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Synthesizer for thought - thesephist.com
Synthesizer for thought - thesephist.com
Draws parallels between the evolution of music production through synthesizers and the potential for new tools in language and idea generation. The author argues that breakthroughs in mathematical understanding of media lead to new creative tools and interfaces, suggesting that recent advancements in language models could revolutionize how we interact with and manipulate ideas and text.
A synthesizer produces music very differently than an acoustic instrument. It produces music at the lowest level of abstraction, as mathematical models of sound waves.
Once we started understanding writing as a mathematical object, our vocabulary for talking about ideas expanded in depth and precision.
An idea is composed of concepts in a vector space of features, and a vector space is a kind of marvelous mathematical object that we can write theorems and prove things about and deeply and fundamentally understand.
Synthesizers enabled entirely new sounds and genres of music, like electronic pop and techno. These new sounds were easier to discover and share because new sounds didn’t require designing entirely new instruments. The synthesizer organizes the space of sound into a tangible human interface, and as we discover new sounds, we could share it with others as numbers and digital files, as the mathematical objects they’ve always been.
Because synthesizers are electronic, unlike traditional instruments, we can attach arbitrary human interfaces to it. This dramatically expands the design space of how humans can interact with music. Synthesizers can be connected to keyboards, sequencers, drum machines, touchscreens for continuous control, displays for visual feedback, and of course, software interfaces for automation and endlessly dynamic user interfaces. With this, we freed the production of music from any particular physical form.
Recently, we’ve seen neural networks learn detailed mathematical models of language that seem to make sense to humans. And with a breakthrough in mathematical understanding of a medium, come new tools that enable new creative forms and allow us to tackle new problems.
Heatmaps can be particularly useful for analyzing large corpora or very long documents, making it easier to pinpoint areas of interest or relevance at a glance.
If we apply the same idea to the experience of reading long-form writing, it may look like this. Imagine opening a story on your phone and swiping in from the scrollbar edge to reveal a vertical spectrogram, each “frequency” of the spectrogram representing the prominence of different concepts like sentiment or narrative tension varying over time. Scrubbing over a particular feature “column” could expand it to tell you what the feature is, and which part of the text that feature most correlates with.
What would a semantic diff view for text look like? Perhaps when I edit text, I’d be able to hover over a control for a particular style or concept feature like “Narrative voice” or “Figurative language”, and my highlighted passage would fan out the options like playing cards in a deck to reveal other “adjacent” sentences I could choose instead. Or, if that involves too much reading, each word could simply be highlighted to indicate whether that word would be more or less likely to appear in a sentence that was more “narrative” or more “figurative” — a kind of highlight-based indicator for the direction of a semantic edit.
Browsing through these icons felt as if we were inventing a new kind of word, or a new notation for visual concepts mediated by neural networks. This could allow us to communicate about abstract concepts and patterns found in the wild that may not correspond to any word in our dictionary today.
What visual and sensory tricks can we use to coax our visual-perceptual systems to understand and manipulate objects in higher dimensions? One way to solve this problem may involve inventing new notation, whether as literal iconic representations of visual ideas or as some more abstract system of symbols.
Photographers buy and sell filters, and cinematographers share and download LUTs to emulate specific color grading styles. If we squint, we can also imagine software developers and their package repositories like NPM to be something similar — a global, shared resource of abstractions anyone can download and incorporate into their work instantly. No such thing exists for thinking and writing. As we figure out ways to extract elements of writing style from language models, we may be able to build a similar kind of shared library for linguistic features anyone can download and apply to their thinking and writing. A catalogue of narrative voice, speaking tone, or flavor of figurative language sampled from the wild or hand-engineered from raw neural network features and shared for everyone else to use.
We’re starting to see something like this already. Today, when users interact with conversational language models like ChatGPT, they may instruct, “Explain this to me like Richard Feynman.” In that interaction, they’re invoking some style the model has learned during its training. Users today may share these prompts, which we can think of as “writing filters”, with their friends and coworkers. This kind of an interaction becomes much more powerful in the space of interpretable features, because features can be combined together much more cleanly than textual instructions in prompts.
