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If all your time is spent watching output tokens, where do your input tokens come from? Letting an agent rip on full auto is basically doom scrolling. Even worse if you're doom scrolling while the agent runs. We humans love frying our dopamine receptors. This feels great until you realize what you were offloading: the struggle. The part where you fail. Failure is the entire point. You don't make progress in the gym unless you take a set at least close to failure. The muscle only adapts when it's forced to. It is no different for the brain. Cognitive Atrophy It is very hard to admit to yourself that your skills have atrophied. It is even harder to admit this to other people. I will admit that over the past several months my brain has gotten smoother (and I wasn't even on Twitter much!). Recently, I had written an abstraction for my diff viewer (diffy), an element system with a macro that lets agents write html-like code in rust for native ui (they reason better with this). But it wasn't adopted everywhere in the repo yet, so when I asked for a new feature, the model decided to hand paint it straight to the viewport instead. Every behavior the element system gives you for free was just... missing. Text wasn't selectable. Hover highlights wouldn't go away. And since I wasn't looking closely, it iterated on the slop and produced more slop, more bugs. I just kept saying continue. I lost a whole day untangling it, and the funny part is that once I actually looked at what it had built, every bug was the same bug. When you hit a roadblock and your immediate reaction is to reach for something else (previously, this used to be other people, but now it is a language model) you are essentially skipping the part where you actually learn to solve the problem. It is funny how one of the best "learning tools" has turned out to be the number one cause (anecdotal. sue me) of the lack of learning! It's been a few months since I started writing this, and things have gotten more dire. Several major software services barely work now, grown engineers I once respected are writing somber posts about missing a language model that was banned for a while. Mourning. For model weights. It's all so dystopian. It didn't work, but boy was it beautiful. As the agents get better, one is basically expected to produce code at an alarming rate. The timeline to get something done is compressed but the time it takes to come up with solutions to hard problems has not. There are usually a few good abstractions one can come up with that balance the upsides and tradeoffs for most software problems. However it is currently trivial to turn your brain off and let the slop flow. The code will be complex. It might look like it all works, but something always breaks. And the solution to that? More slop. Software quality is collapsing as a result, and the societal expectation that engineers understand what they ship is disappearing. You never understood the code in the first place. So when you need to change it, you're asking the same stateless clanker to modify code it has no memory of writing. All output tokens and zero thinking tokens. A lower barrier of entry to write software doesn't imply the standards for good software must be lowered. The culture of doing things because they said you couldn't. The growing trend is to do things because you now can (supposedly), but we used to try and do things because we could not out of sheer stubbornness. Carmack and gang shipped QuakeWorld with client-side prediction over dial-up when the conventional wisdom was that twitch shooters over the internet were unplayable. This only happened because Quake's original netcode was laggy and everyone hated it. (They fixed it in a month.) George Dantzig arrived late to class, mistook two "unsolvable" statistics problems for homework, and solved them. Nobody told him they were impossible, so he just did the work. Andrew Wiles spent seven years alone in his attic working on Fermat's Last Theorem, a problem mathematicians had given up on for 350 years. He announced the proof, a reviewer found a hole in it, and he spent another year fixing that too. Notice that all three of them became who they are because of the struggle, not despite it. The people benefiting most from generative tools today, say Terence Tao or Mitchell Hashimoto, already put in the time, so when they offload work they're just skipping the typing. When people like you and me (if this is not you, then I apologize) offload, we skip the grind itself. With language models, easy tasks got easier, hard tasks stayed hard. The hard part was never the task itself. @codex how do I fix this I don't know, I am figuring this out as I go. The amount of time I have spent actually programming has been dropping month over month this year. I used to have a coding stats section on my website that would track hours I spent writing code split by language, recently I had updated it to this: and it made me quite sad. I do think that sometimes all you need is to realize that the thing you are doing is actually detrimental to your growth. Consistency matters more than one would assume. If you consistently take some time away from these tools and actually use your brain, that alone is already significantly better than offloading your thoughts. Solve the problems yourself. Or at least try, fail, and spend time thinking. There is seemingly no "learning" phase anymore. You are expected to just know things. Learning is