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Hold my hand, grow my skin Erica Western Geiger Counter Do you have any addictions? You may not register them as such, perhaps because they don’t lead to anything you consider harmful consequences. But you have them. In some ways, all your behavior is compulsive. What would the alternative be? A point is, if we have something that we can predict this video Free will comes from the “veil of computability”, things look random until you find the pattern. I was at a bar last night and this girl told me you can’t predict humans, and the exact example she used was that it’s not like y = mx + b Oh, if only she knew. The dreams of my childhood have come true, studying machine learning has shown me how I work. I tried to explain that instead of 2 parameters it’s 100 trillion parameters, and it’s the slightly different y = relu(w@x) + b a bunch of times, you have to put some nonlinearities in there cause linear systems can only approximate a small class of functions. But this explanation was not heard at a bar. She was so confident she was right, and like I don’t even know where to start. Reader of this blog, do you know? AI is coming and we are so unbelievably unprepared. What is this garbage and this garbage. It’s nerd shit and political propaganda. The amount of power over nature that the Silicon Valley death cult is stumbling into is horrifying, and these high priests don’t have a basic grasp of people. No humanities education (perhaps the programs were gutted on purpose). Are we ready for the hypnodrones? How the fuck is targeted advertising legal and culturally okay? This will not stop until they take our free will from us. There’s a fire that burns today Better Nukes don’t end humanity. Current path AI doesn’t end humanity. It just ends all the machines and hands the world over to the street people. Now I see how the dark ages happened. If all the humans died today, all the machines would shortly follow. If all the machines died today, humanity would keep on going. Pay attention to this milestone. To date, machines are not robust, and evolution may be efficient at robust search. If it is, we get dark ages. If it’s not and we find a shortcut, God only knows.
This is not going to be a cakewalk like self driving cars. Most of comma’s competition is now out of business, taking billions and billions of dollars with it. Re: Tesla and FSD, we always expected Tesla to have the lead, but it’s not a winner take all market, it will look more like iOS vs Android. comma has been around for 10 years, is profitable, and is now growing rapidly. In self driving, most of the competition wasn’t even playing the right game. This isn’t how it is for ML frameworks. tinygrad’s competition is playing the right game, open source, and run by some quite smart people. But this is my second startup, so hopefully taking a bit more risk is appropriate. For comma to win, all it would take is people in 2016 being wrong about LIDAR, mapping, end to end, and hand coding, which hopefully we all agree now that they were. For tinygrad to win, it requires something much deeper to be wrong about software development in general. As it stands now, tinygrad is 14556 lines. Line count is not a perfect proxy for complexity, but when you have differences of multiple orders of magnitude, it might mean something. I asked ChatGPT to estimate the lines of code in PyTorch, JAX, and MLIR. JAX = 400k MLIR = 950k PyTorch = 3300k They range from one to two orders of magnitude off. And this isn’t even including all the libraries and drivers the other frameworks rely on, CUDA, cuBLAS, Triton, nccl, LLVM, etc…. tinygrad includes every single piece of code needed to drive an AMD RDNA3 GPU except for LLVM, and we plan to remove LLVM in a year or two as well. But so what? What does line count matter? One hypothesis is that tinygrad is only smaller because it’s not speed or feature competitive, and that if and when it becomes competitive, it will also be that many lines. But I just don’t think that’s true. tinygrad is already feature competitive, and for speed, I think the bitter lesson also applies to software. When you look at the machine learning ecosystem, you realize it’s just the same problems over and over again. The problem of multi machine, multi GPU, multi SM, multi ALU, cross machine memory scheduling, DRAM scheduling, SRAM scheduling, register scheduling, it’s all the same underlying problem at different scales. And yet, in all the current ecosystems, there are completely different codebases and libraries at each scale. I don’t think this stands. I suspect there is a simple formulation of the problem underlying all of the scheduling. Of course, this problem will be in NP and hard to optimize, but I’m betting the bitter lesson wins here. The goal of the tinygrad project is to abstract away everything except the absolute core problem in the cleanest way possible. This is why we need to replace everything. A model for the hardware is simple compared to a model for CUDA. If we succeed, tinygrad will not only be the fastest NN framework, but it will be under 25k lines all in, GPT-5 scale training job to MMIO on the PCIe bus! Here are the steps to get there: Expose the underlying search problem spanning several orders of magnitude. Due to the execution of neural networks not being data dependent, this problem is very amenable to search. Make sure your formulation is simple and complete. Fully capture all dimensions of the search space. The optimization goal is simple, run faster. Apply the state of the art in search. Burn compute. Use LLMs to guide. Use SAT solvers. Reinforcement learning. It doesn’t matter, there’s no way to cheat this goal. Just see if it runs faster. If this works, not only do we win with tinygrad, but hopefully people begin to rethink software in general. Of course, it’s a big if, this isn’t like comma where it was hard to lose. But if it wins… The main thing to watch is development speed. Our bet has to be that tinygrad’s development speed is outpacing the others. We have the AMD contract to train LLaMA 405B as fast as NVIDIA due in a year, let’s see if we succeed.
