list. It was not [not] too proud of a showing for the crown of creation. So [uh] that didn't look so good, but then somebody at Scientific American had the insight to test the efficiency of locomotion for a man on a bicycle. And a man on a bicycle or human on a bicycle blew the Condor away—completely off the top of the charts and that's what a computer is to me. [uh] What a computer is to me is: it's the most remarkable tool that we've ever come up with and it's the equivalent of a bicycle for our minds.<br /> —Steve Jobs in Memory & Imagination: New Pathways to the Library of Congress. Documentary. Krainin Productions, 1990.

Snippet from full documentary: https://www.youtube.com/watch?v=ob_GX50Za6c

Earl Pomeroy suggests that Paxson's note taking method freed his mind to better reflect and appraise his work. This allows a greater efficiency of work, particularly when it comes to easier search and recall as well as the overall process which becomes easier through practice.

Dwyer, Edward J. “File Card Efficiency.” Journal of Reading 26, no. 2 (1982): 171–171.

Ease of use in writing and grading with short assignments by using 4 x 6" index cards in classrooms.

This sounds like some of the articles from 1912 and 1917 about efficiency of card indexes for teaching.

I'm reminded of some programmed learning texts that were card-based (or really strip-based since they were published in book form) in the 1960s and 1970s. Thse books had small strips with lessons or questions on the front with the answers on the reverse. One would read in strips through the book from front to back and then start the book all over again on page one on the second row of strips and so on.

As is common in the tradition of the zettelkasten, Goutor advises "that each note-card should contain only one item of information, whether a quotation, a summary, or anything else". (p28) He ascribes this requirement to his earlier need for clarity. (cross reference: https://hypothes.is/a/SfWFwENIEe2KfGMbR5n7Qg)

He indicates that while it may seem wasteful to have only one item on each card that the savings in time, efficiency in handling, classification, and retrieval will more than compensate for the small waste.

This sort of small local waste being compensated for by a larger global savings and efficiency can be seen in the design of the shipping container industry as discussed in Mark Levinson's The Box (Princeton University Press, 2008). Was this the exact sort of efficiency mentioned by Ahrens'? (Compare at https://hypothes.is/a/t4i32IXoEeyF2n9jQxu6BA)

In his section on "Arrangement of File", C. Wright Mills describes some of the evolution of his "file". Knowing that the form and function of one's notes may change over time (Luhmann's certainly changed over time too, a fact which is underlined by his having created a separate ZK II) one should take some comfort and solace that theirs certainly will as well.

The system designer might also consider the variety of shapes and forms to potentially create a better long term design of their (or others') system(s) for their ultimate needs and use cases. How can one avoid constant change, constant rearrangement, which takes work? How can one minimize the amount of work that goes into creating their system?

The individual knowledge worker or researcher should have some idea about the various user interfaces and potential arrangements that are available to them before choosing a tool or system for maintaining their work. What are the affordances they might be looking for? What will minimize their overall work, particularly on a lifetime project?

https://web.archive.org/web/20120122115952/http://pileofindexcards.org/blog/2006/10/13/one-pocket-rule/

Noguchi Yukio had a "one pocket rule" which they first described in “「超」整理法 (cho seiri ho)”. The broad idea was to store everything in one place as a means of saving time by not needing to search in multiple repositories for the thing you were hunting for. Despite this advice the Noguchi Filing System didn't take complete advantage of this as one would likely have both a "home" and an "office" system, thus creating two pockets, a problem that exists in an analog world, but which can be mitigated in a digital one.

The one pocket rule can be seen in the IndieWeb principles of owning all your own data on your own website and syndicating out from there. Your single website has the entire store of all your material which makes search much easier. You don't need to recall which platform (Twitter, Facebook, Instagram, et al.) you posted something on, you can save time and find the thing much more quickly by searching one place.

This principle also applies to zettelkasten and commonplace books (well indexed), which allow you to find the data or information you put into them quickly and easily.

Hans Monderman (19 November 1945 – 7 January 2008) was a Dutch road traffic engineer and innovator.

https://en.wikipedia.org/wiki/Hans_Monderman

Suggested by Jerry Michalski: https://app.thebrain.com/brains/3d80058c-14d8-5361-0b61-a061f89baf87/thoughts/bd9c210a-ac8a-0e34-b309-f62e61e72778/attachments/724c3cbf-7aba-4ac7-5b1a-392125168c09

increasing service level efficiency can play a major role in reducing upstream energy demands.

This chapter is too entailed with productivity advice, which can be useful to some, but isn't as note taking focused for those who probably need more of that.

What is the differentiator between knowledge workers, knowledge creators, students, researchers, academics. How do we even clearly delineate knowledge worker as a concept. It feels far too nebulous which makes it more difficult to differentiate systems for them to use for improving productivity and efficiency.