fun, don't let anyone take this away from you. I've written about this before. It is probably going to be slow, learning takes time and effort. You will feel stupid (I feel stupid). This is a good feeling, because there exists a world where you are no longer stupid and the path towards it is learning. Books still exist! Libraries are still open, notebooks waiting to be written in. Read more. Write more. But If you really do care about improving yourself, be honest and use these models for what they are, highly efficient filters of zettabytes of data (the internet is estimated to be 175-240 zettabytes (10^{21} bytes)). It was extremely difficult to identify what one needed to read to learn niche topics even like 2 years ago. I remember asking a good friend of mine to recommend material to dive deep into learning about SIMD, and honestly there wasn't much stuff to read except the Intel Intrinsics Guide. And if you've ever taken a look at that, it is quite cancerous for a first-time reader. Language models are super useful here because you can point them at material and you can ask questions that pertain to the thing you care about and it will simply just tell you the correct things. Conclusion One good thing in this age of slop is to consume knowledge at an unbelievable pace. I don't necessarily mean using only model output for learning (I don't trust them to learn any topic more than a shallow amount), but rather using them to help sift through the plethora of information available out there and identifying the right things to read. Human slop exists too and using a language model to supplement your learning might help keep you sane (ironically). I like using these models to write code that I tell it to write (outside of work I enjoy doing it myself entirely), and I am largely disinterested in asking it what I should write. There are exceptions of course, because not everyone is working on scaling software services which has largely been solved (but slowly being forgotten), but that would be for you to decide. The best model you have access to (and it has solved continual learning) is, and always has been, the one inside your skull. It's time to scale up its input tokens.
Glimpse v1.0 Glimpse can now build call graphs, showing you exactly how functions relate to each other in your codebase. Video # what does main call? glimpse code :main # what calls this function? (reverse call graph) glimpse code :process_request --callers # limit the depth glimpse code :build --depth 3 This works by parsing your code with tree-sitter, extracting function definitions and calls, then resolving those calls to their actual definitions. Precise mode Sometimes tree-sitter based resolution isn’t enough. Maybe you’re dealing with dynamic dispatch, generics, or just a language with particularly complex module resolution. For this, Glimpse can use LSPs to resolve definitions semantically. glimpse code :main --precise This spins up actual LSP servers and uses goto-definition / goto-implementation to resolve calls. It’s slower, but accurate. Glimpse will attempt to auto-install the LSP servers for you. Indexing Glimpse eagerly caches whatever it finds into an incremental index. But you can choose to pre-build the index ahead of time for instant queries. # build the index glimpse index build # with LSP for precise resolution glimpse index build --precise # check what you've got glimpse index status The index stores all the definitions, calls, and resolutions so subsequent queries are fast. Language support Glimpse now supports: Go, Rust, C, C++, Python, TypeScript, JavaScript, Zig, Java, Scala, Nix, Lua, Ruby, C#, Kotlin, Swift, and Haskell. Each language has custom tree-sitter queries for extracting definitions, calls, and imports. The grammars are downloaded and compiled automatically on first use. Try it # install cargo install glimpse # or with homebrew brew tap seatedro/glimpse && brew install glimpse # or with nix nix profile install github:seatedro/glimpse # then just glimpse code :main
This is a general devlog covering what I’ve been up to over the past few months! Haskell Hakyll is a Haskell library for generating static websites (yes, you do not, in fact, need Next.js for your personal site). The previous iteration of my website was written with Go + templ, and it was not static. I wrote everything myself, and it was, quite frankly, a horror to maintain. The templ LSP actually hinders more than it helps, and since I did not statically generate the content, it was kind of slow for a personal website. I did not like it. I added some very minor CSS fixes and a theme toggle button for my friend’s new website ludwigabap.com, and I saw the light that is Hakyll. :kneel: So I nerd-sniped myself into rewriting my personal website in Hakyll so that it generates beautiful HTML at build time (it uses Tailwind, too). All the dynamic bits of the website, like my silly stats and coding time, are served from a single Rust Axum server binary on my Hetzner VM that serves other stuff too (Memegrep’s server, among other things). Nix-pill This segues into my next nerd-snipe, or rather, my favorite new pill: the Nix pill. My entire website is built with a single Nix flake, including the Hakyll build step, the Cargo build step, and generating the resulting Docker image. Although, to be honest, the learning curve is very steep and I simply do not have it in me to master this language anytime soon, I like the principles, and it seems to me the least bad build system out there. I