I signed up for Hinge. Holy shit with the boosts. How does someone who works on this wake up every morning and feel okay about themselves? Similarly with the tip screens, Uber algorithm, all the zero sum bullshit using all the tricks of psychology to extract a little bit more from every interaction in society. Nudge. Nudge. NUDGE. Want to partake in normal society like buying a coffee, going on a date, getting a ride, paying a friend. Oh, there’s a middle man now. An evil ominous middleman using state of the art AI algorithms to extract just a little bit more from you. But eventually the market will fix this, right? People will feel sick of being manipulated and move elsewhere? Ahhh, but they see that coming long before you do. They have dashboards. Quick Jeeves, tune the AI to make people feel less manipulated. Give them a little bit more for now, we have to think about maximizing lifetime customer value here. Oh the AI already did this on its own? Jeeves you’ve been replaced! People perpetually on the edge. You want to opt out of this all you say? Good luck running a competitive business! Every metric is now a target. You better maximize engagement or you will lose engagement this is a red queen’s race we can’t afford to lose! Burn all the social capital, burn all your values, FEED IT ALL TO MOLOCH! Someday, people will have to realize we live in a society. What will it take? A complete self cannibalization to the point you can’t eat your own mouth? It sure as hell isn’t going to be people opting out, that’s a collective action problem you can’t solve. Democracy, haha, you think the algorithms will let you vote to kill them? Your vote is as decoupled from action as the amount Uber pays the driver is decoupled from the fare that you pay. There’s no reform here, there’s only revolution. Will it simply be a huge financial collapse? Or do we need World War 3? And even World War 3 is on a spectrum. Will mass starvation fix this? Or will the attitude of thinking it’s okay to manipulate others at scale persist even past that? He’s got his, and I’ve got mine… If you open a government S&P 500 account for everyone with $1,000 at birth that’ll pay their social security cause it like…goes up…wait who’s creating this value again? It’s not okay. Advertising is not okay. Price discrimination is not okay. Using big data, machine learning, and psychology to manipulate others at scale is not okay. But you aren’t going to learn this lesson until you have fed a huge majority of your customers to Moloch. Modern capitialism is wireheading. Release the hypnodrones. How many cans of Pepsi did you want them to consume an hour again?
