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The title is not a rhetorical question, and I'm not going to bury an answer. I don't have an answer. This post is my exploration of the question, and why I think it is a question1. Important things up front: what's my relationship with LLMs today? I don't use any LLMs regularly. I do have access to GitHub Copilot through my employer. I have it available on a hotkey, I think, and I cannot remember how to trigger it since I do not use it. I've explored using LLMs in the past. I used to be a regular Copilot user, and I explored ChatGPT, Claude, etc. to see what their capabilities were. I have done trainings for my coworkers on how to use them effectively, though I would not feel comfortable doing so now. My employer's product uses LLMs. I don't want to link to my employer, but yeah, I guess my paycheck depends on being okay with integrating them in? It's complicated (a refrain). (This post is, obviously, my opinions and does not reflect my employer.) I don't think using or not using them...
3 days ago

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More from ntietz.com blog - technically a blog

What's in a ring buffer? And using them in Rust

Working on my cursed MIDI project, I needed a way to store the most recent messages without risking an unbounded amount of memory usage. I turned to the trusty ring buffer for this! I started by writing a very simple one myself in Rust, then I looked and what do you know, of course the standard library has an implementation. While I was working on this project, I was pairing with a friend. She asked me about ring buffers, and that's where this post came from! What's a ring buffer? Ring buffers are known by a few names. Circular queues and circular buffers are the other two I hear the most. But this name just has a nice ring to it. It's an array, basically: a buffer, or a queue, or a list of items stacked up against each other. You can put things into it and take things out of it the same as any buffer. But the front of it connects to the back, like any good ring1. Instead of adding on the end and popping from the end it, like a stack, you can add to one end and remove from the start, like a queue. And as you add or remove things, where the start and end of the list move around. Your data eats its own tail. This lets us keep a fixed number of elements in the buffer without running into reallocation. In a regular old buffer, if you use it as a queue—add to the end, remove from the front—then you'll eventually need to either reallocate the entire thing or shift all the elements over. Instead, a ring buffer lets you just keep adding from either end and removing from either end and you never have to reallocate! Uses for a ring buffer My MIDI program is one example of where you'd want a ring buffer, to keep the most recent items. There are some general situations where you'll run into this: You want a fixed number of the most recent things, like the last 50 items seen You want a queue, especially with a fixed maximum number of queued elements2 You want a buffer for data coming in with an upper bound, like with streaming audio, and you want to overwrite old data if the consumer can't keep up for a bit A lot of it comes down to performance, and streaming data. Something is producing data, something else is consuming it, and you want to make sure insertions and removals are fast. That was exactly my use: a MIDI device produces messages, my UI consumes them, but I don't want to fill up all my memory, forever, with more of them. How ring buffers work So how do they work? This is a normal, non-circular buffer: When you add something, you put it on the end. If you're using it as a stack, then you can pop things off the end. But if you're using it as a queue, you pop things off the front... And then you have to shuffle everything to the left. That's why we have ring buffers! I'll draw it as a straight line here, to show how it's laid out in memory. But the end loops back to the front logically, and we'll see how it wraps around. We start with an empty buffer, and start and end both point at the first element. When start == end, we know the buffer is empty. If we insert an element, we move end forward. And it gets repeated as we insert multiple times. If we remove an element, we move start forward. We can also start the buffer at any point, and it crosses over the end gracefully. Ring buffers are pretty simple when you get into their details, with just a few things to wrap your head around. It's an incredibly useful data structure! Rust options If you want to use one in Rust, what are your options? There's the standard library, which includes VecDeque. This implements a ring buffer, and the name comes from "Vec" (Rust's growable array type) combined with "Deque" (a double-ended queue). As this is in the standard library, this is quite accessible from most code, and it's a growable ring buffer. This means that the pop/push operations will always be efficient, but if your buffer is full it will result in a resize operation. The amortized running time will still be O(1) for insertion, but you incur the cost all at once when a resize happens, rather than at each insertion. You can enforce size limits in your code, if you want to avoid resize operations. Here's an example of how you could do that. You check if it's full first, and if so, you remove something to make space for the new element. let buffer: VecDeque<u32> = VecDeque::with_capacity(10); for thing in 0..15 { // if the buffer is already full, remove the first element to make space if buffer.len() == 10 { buffer.pop_front(); } buffer.push_back(thing); } There are also libraries that can enforce this for you! For example, circular-buffer implements a ring buffer. It has a fixed max capacity and won't resize on you, instead overwriting elements when you run out of space. The size is set at compile time, though, which can be great or can be a constraint that's hard to meet. There is also ringbuffer, which gives you a fixed size buffer that's heap allocated at runtime. That buys you some flexibility, with the drawback of being heap-based instead of stack-based. I'm definitely reaching for a library when I need a non-growable ring buffer in Rust now. There are some good choices, and it saves me the trouble of having to manually enforce size limits. 1 One of my favorite rings represents the sun and the moon, with the sun nestling inside this crescent moon shape. Unfortunately, the ring is open there. It makes for a very nice visual effect, but it kept getting snagged on things and bending. So it's not a very good ring for living an active hands-on life. 2 These can also be resizable! The Rust standard library one is. This comes with reallocation cost, which amortizes to a low cost but can be expensive in individual moments.