The way that Tiago Forte overlaps the idea of C.O.D.E. (capture/collect, organize, distill, express) with the divergence/convergence model points out some primary differences of his system and that of some of the more refined methods of maintaining a zettelkasten.

<small>Overlapping ideas of C.O.D.E. and divergence/convergence from Tiago Forte's book Building a Second Brain (Atria Books, 2022) </small>

Forte's focus on organizing is dedicated solely on to putting things into folders, which is a light touch way of indexing them. However it only indexes them on one axis—that of the folder into which they're being placed. This precludes them from being indexed on a variety of other axes from the start to other places where they might also be used in the future. His method requires more additional work and effort to revisit and re-arrange (move them into other folders) or index them later.

Most historical commonplacing and zettelkasten techniques place a heavier emphasis on indexing pieces as they're collected.

Commonplacing creates more work on the user between organizing and distilling because they're more dependent on their memory of the user or depending on the regular re-reading and revisiting of pieces one may have a memory of existence. Most commonplacing methods (particularly the older historic forms of collecting and excerpting sententiae) also doesn't focus or rely on one writing out their own ideas in larger form as one goes along, so generally here there is a larger amount of work at the expression stage.

Zettelkasten techniques as imagined by Luhmann and Ahrens smooth the process between organization and distillation by creating tacit links between ideas. This additional piece of the process makes distillation far easier because the linking work has been done along the way, so one only need edit out ideas that don't add to the overall argument or piece. All that remains is light editing.

Ahrens' instantiation of the method also focuses on writing out and summarizing other's ideas in one's own words for later convenient reuse. This idea is also seen in Bruce Ballenger's The Curious Researcher as a means of both sensemaking and reuse, though none of the organizational indexing or idea linking seem to be found there.

This also fits into the diamond shape that Forte provides as the height along the vertical can stand in as a proxy for the equivalent amount of work that is required during the overall process.

This shape could be reframed for a refined zettelkasten method as an indication of work

Forte's diamond shape provided gives a visual representation of the overall process of the divergence and convergence.

But what if we change that shape to indicate the amount of work that is required along the steps of the process?!

Here, we might expect the diamond to relatively accurately reflect the amounts of work along the path.

If this is the case, then what might the relative workload look like for a refined zettelkasten? First we'll need to move the express portion between capture and organize where it more naturally sits, at least in Ahren's instantiation of the method. While this does take a discrete small amount of work and time for the note taker, it pays off in the long run as one intends from the start to reuse this work. It also pays further dividends as it dramatically increases one's understanding of the material that is being collected, particularly when conjoined to the organization portion which actively links this knowledge into one's broader world view based on their notes. For the moment, we'll neglect the benefits of comparison of conjoined ideas which may reveal flaws in our thinking and reasoning or the benefits of new questions and ideas which may arise from this juxtaposition.

This sketch could be refined a bit, but overall it shows that frontloading the work has the effect of dramatically increasing the efficiency and productivity for a particular piece of work.

Note that when compounded over a lifetime's work, this diagram also neglects the productivity increase over being able to revisit old work and re-using it for multiple different types of work or projects where there is potential overlap, not to mention the combinatorial possibilities.

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It could be useful to better and more carefully plot out the amounts of time, work/effort for these methods (based on practical experience) and then regraph the resulting power inputs against each other to come up with a better picture of the efficiency gains.

Is some of the reason that people are against zettelkasten methods that they don't see the immediate gains in return for the upfront work, and thus abandon the process? Is this a form of misinterpreted-effort hypothesis at work? It can also be compounded at not being able to see the compounding effects of the upfront work.

What does research indicate about how people are able to predict compounding effects over time in areas like money/finance? What might this indicate here? Humans definitely have issues seeing and reacting to probabilities in this same manner, so one might expect the same intellectual blindness based on system 1 vs. system 2.

Given that indexing things, especially digitally, requires so little work and effort upfront, it should be done at the time of collection.

I'll admit that it only took a moment to read this highlighted sentence and look at the related diagram, but the amount of material I was able to draw out of it by reframing it, thinking about it, having my own thoughts and ideas against it, and then innovating based upon it was incredibly fruitful in terms of better differentiating amongst a variety of note taking and sense making frameworks.

For me, this is a great example of what reading with a pen in hand, rephrasing, extending, and linking to other ideas can accomplish.

Will this conference debate rebound effects of efficiency? If not, it will not have the desirable net effect.