“For example, if one believes that affirmative action is good for black people, does it make sense to demand affirmative action in hostile or dogmatic terms? Obviously it would be more productive to take a diplomatic and conciliatory approach that would make at least verbal and symbolic concessions to white people who think that affirmative action discriminates against them. But leftist activists do not take such an approach because it would not satisfy their emotional needs.” – Unabomber Manifesto To date, the Trump administration has been an absolute tragedy. It has been the acting out of emotions. There are no adults in the room. I’m not saying there would have been adults in the room with the Kamala regime either, but I had some hopes for positive change with the Trump tech-bro alliance and now they are gone. At least truths are being laid bare versus heads being buried in the sands of joy, but I think there was a much better way. For example, I don’t support America funding the war in Ukraine. But the way Zelensky was treated is just dumb. See the Unabomber quote above, between this and the Munich speech, Mr. JD Vance, I hope your emotional needs are being met (at the expense of the good will of our allies). It's the economy, stupid Regardless of anyone’s long-term objectives in the US, be they decoupling from China, bringing manufacturing to the US, bringing lifestyle improvements to US citizens; I think it’s unquestionable that uncertainty about the future was needlessly increased. And unless the uncertainty was the goal, I can’t figure out why things were done the way they were. And if the uncertainty was the goal…uhhh…is our government captured by Russian or Chinese agents? Because that’s who benefits. I don’t trust the news very much. I have no idea if the guy in the El Salavdor prison had a fair trial, if the students being deported are criminals, or even if they are being deported at all. It’s really hard and time consuming to get to the truth about any of these things. However, when markets crash. that is obviously real. With the news, there’s usually no way to trade on it being real or fake, there’s nobody to take the other side. But with big public markets, there’s very deep liquidity if you think they are priced wrong. In addition to the 10% the market is down, the dollar is also down 10%. Considering the market is priced in dollars, it’s closer to 20% down. And even worse on top of all of this, prices are going up due to the tariffs. Was crashing the economy the goal? A side-effect of a greater plan? Because given how this was executed, a 3-week old LLM could have told you shit was gonna crash. And it’s not going to bring manufacturing back. I have done manufacturing in America for years, and anyone with any experience could have told you that this wouldn’t work, manufacturing requires long term investment and long term investment requires stability. What was the real goal here? Elon, you need to reconcile with your daughter Andrew Callaghan did a good piece on Elon’s radicalization. I get it, we have all been there. For me it was Gamergate (which still has a terrible wikipedia page that doesn’t explain what it was). But this doesn’t have to be you forever. You are the closest thing to an adult in any room in America. When you compare America to China, it’s really more like comparing Elon to China. ULA is a little joke compared to CNSA. And look into what percent of US car exports are Teslas. The man is singlehandedly beating the rest of the US combined. If you want any hope of standing against China, your political coalition better include him. Elon has been pretty politically quiet lately. I’m sure he knew exactly what would happen with the tariffs, but he couldn’t stop them. I got fooled too, thought it could be different this time. But it’s no different from 2017. (btw, we are finally beating climate change thanks to cheap solar panels from China) I know the idea of PR is against a lot of what you believe in, but you need to heads down put together a large scale PR campaign, distance yourself from this train wreck, denounce stupid fake right wing conspiracy theories, reconcile with your daughter (from a reader of sci-fi and The Culture, is the trans thing that hard to understand?), resolve your stupid beef with OpenAI (we are all disappointed, but you don’t have a great track record for open source either), and start building a new political party. Pro large scale legal immigration, not a single illegal border crosser. Pro choice (within reason), and also pro gun (within reason). Inclusive and diverse, with an unwavering focus on merit. Anti crime, with an understanding that victimless crime is not crime. Expose higher education and the medical system to the free market (watch how fast prices fall) Free market and trade, but not an unregulated market. Markets require regulation to be free. It’s probably the only shot we have against China. The current Republicans and Democrats are just far too stupid; the Chinese are watching this tariff drama and laughing their asses off. Their plans are measured in centuries. America, do you want to be a protectionist backwater? If so, and all the thymos is gone, then there’s no place for me there. If this is really the way things are going, the only thing for anyone to do is leave. We’ll see how it shapes up in the next few years. But if the racists or the other racists are still running the show, we really are just cooked. Enjoy your handouts to black people and your handouts to white people in a poverty stricken shithole.
You know about Critical Race Theory, right? It says that if there’s an imbalance in, say, income between races, it must be due to discrimination. This is what wokism seems to be, and it’s moronic and false. The right wing has invented something equally stupid. Introducing Critical Trade Theory, stolen from this tweet. If there’s an imbalance in trade between countries, it must be due to unfair practices. (not due to the obvious, like one country is 10x richer than the other) There’s really only one way the trade deficits will go away, and that’s if trade goes to zero (or maybe if all these countries become richer than America). Same thing with the race deficits, no amount of “leg up” bullshit will change them. Why are all the politicians in America anti-growth anti-reality idiots who want to drive us into the poor house? The way this tariff shit is being done is another stupid form of anti-merit benefits to chosen groups of people, with a whole lot of grift to go along with it. Makes me just not want to play.
More in programming
I always had a diffuse idea of why people are spending so much time and money on amateur radio. Once I got my license and started to amass radios myself, it became more clear.