a week ago 11 votes
Summarizing our recommendations for software documentation

Last year, my coworker Suzanne and I got a case study accepted into an ethnography conference! She's an anthropologist by training, and I'm a software engineer. How'd we wind up there? The short version is I asked her what I thought was an interesting question, and she thought it was an interesting question, and we wound up doing research. We have a lot more to go on the original question—we're studying the relationship between the values we hold as engineers and our documentation practices—and this case study is the first step in that direction. The title of the case study is a mouthful: "Foundations of Practice: An Ethnographic Exploration of Software Documentation and its Cultural Implications for an Agile Startup". I mean, it's intended for a more academic audience, and in a field that's not software engineering. But what we studied is relevant for software engineers, so let's talk about it here in more familiar language! If you want to read the full case study, it's open access. I'll start with the recommendations we provided, share a little bit about our methodology, and finish us out with a little about where we can go from here. Our recommendations The case study concluded with recommendations. This is an area I'd like us to do a lot more work in, because recommendations based on a case study are based on one example, and they'd obviously be much stronger based on more data! But for the conference submission, they were a necessary component. I think that the specific recommendations we gave hold up based on my experience (I'm biased, so take this as it is). These were our core recommendations. Start with high-level documentation. If you don't have any docs today, or all your docs are just in a bad way, the biggest bang-for-buck is with your high-level systems docs and process documentation. Don't have a system architecture diagram? Make it! Don't have a CI process diagram? Make it! These help you get your bearings on everything quickly, and they're also usually much faster to make than detailed documentation of more focused pieces. Use design reviews! Here, "design review" means putting your architecture changes—or any proposal for a major code change—through a review process analogous to a code review. This is one of the things we implemented at my company over four years ago, and it's incredibly useful. It makes us think more deeply on our designs, so we make fewer errors in the design phase of any given feature. And it makes the design visible to the whole team, so we get much better knowledge transfer. If I could drop these into every software company, I would. They're that useful. Think about your audience. This is just plain good writing advice, and it bears repeating. Not every kind of documentation has the same audience, and if you don't take that into account you'll write bad docs that your end user won't be able to use effectively. You may use too much jargon for the lay user, or too little jargon for efficient communication with the engineers working on a feature. Maintain the docs, updating them as part of your workflow. I think we all know that docs should be updated. The recommendation here is that updating docs should be part of your workflow. If you run into something that's out of date, go ahead and fix it. If someone asks you a question because it wasn't in a given doc, go ahead and add it there. Document test plans. QA processes are woefully underappreciated in software engineering. I don't quite understand why QA engineering is so looked down upon, because y'all, that stuff is hard. At any rate, testing? That's something you should document! Assuming you run tests before you release (you do, don't you?) then you need to have some organization and documentation around what those tests are, why they're there, etc. This needs to be shared between both QA and product engineers since if the test fails, it's probably, you know, the product engineer's change that broke it—so the better those docs are, the faster they can find the issue. Make onboarding docs. We know that good onboarding is important for bringing new team members up to productive contribution quickly. And we know that documentation is a big part of that. So focus on your documentation as part of your onboarding strategy. Run post-mortems and retrospectives. Mistakes will happen, and when they do? It's imperative that we go back through why they happened and what changes (if any) are merited to our processes as a result. Maybe there's work to be done to prevent similar incidents, or there's something we could do to detect this quicker in the future. Whatever you find, also update your docs: point to the post-mortems in the design docs that led to these decisions so that if someone reads those, they'll also see the longer-term impacts of those decisions. Encourage collaboration on documentation. You can do this by involving multiple team members in creating and reviewing design docs. This is a tool for mentoring and professional development. It also improves all the documentation quality. If you involve team members at all levels (not just your senior engineers!), you'll be able to ensure the docs and processes meet everyone's actual needs. Prioritize critical, complex areas for docs. You can't document everything. We mentioned earlier that you want to start with a high-level documentation overview, but you also want to focus your efforts on things which are critical or particularly complex. This will pay off by reducing the difficulty of understanding these areas, reducing rates of defects and speeding up development. Eliminate ineffective docs, focus on friction points. If your team says that documentation isn't serving a useful purpose, trust them and get rid of it. Change what you do to do something more effective. Focus your documentation efforts on resolving friction points between teams or in the development process. The methodology Our research comprised two main pieces: a literature review and interviews with our engineering team. We did the literature review first, to get our bearings. And, honestly, I was hoping to find answers to what we ultimately were setting out to answer. I'd rather not have to do this research to get our answers! The existing papers gave us a good grounding. I won't repeat too much here—you can read the section in the case study if you're interested. The bulk of the new research we did was through interviews, and analysis of those interviews1. We interviewed nine of our software engineers who were present at a critical transition in the company's history, when we implemented a major new documentation process as a result of transitioning to remote work. Each interview was recorded with the consent of the participants. We then transcribed them and did qualitative coding to extract themes. We were looking for some pre-defined themes (collaboration, learning, and knowledge sharing) and we were also interested in emergent themes. From there, we were able to extract out five values that are represented by documentation practices at the company. These values (collaboration, learning, continuous improvement, accountability, and technical excellence) are exhibited through our documentation practices. They are also reinforced by the documentation practices, so it's not wholly a causal relationship one way or the other. At this point we were able to take the results of the interviews and combine that with the literature review to figure out recommendations based on our case study. These are, of course, not universal. And they're to some extent conjecture: by the nature of a case study, we're not able to ground this in data across multiple companies. But they're a launching off point for teams in need and for future research. What's next? Ultimately, we want to drive toward answering the bigger questions we have around software engineering and documentation. One of those is: a lot of software engineers say their documentation is bad, and we also say that we value good documentation, so why do we not make the documentation better? Why are we not able to live our what we value there? Or do we not value documentation? To answer these questions to a satisfying end, we'll need to do a larger study. That means we'll need to recruit participants across many companies, and we'll need to design a study that can cut to the heart of these issues. I'm not sure when we'll have the time or energy to approach that, but I know we've both been completely sucked in by these questions. So we'll get there eventually! 1 One of the most interesting questions Suzanne got when presenting our research was: how did you get permission to do this? The question surprised me, because I hadn't thought that other companies would make this really hard, but her peers at the conference certainly had a hard time doing similar projects! The answer to this is a few things: we didn't ask for budget (nothing needs approval there), our engineers volunteered their time for it (they were interested, too!), and I'm on the leadership team and was able to just talk to the other company leaders to clear it.