·thesephist.com·
Synthesizer for thought - thesephist.com
Timeful Texts
Timeful Texts
Consider texts like the Bible and the Analects of Confucius. People integrate ideas from those books into their lives over time—but not because authors designed them that way. Those books work because they’re surrounded by rich cultural activity. Weekly sermons and communities of practice keep ideas fresh in readers’ minds and facilitate ongoing connections to lived experiences. This is a powerful approach for powerful texts, requiring extensive investment from readers and organizers. We can’t build cathedrals for every book. Sophisticated readers adopt similar methods to study less exalted texts, but most people lack the necessary skills, drive, and cultural contexts. How might we design texts to more widely enable such practices?
spaced repetition is just one approach for writing timeful texts. What other powerful tools might it be possible to create, making future books into artifacts that transcend their pages, as they slowly help readers shape their lives?
·numinous.productions·
Timeful Texts
Future-proofing Your Knowledge in the Age of Information Overload
Future-proofing Your Knowledge in the Age of Information Overload

Reason for using Obsidian: > In the age of information overload and increasing censorship, it is crucial to future-proof your knowledge by creating a personal memex or knowledge management system. A memex, as envisioned by Vannevar Bush, is a device that stores and retrieves vast amounts of information, supplementing human memory. By building a digital memex, you can own your data, access it offline, quickly capture information, sync across devices, and easily search and interconnect knowledge. This system enhances working memory, reduces cognitive overload, and allows you to monetize what you know in the knowledge economy. Obsidian, an open-source application, is an ideal tool for creating a personal knowledge management system due to its flexibility, bi-directional linking, and integrations with other productivity apps.

A memex is a hypothetical device described by Vannevar Bush in his 1945 article “As We May Think”. It stands for "memory extension" and is considered a precursor to the concept of hypertext and the World Wide Web. The memex was envisioned as a mechanical device that could store and retrieve vast amounts of information by interconnecting documents, books, communications, records, annotations, and personal notes. It aimed to supplement human memory and facilitate information organization and retrieval.
All information should be easily searchable and interconnected to optimize resurfacing of knowledge with “exceeding speed and flexibility”.
Because of the information overload we experience every day in the digital world, we tend to forget where to find information we encountered even within the same day of seeing it. This is a problem everyone experiences to varying degrees.
Building a PKM system allows you to outsource valuable information into a centralized location, reducing cognitive overload.
Generating the notes in Markdown makes them future-proof. Even if Obsidian dies and for some reason you can no longer download the application, you’ll still be able to read, write and edit your notes with literally any computer.
·thereversion.co·
Future-proofing Your Knowledge in the Age of Information Overload
How tweet threads cured my writer's block: Twitter as a medium for sketching
How tweet threads cured my writer's block: Twitter as a medium for sketching
witter’s main constraint is encouraging concision. It’s hard to dwell on word choice when you have so little space to work with. Twitter’s conversational tone also helps here—I can just write like I talk, and any fancy words would seem out of place. And of course, I can’t tweak fonts and margins, which cuts off a distraction vector.
each idea has to be wrapped in a little atomic package. I find this helpful for figuring out the boundaries between my thoughts and clarifying the discrete units of an argument.
a thread is linear! No indenting allowed. This forces a brisk straightline through the argument, instead of getting mired in the fine points of the sub-sub-sub-arguments of the first idea.
I think Twitter is useless for persuading a skeptical reader; there’s simply not space for providing enough detail and context.
I prefer to use Twitter as a way to workshop ideas with sympathetic parties who already have enough context to share my excitement about the ideas.