What does it mean when someone writes that a programming language is “strongly typed”? I’ve known for many years that “strongly typed” is a poorly-defined term. Recently I was prompted on Lobsters to explain why it’s hard to understand what someone means when they use the phrase. I came up with more than five meanings! how strong? The various meanings of “strongly typed” are not clearly yes-or-no. Some developers like to argue that these kinds of integrity checks must be completely perfect or else they are entirely worthless. Charitably (it took me a while to think of a polite way to phrase this), that betrays a lack of engineering maturity. Software engineers, like any engineers, have to create working systems from imperfect materials. To do so, we must understand what guarantees we can rely on, where our mistakes can be caught early, where we need to establish processes to catch mistakes, how we can control the consequences of our mistakes, and how to remediate when somethng breaks because of a mistake that wasn’t caught. strong how? So, what are the ways that a programming language can be strongly or weakly typed? In what ways are real programming languages “mid”? Statically typed as opposed to dynamically typed? Many languages have a mixture of the two, such as run time polymorphism in OO languages (e.g. Java), or gradual type systems for dynamic languages (e.g. TypeScript). Sound static type system? It’s common for static type systems to be deliberately unsound, such as covariant subtyping in arrays or functions (Java, again). Gradual type systems migh have gaping holes for usability reasons (TypeScript, again). And some type systems might be unsound due to bugs. (There are a few of these in Rust.) Unsoundness isn’t a disaster, if a programmer won’t cause it without being aware of the risk. For example: in Lean you can write “sorry” as a kind of “to do” annotation that deliberately breaks soundness; and Idris 2 has type-in-type so it accepts Girard’s paradox. Type safe at run time? Most languages have facilities for deliberately bypassing type safety, with an “unsafe” library module or “unsafe” language features, or things that are harder to spot. It can be more or less difficult to break type safety in ways that the programmer or language designer did not intend. JavaScript and Lua are very safe, treating type safety failures as security vulnerabilities. Java and Rust have controlled unsafety. In C everything is unsafe. Fewer weird implicit coercions? There isn’t a total order here: for instance, C has implicit bool/int coercions, Rust does not; Rust has implicit deref, C does not. There’s a huge range in how much coercions are a convenience or a source of bugs. For example, the PHP and JavaScript == operators are made entirely of WAT, but at least you can use === instead. How fancy is the type system? To what degree can you model properties of your program as types? Is it convenient to parse, not validate? Is the Curry-Howard correspondance something you can put into practice? Or is it only capable of describing the physical layout of data? There are probably other meanings, e.g. I have seen “strongly typed” used to mean that runtime representations are abstract (you can’t see the underlying bytes); or in the past it sometimes meant a language with a heavy type annotation burden (as a mischaracterization of static type checking). how to type So, when you write (with your keyboard) the phrase “strongly typed”, delete it, and come up with a more precise description of what you really mean. The desiderata above are partly overlapping, sometimes partly orthogonal. Some of them you might care about, some of them not. But please try to communicate where you draw the line and how fuzzy your line is.
(Last week's newsletter took too long and I'm way behind on Logic for Programmers revisions so short one this time.1) In classical logic, two operators F/G are duals if F(x) = !G(!x). Three examples: x || y is the same as !(!x && !y). <>P ("P is possibly true") is the same as ![]!P ("not P isn't definitely true"). some x in set: P(x) is the same as !(all x in set: !P(x)). (1) is just a version of De Morgan's Law, which we regularly use to simplify boolean expressions. (2) is important in modal logic but has niche applications in software engineering, mostly in how it powers various formal methods.2 The real interesting one is (3), the "quantifier duals". We use lots of software tools to either find a value satisfying P or check that all values satisfy P. And by duality, any tool that does one can do the other, by seeing if it fails to find/check !P. Some examples in the wild: Z3 is used to solve mathematical constraints, like "find x, where f(x) >= 0. If I want to prove a property like "f is always positive", I ask z3 to solve "find x, where !