do most of my work on a MacBook running a NixOS VM as well. (seatedro/dotnix on GitHub.) It’s so much nicer to have a real dev workflow versus whatever the fuck macOS is. Sorry, but Homebrew is not good software. Ember The reason I started programming was that I was playing a game called Midtown Madness as a wee lad and decided that one day I would build a cool game like that. So, after 15 years, I’ve decided to embark on a small adventure to build a cool physics simulation (and eventually a voxel) engine. It’s written entirely in Zig because I enjoy writing Zig and did not want to touch C++ (although there were times I thought about committing this sin). When Ember gets far enough, I might write separate devlogs, but with what’s written so far, there isn’t enough to justify one. I was knee-deep in the mines because I wanted extremely specific features like multi-viewport docking with ImGui, and the off-the-shelf Zig libraries did not want to ship that for some reason. So there were many adventures in getting this shit to compile neatly. Ember now uses SDL3 for windowing and has an abstract rendering API (rudimentary, but the backends are in place) with SDLRenderer3, OpenGL, and WGPU-native backends that can be neatly switched at comptime. I’m using a bunch of cool resources to learn more about how to do this because I’ve never really written any game-dev related code before. I just want to build some cool simulations, and I will get there no matter what. github / seatedro / ember Thanatos After 5 years, I have finally built a new personal computer. I will be running NixOS as my main operating system with Hyprland and Wayland. I will also have Windows installed on a separate drive mainly for video games, though I expect to use Linux more often. It’s so nice not having to worry about my 256 GB SSD getting filled up on my MacBook Air. :> Exa Also, I joined Exa last month to work on the back-end team, and it has been so fun! I am soaking up as much knowledge from my significantly smarter peers at a good pace. As per custom, I revisited @ludwigABAP’s post: On becoming competitive when joining a new company. (PS: it’s on a new website.) Fin Back to the code cave I go—going to extract the polymorphic.
two-weeks I built a website (twoweeksisallyouneed dot com) with just Claude 3.5 Sonnet, zero lines of code written by me. Why I did this So a couple weeks back I had a computer vision midterm and i was allowed a single page of notes. I decided to use Claude to generate a cheat sheet in LaTeX. It was crazy lol, I was able to cook up something usable in 15 mins. pic.twitter.com/0tvIsdv34d — ro/nin (@seatedro) October 24, 2024 Someone had asked me to make a similar cheatsheet for ML, but I thought why not get claude to make an entire website instead? Early days I didn’t really give claude any specific information except what I wanted to build. My plan was as follows: > build out the UI skeleton first > populate with some dummy data > set up a content pipeline > tie up the ui with the data > fix bugs Claude decided to use react (Shocking). With just a couple of chats I was able to get the retro/hacker/matrix style UI down. (It’s going to be hard for frontend engineers to keep up with AI at this rate) I spent some time building and adding secrets/easter eggs to the website which no one has found yet lmaoooo. If/when all the easter eggs are found, I will open source the repository. Good hunting until then bros. Frustrations Things got really annoying, really fast. As soon as I wanted to build some sort of content pipeline, everything went to shit. Claude, no matter how smart of an AI, is not human. It did not think ahead. If I was going to build out this website I would not have started with a barebones react/vite app. I would have probably gone for a full stack framework like sveltekit instead. Generating content for the website was/is a nightmare. LLMs hallucinate, this is known, but did you also know how incredibly frustrating it is to get them to follow instructions? There were multiple instances where Claude (with all the 40% of project context of javascript code) generated a TypeScript interface and proceeded to spit TypeScript code. This project has 0 TypeScript???? The new edit in place nonsense was getting on my nerves. Half the time the output artifact wouldn’t even change, and the other half it would mess up the changes. I have to mention “please use a new artifact” if I wanted any real usable code. I was enthusiastic about building something with just Claude the first few days, then I started getting weary, and then eventually I wanted to take a sabbatical from using AI. When the project context grows, (think like 20% or more), Claude seems to have a hard time using that information. Often times I found myself hitting send, and Claude would spit some nonsense, I would hit stop and paste any relevant code directly and then get some useful code. Context is probably the biggest annoyance I’ve had with LLMs. Random thoughts Perplexity (with claude 3.5) is great (to an extent) because it’s essentially a RAG search so I was able to get somewhat up to date content for the resources and references sections from it. I feel like I was able to ship something of decent quality for sure, but I lost a lot of brain cells during the process. Do not take away from the programmer the only thing he wishes to do, program. Proompting I didn’t particularly do anything unique to get the best out of my prompts/chats. I did do everything in a Project on claude dot