Overall, it seems that we want constraints that help keep us on track with fluid thought, but don’t rule out too many interesting possibilities. Considering both of these criteria together is a subtle balancing act, and I don’t see easy answers.
low barrier to finishing. On Twitter, a single sentence is a completely acceptable unit of publication. Anything beyond that is sort of a bonus. In contrast, most of my blog posts go unpublished because I fear they’re not complete, or not good enough in some dimension. These unpublished drafts are obviously far more complete than a single tweet, but because they’re on a blog, they don’t feel “done,” and it’s hard to overcome the fear of sharing.
This seems like a crucial part of sketching tools: when you make a sketch, it should be understood that your idea is immature, and feel safe to share it in that state. There’s a time and a place for polished, deeply thorough artifacts… and it’s not Twitter! Everyone knows you just did a quick sketch.
I believe that quantity leads to quality. The students who make more pots in ceramics class improve faster than the students who obsess over making a single perfect pot. A tool with a built-in low barrier to finishing makes it easier to overcome the fear, do more work, and share it at an earlier stage.
For me, Twitter does an oddly good job at simulating the thrilling creative energy of a whiteboarding session. People pop in and out of the conversation offering insights; trees and sub-trees form riffing off of earlier points.
I’m curious to think more about the constraints/freedoms afforded by different kinds of creative tools, and whether we could get more clever with those constraints to enable new kinds of sketching. I’m especially curious about kinds of sketching which are only possible thanks to computers, and couldn’t have been done with paper and pen.
·geoffreylitt.com·
How tweet threads cured my writer's block: Twitter as a medium for sketching
Build tools around workflows, not workflows around tools | thesephist.com
Build tools around workflows, not workflows around tools | thesephist.com
Building your own productivity tools that conform to your unique workflows and mental models is more effective than using mass-market tools and bending your workflows to fit them
My biggest benefit from writing my own tool set is that I can build the tools that exactly conform to my workflows, rather than constructing my workflows around the tools available to me. This means the tools can truly be an extension of the way my brain thinks and organizes information about the world around me.
I think it’s easy to underestimate the extent to which our tools can constrain our thinking, if the way they work goes against the way we work. Conversely, great tools that parallel our minds can multiply our creativity and productivity, by removing the invisible friction of translating between our mental models and the models around which the tools are built.
I don’t think everyone needs to go out and build their own productivity tools from the ground-up. But I do think that it’s important to think of the tools you use to organize your life as extensions of your mind and yourself, rather than trivial utilities to fill the gaps in your life.
·thesephist.com·
Build tools around workflows, not workflows around tools | thesephist.com
Muse retrospective by Adam Wiggins
Muse retrospective by Adam Wiggins
  • Wiggins focused on storytelling and brand-building for Muse, achieving early success with an email newsletter, which helped engage potential users and refine the product's value proposition.
  • Muse aspired to a "small giants" business model, emphasizing quality, autonomy, and a healthy work environment over rapid growth. They sought to avoid additional funding rounds by charging a prosumer price early on.
  • Short demo videos on Twitter showcasing the app in action proved to be the most effective method for attracting new users.
Muse as a brand and a product represented something aspirational. People want to be deeper thinkers, to be more strategic, and to use cool, status-quo challenging software made by small passionate teams. These kinds of aspirations are easier to indulge in times of plenty. But once you're getting laid off from your high-paying tech job, or struggling to raise your next financing round, or scrambling to protect your kids' college fund from runaway inflation and uncertain markets... I guess you don't have time to be excited about cool demos on Twitter and thoughtful podcasts on product design.
I’d speculate that another factor is the half-life of cool new productivity software. Evernote, Slack, Notion, Roam, Craft, and many others seem to get pretty far on community excitement for their first few years. After that, I think you have to be left with software that serves a deep and hard-to-replace purpose in people’s lives. Muse got there for a few thousand people, but the economics of prosumer software means that just isn’t enough. You need tens of thousands, hundreds of thousands, to make the cost of development sustainable.
We envisioned Muse as the perfect combination of the freeform elements of a whiteboard, the structured text-heavy style of Notion or Google Docs, and the sense of place you get from a “virtual office” ala group chat. As a way to asynchronously trade ideas and inspiration, sketch out project ideas, and explore possibilities, the multiplayer Muse experience is, in my honest opinion, unparalleled for small creative teams working remotely.