(f(x) >= 0), and see if that is unsatisfiable. This use case powers a LOT of theorem provers and formal verification tooling. Property testing checks that all inputs to a code block satisfy a property. I've used it to generate complex inputs with certain properties by checking that all inputs don't satisfy the property and reading out the test failure. Model checkers check that all behaviors of a specification satisfy a property, so we can find a behavior that reaches a goal state G by checking that all states are !G. Here's TLA+ solving a puzzle this way.3 Planners find behaviors that reach a goal state, so we can check if all behaviors satisfy a property P by asking it to reach goal state !P. The problem "find the shortest traveling salesman route" can be broken into some route: distance(route) = n and all route: !(distance(route) < n). Then a route finder can find the first, and then convert the second into a some and fail to find it, proving n is optimal. Even cooler to me is when a tool does both finding and checking, but gives them different "meanings". In SQL, some x: P(x) is true if we can query for P(x) and get a nonempty response, while all x: P(x) is true if all records satisfy the P(x) constraint. Most SQL databases allow for complex queries but not complex constraints! You got UNIQUE, NOT NULL, REFERENCES, which are fixed predicates, and CHECK, which is one-record only.4 Oh, and you got database triggers, which can run arbitrary queries and throw exceptions. So if you really need to enforce a complex constraint P(x, y, z), you put in a database trigger that queries some x, y, z: !P(x, y, z) and throws an exception if it finds any results. That all works because of quantifier duality! See here for an example of this in practice. Duals more broadly "Dual" doesn't have a strict meaning in math, it's more of a vibe thing where all of the "duals" are kinda similar in meaning but don't strictly follow all of the same rules. Usually things X and Y are duals if there is some transform F where X = F(Y) and Y = F(X), but not always. Maybe the category theorists have a formal definition that covers all of the different uses. Usually duals switch properties of things, too: an example showing some x: P(x) becomes a counterexample of all x: !P(x). Under this definition, I think the dual of a list l could be reverse(l). The first element of l becomes the last element of reverse(l), the last becomes the first, etc. A more interesting case is the dual of a K -> set(V) map is the V -> set(K) map. IE the dual of lived_in_city = {alice: {paris}, bob: {detroit}, charlie: {detroit, paris}} is city_lived_in_by = {paris: {alice, charlie}, detroit: {bob, charlie}}. This preserves the property that x in map[y] <=> y in dual[x]. And after writing this I just realized this is partial retread of a newsletter I wrote a couple months ago. But only a partial retread! ↩ Specifically "linear temporal logics" are modal logics, so "eventually P ("P is true in at least one state of each behavior") is the same as saying !always !P ("not P isn't true in all states of all behaviors"). This is the basis of liveness checking. ↩ I don't know for sure, but my best guess is that Antithesis does something similar when their fuzzer beats videogames. They're doing fuzzing, not model checking, but they have the same purpose check that complex state spaces don't have bugs. Making the bug "we can't reach the end screen" can make a fuzzer output a complete end-to-end run of the game. Obvs a lot more complicated than that but that's the general idea at least. ↩ For CHECK to constraint multiple records you would need to use a subquery. Core SQL does not support subqueries in check. It is an optional database "feature outside of core SQL" (F671), which Postgres does not support. ↩
Omarchy 2.0 was released on Linux's 34th birthday as a gift to perhaps the greatest open-source project the world has ever known. Not only does Linux run 95% of all servers on the web, billions of devices as an embedded OS, but it also turns out to be an incredible desktop environment! It's crazy that it took me more than thirty years to realize this, but while I spent time in Apple's walled garden, the free software alternative simply grew better, stronger, and faster. The Linux of 2025 is not the Linux of the 90s or the 00s or even the 10s. It's shockingly more polished, capable, and beautiful. It's been an absolute honor to celebrate Linux with the making of Omarchy, the new Linux distribution that I've spent the last few months building on top of Arch and Hyprland. What began as a post-install script has turned into a full-blown ISO, dedicated package repository, and flourishing community of thousands of enthusiasts all collaborating on making it better. It's been improving rapidly with over twenty releases since the premiere in late June, but this Version 2.0 update is the biggest one yet. If you've been curious about giving Linux a try, you're not afraid of an operating system that asks you to level up and learn a little, and you want to see what a totally different computing experience can look and feel like, I invite you to give it a go. Here's a full tour of Omarchy 2.0.