My linked In comments were:

Alessandro Blasi, will this conference address the rebound effect? In particular, Brockway et al. have done a 2021 meta-analysis of 33 research papers on rebound effects of energy efficiency efforts and conclude:

"...economy-wide rebound effects may erode more than half of the expected energy savings from improved energy efficiency. We also find that many of the mechanisms driving rebound effects are overlooked by integrated assessment and global energy models. We therefore conclude that global energy scenarios may underestimate the future rate of growth of global energy demand."

https://www.sciencedirect.com/science/article/pii/S1364032121000769?via%3Dihub

Unless psychological and sociological interventions are applied along with energy efficiency to mitigate rebound effects, you will likely and ironically lose huge efficiencies in the entire efficiency intervention itself.

Also, as brought up by other commentators, there is a difference between efficiency and degrowth. Intelligent degrowth may work, especially applied to carbon intensive areas of the economy and can be offset by high growth in low carbon areas of the economy.

Vaclav Smil is pessimistic about a green energy revolution replacing fossil fuels https://www.ft.com/content/71072c77-53b3-4efd-92ae-c92dc02f09ad, which opens up the door to serious consideration of degrowth, not just efficiency improvements. Perhaps the answer is in a combination of all of the above, including targeted degrowth.

Technology moves quickly and unexpectedly. At the time of Smil's book release, there was no low carbon cement. Now there is a promising breakthrough: https://www.cnbc.com/2022/04/28/carbon-free-cement-breakthrough-dcvc-put-55-million-into-brimstone.html

As researchers around the globe work feverishly to make low carbon breakthroughs, there is obviously no guarantee of when they will occur. In that case then, with only a few years to peak, it would seem the lowest risk pathway would be to prioritize the precautionary principle over a gambling pathway (such as relying on Negative Emissions Technology breakthroughs) and perhaps consider along with rebound effect conditioned efficiency improvements also include a strategy of at least trialing a temporary, intentional degrowth of high carbon industries / growth of low carbon industries.

Experts have more practiced levels of visual perception of surroundings that provide them with information more quickly than novices who don't yet know what or where to focus their attention. Teaching with eye tracking technology might help to bridge the gap between novice and expert more quickly.

Systems that are too efficient will become brittle. Brittle systems collapse catastrophically when conditions vary too far from expectations. The only way to accommodate unforeseeable circumstances is to give up some efficiency for greater flexibility. This produces robust systems that endure where brittle systems collapse.

Much as coaches help their athletes become better, teachers are there to help students use their time and work efforts in the most effective ways.

Streamlining one's entire workflow from start to finish can unleash tremendous amounts of additional system-wide productivity. Starting out by tinkering with small things here and there is more likely to doom these smaller individual changes to failure with out associated global changes.

Once the overall system has been redesigned and reconfigured, then one can make and perfect smaller scale local changes.

Link this to the idea of kelp and sailing/rowing from The West Wing.

Let's be honest that there are certainly methods for doing all of this within our brains and not needing to rely on external structures. This being said, using writing, literacy, and external structures does allow us to process things faster than before.

Can we calculate what the level of greater efficiency allows for doing this? What is the overall throughput difference in being able to forget and write? Not rely on communication with others? What does a back of the envelope calculation for this look like?

Technology, the body, physical space, and social interaction can be extensions of the mind.

What others might exist? Examples?

New technologies don't always have the user interface to make them better than old methods.

Sometime in the past six months I ran across a description of how migrant workers do this sort of activity in farming contexts. That article also pointed out the fact that the average person couldn't do this sort of work and that there was extreme value in it.

This is the problem however. We can't program humans out of the equation entirely, for what is the general enterprise meant for in the first place?

Reminder to go back and read this.

[[Frederick Winslow Taylor]]

Clark, C. (2021). The Blame Efficiency Hypothesis: An Evolutionary Framework to Resolve Rationalist and Intuitionist Theories of Moral Condemnation.

Salvador, C. E., Berg, M. K., Yu, Q., San Martin, A., & Kitayama, S. (2020). Relational Mobility Predicts Faster Spread of COVID-19: A 39-Country Study. Psychological Science, 31(10), 1236–1244. https://doi.org/10.1177/0956797620958118

Park, J. J. H., Grais, R. F., Taljaard, M., Nakimuli-Mpungu, E., Jehan, F., Nachega, J. B., Ford, N., Xavier, D., Kengne, A. P., Ashorn, P., Socias, M. E., Bhutta, Z. A., & Mills, E. J. (2021). Urgently seeking efficiency and sustainability of clinical trials in global health. The Lancet Global Health, 9(5), e681–e690. https://doi.org/10.1016/S2214-109X(20)30539-8

“Still Using a Cloth Mask? Upgrade to an N95 or P100!” Accessed February 28, 2021. https://www.microcovid.org/blog/masks.

Nuijten, M. B. (2020). Efficient Scientific Self-Correction in Times of Crisis. PsyArXiv. https://doi.org/10.31234/osf.io/9hc8z