But friction began almost immediately. The team lead or organizer was usually the one bringing Muse to the team, and they were already a fan of its approach. But the other team members are generally a little annoyed to have to learn any new tool, and Muse’s steeper learning curve only made that worse. Those team members would push the problem back to the team lead, treating them as customer support (rather than contacting us directly for help). The team lead often felt like too much of the burden of pushing Muse adoption was on their shoulders. This was in addition to the obvious product gaps, like: no support for the web or Windows; minimal or no integration with other key tools like Notion and Google Docs; and no permissions or support for multiple workspaces. Had we raised $10M back during the cash party of 2020–2021, we could have hired the 15+ person team that would have been necessary to build all of that. But with only seven people (we had added two more people to the team in 2021–2022), it just wasn’t feasible.
We neither focused on a particular vertical (academics, designers, authors...) or a narrow use case (PDF reading/annotation, collaborative whiteboarding, design sketching...). That meant we were always spread pretty thin in terms of feature development, and marketing was difficult even over and above the problem of explaining canvas software and digital thinking tools.
being general-purpose was in its blood from birth. Part of it was maker's hubris: don't we always dream of general-purpose tools that will be everything to everyone? And part of it was that it's truly the case that Muse excels at the ability to combine together so many different related knowledge tasks and media types into a single, minimal, powerful canvas. Not sure what I would do differently here, even with the benefit of hindsight.
Muse built a lot of its reputation on being principled, but we were maybe too cautious to do the mercenary things that help you succeed. A good example here is asking users for ratings; I felt like this was not to user benefit and distracting when the user is trying to use your app. Our App Store rating was on the low side (~3.9 stars) for most of our existence. When we finally added the standard prompt-for-rating dialog, it instantly shot up to ~4.7 stars. This was a small example of being too principled about doing good for the user, and not thinking about what would benefit our business.
Growing the team slowly was a delight. At several previous ventures, I've onboard people in the hiring-is-job-one environment of a growth startup. At Muse, we started with three founders and then hired roughly one person per year. This was absolutely fantastic for being able to really take our time to find the perfect person for the role, and then for that person to have tons of time to onboard and find their footing on the team before anyone new showed up. The resulting team was the best I've ever worked on, with minimal deadweight or emotional baggage.
ultimately your product does have to have some web presence. My biggest regret is not building a simple share-to-web function early on, which could have created some virality and a great deal of utility for users as well.
In terms of development speed, quality of the resulting product, hardware integration, and a million other things: native app development wins.
After decades working in product development, being on the marketing/brand/growth/storytelling side was a huge personal challenge for me. But I feel like I managed to grow into the role and find my own approach (podcasting, demo videos, etc) to create a beacon to attract potential customers to our product.
when it comes time for an individual or a team to sit down and sketch out the beginnings of a new business, a new book, a new piece of art—this almost never happens at a computer. Or if it does, it’s a cobbled-together collection of tools like Google Docs and Zoom which aren’t really made for this critical part of the creative lifecycle.
any given business will find a small number of highly-effective channels, and the rest don't matter. For Heroku, that was attending developer conferences and getting blog posts on Hacker News. For another business it might be YouTube influencer sponsorships and print ads in a niche magazine. So I set about systematically testing many channels.
·adamwiggins.com·
Muse retrospective by Adam Wiggins
How can we develop transformative tools for thought?
How can we develop transformative tools for thought?
a more powerful aim is to develop a new medium for thought. A medium such as, say, Adobe Illustrator is essentially different from any of the individual tools Illustrator contains. Such a medium creates a powerful immersive context, a context in which the user can have new kinds of thought, thoughts that were formerly impossible for them. Speaking loosely, the range of expressive thoughts possible in such a medium is an emergent property of the elementary objects and actions in that medium. If those are well chosen, the medium expands the possible range of human thought.