In 2020, Apple released the M1 with a custom GPU. We got to work reverse-engineering the hardware and porting Linux. Today, you can run Linux on a range of M1 and M2 Macs, with almost all hardware working: wireless, audio, and full graphics acceleration. Our story begins in December 2020, when Hector Martin kicked off Asahi Linux. I was working for Collabora working on Panfrost, the open source Mesa3D driver for Arm Mali GPUs. Hector put out a public call for guidance from upstream open source maintainers, and I bit. I just intended to give some quick pointers. Instead, I bought myself a Christmas present and got to work. In between my university coursework and Collabora work, I poked at the shader instruction set. One thing led to another. Within a few weeks, I drew a triangle. In 3D graphics, once you can draw a triangle, you can do anything. Pretty soon, I started work on a shader compiler. After my final exams that semester, I took a few days off from Collabora to bring up an OpenGL driver capable of spinning gears with my new compiler. Over the next year, I kept reverse-engineering and improving the driver until it could run 3D games on macOS. Meanwhile, Asahi Lina wrote a kernel driver for the Apple GPU. My userspace OpenGL driver ran on macOS, leaving her kernel driver as the missing piece for an open source graphics stack. In December 2022, we shipped graphics acceleration in Asahi Linux. In January 2023, I started my final semester in my Computer Science program at the University of Toronto. For years I juggled my courses with my part-time job and my hobby driver. I faced the same question as my peers: what will I do after graduation? Maybe Panfrost? I started reverse-engineering of the Mali Midgard GPU back in 2017, when I was still in high school. That led to an internship at Collabora in 2019 once I graduated, turning into my job throughout four years of university. During that time, Panfrost grew from a kid’s pet project based on blackbox reverse-engineering, to a professional driver engineered by a team with Arm’s backing and hardware documentation. I did what I set out to do, and the project succeeded beyond my dreams. It was time to move on. What did I want to do next? Finish what I started with the M1. Ship a great driver. Bring full, conformant OpenGL drivers to the M1. Apple’s drivers are not conformant, but we should strive for the industry standard. Bring full, conformant Vulkan to Apple platforms, disproving the myth that Vulkan isn’t suitable for Apple hardware. Bring Proton gaming to Asahi Linux. Thanks to Valve’s work for the Steam Deck, Windows games can run better on Linux than even on Windows. Why not reap those benefits on the M1? Panfrost was my challenge until we “won”. My next challenge? Gaming on Linux on M1. Once I finished my coursework, I started full-time on gaming on Linux. Within a month, we shipped OpenGL 3.1 on Asahi Linux. A few weeks later, we passed official conformance for OpenGL ES 3.1. That put us at feature parity with Panfrost. I wanted to go further. OpenGL (ES) 3.2 requires geometry shaders, a legacy feature not supported by either Arm or Apple hardware. The proprietary OpenGL drivers emulate geometry shaders with compute, but there was no open source prior art to borrow. Even though multiple Mesa drivers need geometry/tessellation emulation, nobody did the work to get there. My early progress on OpenGL was fast thanks to the mature common code in Mesa. It was time to pay it forward. Over the rest of the year, I implemented geometry/tessellation shader emulation. And also the rest of the owl. In January 2024, I passed conformance for the full OpenGL 4.6 specification, finishing up OpenGL. Vulkan wasn’t too bad, either. I polished the OpenGL driver for a few months, but once I started typing a Vulkan driver, I passed 1.3 conformance in a few weeks. What remained was wiring up the geometry/tessellation emulation to my shiny new Vulkan driver, since those are required for Direct3D. Et voilà, Proton games. Along the way, Karol Herbst passed OpenCL 3.0 conformance on the M1, running my compiler atop his “rusticl” frontend. Meanwhile, when the Vulkan 1.4 specification was published, we were ready and shipped a conformant implementation on the same day. After that, I implemented sparse texture support, unlocking Direct3D 12 via Proton. …Now what? Ship a great driver? Check. Conformant OpenGL 4.6, OpenGL ES 3.2, and OpenCL 3.0? Check. Conformant Vulkan 1.4? Check. Proton gaming? Check. That’s a wrap. We’ve succeeded beyond my dreams. The challenges I chased, I have tackled. The drivers are fully upstream in Mesa. Performance isn’t too bad. With the Vulkan on Apple myth busted, conformant Vulkan is now coming to macOS via LunarG’s KosmicKrisp project building on my work. Satisfied, I am now stepping away from the Apple ecosystem. My friends in the Asahi Linux orbit will carry the torch from here. As for me? Onto the next challenge!