ai though, which let me set Project Instructions like so: BE ENTHUSIASTIC. WE ARE GOING TO CHANGE THE WAY THE WORLD LEARNS WITH THIS WEBSITE🚀🚀🚀🚀 LLMs seem to be much more open to doing anything you ask if you gaslight them, so go ahead and do it. Here are some prompts that I used while building the website: PROMPT ------ This is AWESOME: * For the loading screen add some text that says "you can learn anything in two weeks" * The ascii text is also weird, it says erain? is that supposed to mean something? * Where did all my placeholder topics go? * MOAR scrt scan lines * The matrix rain needs to fall vertically and it should be subtle. On mouse move it should get a bit brighter (the char under the mouse) What else do you think you could add? Surprise me One time I asked Claude to add something and it started changing the existing UI????? PROMPT: ------ OKAY, we have a beautiful boot sequence now. let's flesh out the main content screen. First let's fix some bugs: * The animations restart everytime i move my mouse instead of continue organically * What i mean is, when i move my mouse over the windows or around the matrix rain, the matrix rain restarts and so do the typewriter effect on the window title Work on these * [REDACTED] Easter eggs: * Fun Features: * "Power saving mode" that dims everything except what you're reading ....[REDACTED] So many times I ended up editing the prompt and adding lines like this: PLEASE DON'T CHANGE THE EXISTING UI. IT LOOKS GOOD BRO. I’ll just add some random prompts here PROMPT ------ Broski, we need to make the UI responsive and shit. Lot of people are reporting issues with it on mobile and smaller screens PROMPT ------ what sort of content do u think we should add? i was thinking things like formulae, charts (for phd), code blocks (for eng), research papers, youtube video links, blog posts etc. Let's think out loud how we're gonna do this before we proceed PROMPT ------ `pasted_code.jsx` Here is my current dashboard. Here is some sample concept content i have: `pasted_data.json` I need you to render this beautifully in the dashboard. Make any and all changes needed. It needs to look beautiful. And anything else u feel would be good. List out the things you're adding before adding it okay? Concluding thoughts This was a good experiment, a success. If you have a clear vision for what you want your product to be, then AI can help you achieve that vision quite well! However, I don’t think I will be using AI for the foreseeable future. I feel like my learning is stagnating the more i use AI and I want to write my slop code with my own two hands. I might use avante.nvim to quickly write some duplicated code here and there but by god, I miss coding. Actual coding.
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After a write-up in the New York Times, Mommy Bloggers had two options. Either lean in, or step back. Given how popular it became after that, it's not hard to guess which option they chose. The post Mommy bloggers react appeared first on The History of the Web.
I'm quite a bit late on this one, but Haunt version 0.4.0 was released released back in July. I haven't had much time for blogging, but I'm catching up now! This release contains a small set of improvements and bug fixes since the 0.3.0 release in 2024. About Haunt Haunt is a static site generator that uses the Guile Scheme as its configuration language. It aims to be simple, functional, and extensible. Features include: Easy blog and Atom/RSS feed generation Markdown post support Simple development server for viewing edits before publishing Purely functional build process User extensibility Notable changes Added support for HTML in Markdown documents. This was a long time coming because guile-markdown did not support it and the library was abandoned by the original maintainer. As part of my work at Spritely, we forked it, implemented the relevant portions of the CommonMark specification, and released it. Spritely's guile-commonmark fork is now considered to be the official upstream by Guix and others. A further consequence of this is that guile-lib is now a required dependency for building Haunt as we need the (htmlprag) module to parse Markdown documents with embedded HTML. html->shtml from guile-lib's (htmlprag) module is now used instead of xml->sxml in the HTML reader. It was silly of me to use xml->sxml for this purpose years ago, but at the time I wanted guile-lib to be an optional dependency. Added haunt new subcommand for creating a new site. Added default directory, template, and prefix arguments to flat-pages procedure. Added support for index metadata flag to flat pages for pretty URLs. Flat pages now receive all page metadata, not just the page title. This is a breaking change from 0.3.0. Added .scm as an additional extension for sxml-reader. make-file-extension-matcher now supports multiple extensions. Fixed emission of <script> and <style> elements. Fixed handling of no available reader in flat pages builder. Fixed unreachable error handling clause when a reader is not found for a post. Fixed default blog theme template missing an <html> tag. Fixed overloaded -h option in haunt serve. Deprecated post in Skribe reader in favor of document. Download Haunt 0.4.0 is already available in Guix: guix pull guix install haunt See the Haunt project page for information on how to build from source. Thank you to Camilo Rodrigues, Noé Lopez, jgart, Jakob L. Kreuze, and Daniel Meißner for their contributions to this release! Happy haunting!