Memory systems make memory into a choice, rather than an event left up to chance: This changes the relationship to what we're learning, reduces worry, and frees up attention to focus on other kinds of learning, including conceptual, problem-solving, and creative.
Memory systems can be used to build genuine conceptual understanding, not just learn facts: In Quantum Country we achieve this in part through the aspiration to virtuoso card writing, and in part through a narrative embedding of spaced repetition that gradually builds context and understanding.
Mnemonic techniques such as memory palaces are great, but not versatile enough to build genuine conceptual understanding: Such techniques are very specialized, and emphasize artificial connections, not the inherent connections present in much conceptual knowledge. The mnemonic techniques are, however, useful for bootstrapping knowledge with an ad hoc structure.
What practices would lead to tools for thought as transformative as Hindu-Arabic numerals? And in what ways does modern design practice and tech industry product practice fall short? To be successful, you need an insight-through-making loop to be operating at full throttle, combining the best of deep research culture with the best of Silicon Valley product culture.
Historically, work on tools for thought has focused principally on cognition; much of the work has been stuck in Spock-space. But it should take emotion as seriously as the best musicians, movie directors, and video game designers. Mnemonic video is a promising vehicle for such explorations, possibly combining both deep emotional connection with the detailed intellectual mastery the mnemonic medium aspires toward.
It's striking to contrast conventional technical books with the possibilities enabled by executable books. You can imagine starting an executable book with, say, quantum teleportation, right on the first page. You'd provide an interface – perhaps a library is imported – that would let users teleport quantum systems immediately. They could experiment with different parts of the quantum teleportation protocol, illustrating immediately the most striking ideas about it. The user wouldn't necessarily understand all that was going on. But they'd begin to internalize an accurate picture of the meaning of teleportation. And over time, at leisure, the author could unpack some of what might a priori seem to be the drier details. Except by that point the reader will be bought into those details, and they won't be so dry
Aspiring to canonicity, one fun project would be to take the most recent IPCC climate assessment report (perhaps starting with a small part), and develop a version which is executable. Instead of a report full of assertions and references, you'd have a live climate model – actually, many interrelated models – for people to explore. If it was good enough, people would teach classes from it; if it was really superb, not only would they teach classes from it, it could perhaps become the creative working environment for many climate scientists.
In serious mediums, there's a notion of canonical media. By this, we mean instances of the medium that expand its range, and set a new standard widely known amongst creators in that medium. For instance, Citizen Kane, The Godfather, and 2001 all expanded the range of film, and inspired later film makers. It's also true in new media. YouTubers like Grant Sanderson have created canonical videos: they expand the range of what people think is possible in the video form. And something like the Feynman Lectures on Physics does it for textbooks. In each case one gets the sense of people deeply committed to what they're doing. In many of his lectures it's obvious that Feynman isn't just educating: he's reporting the results of a lifelong personal obsession with understanding how the world works. It's thrilling, and it expands the form.
There's a general principle here: good tools for thought arise mostly as a byproduct of doing original work on serious problems.
Game companies develop many genuinely new interface ideas. This perhaps seems surprising, since you'd expect such interface ideas to also suffer from the public goods problem: game designers need to invest enormous effort to develop those interface ideas, and they are often immediately copied (and improved on) by other companies, at little cost. In that sense, they are public goods, and enrich the entire video game ecosystem.
Many video games make most of their money from the first few months of sales. While other companies can (and do) come in and copy or riff on any new ideas, it often does little to affect revenue from the original game, which has already made most of its money In fact, cloning is a real issue in gaming, especially in very technically simple games. An example is the game Threes, which took the developers more than a year to make. Much of that time was spent developing beautiful new interface ideas. The resulting game was so simple that clones and near-clones began appearing within days. One near clone, a game called 2048, sparked a mini-craze, and became far more successful than Threes. At the other extreme, some game companies prolong the revenue-generating lifetime of their games with re-releases, long-lived online versions, and so on. This is particularly common for capital-intensive AAA games, such as the Grand Theft Auto series. In such cases the business model relies less on clever new ideas, and more on improved artwork (for re-release), network effects (for online versions), and branding. . While this copying is no doubt irritating for the companies being copied, it's still worth it for them to make the up-front investment.
in gaming, clever new interface ideas can be distinguishing features which become a game's primary advantage in the marketplace. Indeed, new interface ideas may even help games become classics – consider the many original (at the time) ideas in games ranging from Space Invaders to Wolfenstein 3D to Braid to Monument Valley. As a result, rather than underinvesting, many companies make sizeable investments in developing new interface ideas, even though they then become public goods. In this way the video game industry has largely solved the public goods problems.
It's encouraging that the video game industry can make inroads on the public goods problem. Is there a solution for tools for thought? Unfortunately, the novelty-based short-term revenue approach of the game industry doesn't work. You want people to really master the best new tools for thought, developing virtuoso skill, not spend a few dozen hours (as with most games) getting pretty good, and then moving onto something new.
Adobe shares in common with many other software companies that much of their patenting is defensive: they patent ideas so patent trolls cannot sue them for similar ideas. The situation is almost exactly the reverse of what you'd like. Innovative companies can easily be attacked by patent trolls who have made broad and often rather vague claims in a huge portfolio of patents, none of which they've worked out in much detail. But when the innovative companies develop (at much greater cost) and ship a genuinely good new idea, others can often copy the essential core of that idea, while varying it enough to plausibly evade any patent. The patent system is not protecting the right things.
many of the most fundamental and powerful tools for thought do suffer the public goods problem. And that means tech companies focus elsewhere; it means many imaginative and ambitious people decide to focus elsewhere; it means we haven't developed the powerful practices needed to do work in the area, and a result the field is still in a pre-disciplinary stage. The result, ultimately, is that it means the most fundamental and powerful tools for thought are undersupplied.
Culturally, tech is dominated by an engineering, goal-driven mindset. It's much easier to set KPIs, evaluate OKRs, and manage deliverables, when you have a very specific end-goal in mind. And so it's perhaps not surprising that tech culture is much more sympathetic to AGI and BCI as overall programs of work. But historically it's not the case that humanity's biggest breakthroughs have come about in this goal-driven way. The creation of language – the ur tool for thought – is perhaps the most important occurrence of humanity's existence. And although the origin of language is hotly debated and uncertain, it seems extremely unlikely to have been the result of a goal-driven process. It's amusing to try imagining some prehistoric quarterly OKRs leading to the development of language. What sort of goals could one possibly set? Perhaps a quota of new irregular verbs? It's inconceivable!
Even the computer itself came out of an exploration that would be regarded as ridiculously speculative and poorly-defined in tech today. Someone didn't sit down and think “I need to invent the computer”; that's not a thought they had any frame of reference for. Rather, pioneers such as Alan Turing and Alonzo Church were exploring extremely basic and fundamental (and seemingly esoteric) questions about logic, mathematics, and the nature of what is provable. Out of those explorations the idea of a computer emerged, after many years; it was a discovered concept, not a goal.
Fundamental, open-ended questions seem to be at least as good a source of breakthroughs as goals, no matter how ambitious. This is difficult to imagine or convince others of in Silicon Valley's goal-driven culture. Indeed, we ourselves feel the attraction of a goal-driven culture. But empirically open-ended exploration can be just as, or more successful.
There's a lot of work on tools for thought that takes the form of toys, or “educational” environments. Tools for writing that aren't used by actual writers. Tools for mathematics that aren't used by actual mathematicians. And so on. Even though the creators of such tools have good intentions, it's difficult not to be suspicious of this pattern. It's very easy to slip into a cargo cult mode, doing work that seems (say) mathematical, but which actually avoids engagement with the heart of the subject. Often the creators of these toys have not ever done serious original work in the subjects for which they are supposedly building tools. How can they know what needs to be included?
·numinous.productions·
How can we develop transformative tools for thought?