This is a transcript from a talk I gave at the German Perl Workshop earlier this year. If you'd prefer to watch the video recording, you can find it here. I have lots of photographic projects on the go. Lots of these being on film, as some of these I started shooting a long time ago. I don’t have any particular loyalty or attraction to film, it’s just that I started shooting many of these projects before affordable medium format digital was available. Since I mostly shoot medium/large format film I never really jumped to digital until recently, so film has continued to feature heavily in my workflow. That said, it’s a pain in the arse to shoot film now given the spiraling costs, limited availability, and issues around traveling with it: modern airport CT scanners, being rolled out across many airports, are much more convenient but will fog film. Asking for a hand inspection often comes down to arbitrary timing - how busy the security is, how experienced the operator is, or if you’re lucky/unlucky. I’ve had film forced to be scanned (and fogged) and politely argued with security on more than one occasion. I don’t want to deal with that so don’t travel with film anymore, thus I am shooting less of it and have mostly moved to digital. I still have a tonne of film I need to scan and process however. Here’s just some of the binders and files of film. I don’t plan to scan all of this, but I do plan to scan the ones I need to. Probably in the region of a couple of thousand frames. I want to scan to the highest possible quality (within reason) for archiving, book projects, and large prints. If you’re wondering how large I print, it can be up to 160x60cm panoramics for selling. This is restricted by the size of my printer (that’s another story). Three Years Ago Three years ago I almost bought a scanner. I ended up blogging about it and the post got a bit of traction on Hacker News (HN). I’m never quite sure which posts I submit will pique the interest of the users. I’ll spend months chipping away at a draft and when I post it it tanks. Or I’ll cobble something together in twenty minutes, like the linked one above, and it gets 440 points and over 300 comments… The thread had some useful suggestions and some not so useful ones, the not so useful ones being effectively “buy an Epson”: I’ve had one for fifteen years and it’s not good enough for large prints or archiving. It’s passable for web stuff and smaller prints, but for my recent use cases? Not even close. Ten years ago I had negatives scanned with a high resolution scanner for the first time and recently, wanting to scan my archives for various projects, I decided I should invest in one of those scanners. The Original Plan The plan, back in 2023, was simple: Buy scanner (at significantly reduced rate) Scan all my film Sell scanner Profit! And I mean profit - the scanner that I almost bought was being offered to me at about 2/3rd of the price they usually sell. And they’re becoming harder to find in working order so the prices are going up. Or profit in not having to pay > 25.- CHF per frame to have someone else do this. You can see the pricing from The Film Lab. You can read the original blog post to find out more about the scanner in question, so I won’t repeat it here. Other than the parts being relevant to the rest of this post, namely that the scanner was showing hard and soft problems. The software that drives the scanner was last updated in 2012, it’s proprietary and closed source, requiring 32bit architecture and no third party drivers or software exist. So you are stuck using old software/computers to run it. Or maybe you could use emulation / virtualisation? The problem there is that the interface is firewire, or SCSI on the even older models, and firewire is known to be problematic on these scanners as the controllers start to go bad after a decade of continued use. That’s a risk, and the scanner was very much EOL as the firewire controller was dying: both ports were bad that suggests controller, not ports. The scanner would have been €5,000 to purchase and then €3,000 (ish) to repair. Or, as HN suggested - just open it up and use a soldering iron. I’m not going to drop 5k on something and then start poking it with a soldering iron. I’ll pass on that thanks. Camera Scanning In the meantime I’ve been camera scanning, which you can read about in another blog post. But how does that compare cost wise? It’s expensive because you’ll need a high resolution camera, a macro lens, copy stand, negative carrier/holder, and quality light source. You’ll look to spend anything from three to five thousand Euros on everything. Camera scanning does actually work well, in that it’s close to a high resolution dedicated scanner. But you have to setup the entire thing every time you want to use it, including ensuring everything is straight and parallel. It also suffers from the same weakness as most other scanning methods. What do you think that is? Film Flatness Or lack thereof: Film is rarely flat, especially so with 35mm. These are pretty mild examples of curl. It tends to be flatter in the larger formats but then you get into flatness issues due to it sagging. The smallest difference in the film plane can cause major issues in sharpness due to focus fall off (film scanning is essentially macro photography). Any workflow or solution that does not take this into account is significantly compromised. And the workflow is only as good as its weakest part. This is the biggest problem in scanning film - all other considerations are more than adequate these days: resolution, dynamic range, etc. However, most negative carriers don’t keep the film perfectly flat. This has always been a problem - this is from a book called “Edge of Darkness” which is about traditional analog photography and printing, and summarises the problems of negative carriers thusly: “if you use a glassless negative carrier, you might as well just buy the cheapest enlarging lens you can find. You are simply throwing away the money and sharpness you paid for it in your enlarging lens, and also in your fine camera and the expensive lenses you bought for it… No film will lie flat in a glassless carrier. That’s right, none… There is no avoiding this issue. Use glass.” So you have to use (anti-newton ring) glass, which introduces other issues - you’ve now got extra glass in the transmission path, and dust (which isn’t a massive problem, but a pain nonetheless). You could use drum scanning, which is absurdly impractical from a cost and operating point of view. Or you could use a Flextight, the scanner I almost bought three years ago. Interim Solution I stuck with camera scanning, but wasn’t happy though, because of film flatness and the setup faff. So of course I started looking for another scanner. I was idly browsing near the end of 2025 and came across this one. It’s exactly the same spec as the one I tried three years ago, except SCSI not Firewire so less prone to failure. It just predates Hasselblad buying Imacon (so is pre the rebranding, etc). It was in Switzerland so I could inspect and pick it up. It was also significantly cheaper than the previous one I had looked at, so worth a punt even if I needed to take a soldering iron to it. We went to St Gallen for a weekend and I picked it up. Here’s the software interface back in my studio. Look at that marvelous interface! None of that liquid glass bollocks. The first scans were promising, but I had the sense things needed some TLC. The first thing was calibrating the focus, which the software can do in combination with a focus slide. I was lucky that the focus slide was included with the scanner and I’m not sure what I would have done otherwise. Probably paid a fortune for a replacement? Possibly a lot of manual trial and error with the software? After doing that I scanned images of the 1951 USAF resolution test chart (taken on ultra high resolution 35mm film): That’s what the resulting scan looked like. Notice that it’s sharp from edge to edge, corner to corner. At 100% crop we can resolve around 110 to 123 line pairs per mm, which equates to about 5,600 to 6,300 DPI. This is beyond the limit of most 35mm lenses, but importantly - exactly to spec for this scanner. So I was happy the focus was calibrated. If you’re curious this is the same target with the camera scanning setup. It’s close, but we’ve got another variable in the workflow, several even, and that impacts the results. It’s not as sharp, and the extra glass in the transmission path causes aberrations. Another thing that needed attention was the power supply. The seller mentioned that “sometimes it takes five minutes to warm up”. Sometimes it was more than five minutes, and the power supply would click click click away. So that needed fixing and it was easy enough to find a compatible new replacement, however it cost 200 Euros. Expensive! The third problem I noticed was that some of the scans were coming out stretched. Often about 10% too wide/long, sometimes more than that. My panoramics looked panoooooooramic. I did some research and someone suggested this might be a “buffering issue”, which I thought was nonsense. Doing some testing I heard slipping sounds when the scanner was pulling the film into the body. After more research I stumbled on a post that suggested the belts need replacing. I opened the scanner up, and sure enough: A ha! You can’t quite see that the one on the back is even worse. I replaced those with compatible belts: 535 synchroflex t 2.5/245. Problem solved. The fourth problem was that the film holders were old and/or had been mishandled. They were falling apart and held together with electrical tape or glue, which didn’t seem optimal. Replacements cost 350 Euros in total for the four I needed. They’re now available cheaper from China, since the patents have expired. Or, you know, China. They used to cost about 200 Euros each from Hasselblad. The fifth problem, which is a potential one and hasn’t manifested yet, is that the lamps may eventually need replacing. I picked up a couple for 25 Euros. That seemed like a reasonable thing to do while they’re still available. Success? Let’s add up the costs of acquiring this scanner and renovating it: Scanner: 1,750.- CHF Power Supply: 175.- CHF Belts: 25.- CHF Film Holders: 350.- CHF Lamps: 25.- CHF Total: 2,325.- CHF (c. 2,500 EUR) In the last year (since acquiring the scanner) I have scanned: c. 250 panoramics frames (~ 6,000 CHF) c. 2,500 medium format frames (~ 80,000 CHF) c. 200 large format frames (~ 9,000 CHF) The figures in parentheses are what it would have cost me to have that number of frames scanned by a third party. That is, er, quite a saving. Also quite a lucrative business model perhaps? I think I can argue the cost of the scanner was a very good investment, and I haven’t finished using it yet. Even if it were to stop working tomorrow, it has already paid for itself many times over. Could it stop working tomorrow? Yes, because of other issues that will be harder to solve. The Bigger Issue(s)? A Power Mac G4 (discontinued in 2004). This came with the scanner, the necessary hardware and software to drive it, and is almost certainly living on borrowed time. Spinning metal is never good in the long-term. I’ll maybe purchase a backup soon, as these can still be found for a couple of hundred Euros. The key thing though, is that this very expensive, very high quality scanner, will at some point be rendered useless by the upgrade treadmill because the software required to run it will be increasingly difficult to run. A scanner that is still used by businesses, educational institutions, and individuals like me. A scanner that originally cost tens of thousands of Euros less than a decade ago. The upgrade treadmill is constantly whirring away. This is from the top of the Seattle Space Needle. “Do not upgrade anything on computer”. Clearly that notice speaks of someone being bitten by an upgrade at some point. I wonder is anyone else feeling the fatigue? Security updates, sure I can understand. But feature creep and trivialities? No! What tangible benefits have the last ten, fifteen, or even twenty years of OS updates brought? Other than security, and compatibility with newer hardware? New hardware is great, really, but by association forced deprecation of older hardware. No! It feels like the upgrade treadmill gets faster and steeper every year. Add to that subscription lock-in and dead endpoints: “I couldn’t vacuum my house because an SSL cert had expired” is what someone told me earlier this year. Fortunately this person is a software engineer so ended up man-in-the-middling the network traffic to get the vacuum cleaner to work again (no SSL-pinning it seems). “GoPro is announcing the end of life of the GoPro Quik app for macOS, effective at the end of 2024”. They discontinued the former in favour of their mobile app, which requires an account, login, subscription, and so on. I just want to transfer the videos from the hardware, I don’t need any of this crap (I don’t need any of that crap, it turns out GoPro haven’t locked the device down enough to prevent using third party apps to access the files. Yet). And, of course, software has to be in everything. These days the scanner would/could have an embedded Raspberry PI? Just a keyboard and mouse input, monitor and USB output would reduce the surface area, connectivity issues, and software dependency. Or software is never done? Because: externalities. I guess software is “done” when it’s no longer supported? Marciano Planque has a good piece on this: When hardware products reach end-of-life (EOL), companies should be forced to open-source the software. I think that’s a fair thing to say. I suspect Hasselblad/Imacon never open-sourced the software due to licensing issues. Or they just lost the source. Or they just don’t care, I don’t know. Maybe some combination of the three. And, inevitably, discontinued hardware like this scanner. Or, that is to say, discontinued parts? What about regulation changes? The panoramics I shoot are with a camera that was discontinued in 2004 because EU regulation banned lead solder in circuit boards. The company decided redesigning the parts wasn’t worth it. Old hardware has new exciting ways to fail. As time goes on components will fail or loosen - components that were expected to last decades. Then that results in tribal knowledge, or worse link rot and QR code rot. A lot of this stuff is hidden in walled gardens. There’s a Facebook Imacon group, for example. Why in the ever-loving fuck is a group for technical people, by technical people, on Facebook? Then there’s misleading AI. “My flextight scans are coming out stretched, what might the problem be?” LLM’s have gobbled up all the right information, and all the wrong information. Or information that is massively out of date. Nowhere in the suggestions here does it mention the belts might need replacing, which, according to my own research, is the most common reason these days. Legacy Software A decade ago I wrote an essay that also hit the front page of HN: All Software is Legacy. I think it is still relevant today, some parts not so much given we are now in The Age of Prompt, but mostly it’s still true. Nicholas always said “legacy software is the ugly stuff that makes you money”, which I think is true. But now it’s the stuff that surrounds us, like when I want to withdraw cash (guess what software most cash machines are still running?). Or when I want to take a train - when I gave this talk in Germany I had to get from the airport to the city centre. The ticket machines were disabled with a sign saying “no longer in use, download the app”. Then register. Then buy the ticket. I just want to give you money. Or when I wanted to pay for parking while stopping off at some random town in the UK - the same situation as with the ticket machines. “Download the app, register, pay”. Fuck that, I went and parked somewhere else. I just want to park, I don’t want to fight with software. Or if I want to hire a bike (not pictured: the half dozen apps on my phone to hire a bike). And when I want to buy stuff from a shop… One of the self-checkouts crashed recently in the coop, rebooting into a version of SUSE Linux from well over a decade ago. We’re collectively creating more and more of this everyday, letting it out into the world where it becomes a future liability for someone or the death knell for something. A pile of bikes, an unplugged ticket machine, a top of the line but no longer driveable scanner. References Imacon Users Group (the non-Facebook group) The state of Hasselblad Flextight scanners (2019) 1951 USAF resolution test chart Vlads Test Target Printer Story Original Scanner Blog Responses to HN Camera Scanning All Software is Legacy Repair Cafe
The Tetris effect is one of psychology’s most easy to reproduce experiments. Simply spend a bit of time playing the eponymous game every day for a few weeks. After a little while, you’ll start recognizing familiar Tetromino shapes in clouds, buildings, and everyday objects. You might even see them appear before your eyes when you start falling asleep. Tom Tang Attention hijacking There’s one lesson the Tetris effect teaches us: whatever you focus on long enough will end up shaping your thoughts. This can be a good thing since it’s how we learn new skills and discover new ideas. Sadly, less and less of our attention is focused intentionally. Instead of picking what we want to see we let other people decide what is supposed to be good for us. Do you want to watch a video? YouTube knows you like cooking and art streams. But why not also recommend a few clips about the stock market bubble, global warming, and the war in Iran. Doomscrolling will make you stay longer and click on a few more ads. Do you want to listen to music? Just open a Spotify playlist and let the algorithm figure out what you like. Please ignore the AI slop they will insert in between real songs to avoid paying royalties to real artists. Do you want to know how your colleagues are doing? Too bad, LinkedIn will bury any relevant career news between the opinion of complete strangers. It is surely just a coincidence that those strangers happen to be shilling whatever Microsoft is invested in at the moment. Do you want the opinion of strangers on a product? Well those Redditors you wanted to ask are probably just a bunch of LLMs talking to a bunch of Russian trolls now. I hope you didn’t value their opinion too much. If, like me and most people, you spend the major part of your day focused on your device, there’s no doubt it’s affecting you. And when you let someone else dictate what appears on your screen, it’s the same as giving them the key to your brain. New York Said Back to an intentional internet The internet wasn’t always like that. Before recommendation algorithms where a thing, you had to decide what you would be doing on the computer. You didn’t really have one big app that you could open and order it to entertain you. Instead, you had a few dozen of bookmarks to websites, each with a specific idea in mind. A site for video game news, that one website with lots of tutorials, a blog about anime that didn’t update often enough, a wiki about a TV show from the 90s… Of course awful things existed on the web. We had Encyclopedia Dramatica and Rotten.com, but you actually had to put the effort to go there if you wanted. Nobody was going to put pictures of dead kids and far-right propaganda as a suggestion after a pancake recipe or a cat video. The good thing is that this intentional internet is still around. It has just been a bit buried below the corporate web, but it’s not very hard to find. After all you’re on this blog, so you probably already have a good idea about it. The main difference between this time and now is you. When you want to get back to reading blogs, RSS feeds, and finish that tutorial instead of doomscrolling shorts, you have to get used to a slower internet. One where content is not infinite and doesn’t get updated every click. But like every habit, the only thing you have to do is to keep at it. And if you pay enough attention to it, something will click in your brain.