2 weeks ago 16 votes
Bright lights in dark times

It's kind of dark times right now. And I'm definitely only talking about the days being short. It's pretty dark out right now, since it's the winter in the northern hemisphere. Every year, I start to realize somewhere around January that I'm tired, really tired, and don't want to do anything. I'm not sure that this is seasonal affective disorder, but I did start to explore it and found that bright light makes me feel a lot better in the winter. The problem is, I go through this discovery every year, it seems. My earlier attempts After I first learned that bright light can actually help you feel better in the winter, I got a Happy Light. That's the actual branding on it, and it might have helped, maybe? But it was really inconvenient to use. I got one of the more affordable ones, which meant a small panel I had to sit uncomfortably close to. And I was supposed to use it almost first thing in the morning for 30 minutes. That's... really not going to fit in my routine, especially now that I have two young kids who are raring to go right at 7am, and they do not want to deal with mom sitting in front of a lamp that early. So I just kind of stopped using it, and would poke at it in the drawer occasionally but not really do anything with it. Instead, I got a few more lamps in my office. These seemed to help, a little, but that might just be that I like my spaces well lit1. Going as bright as possible Somewhere along the line I saw a post talking about winter energy and light. And the author suggested that indoor lights just have to be bright. They recommended some high-watt LED bulbs. I went ahead and ordered some and... these are very bright. They're 100 watts of LEDs each, and I have two of them. I plugged them in to these plug-in fixtures that have inline switches. These seemed to really help me out a lot. On days I used them, I was more energetic and felt better. But I had a lot of days when I didn't use them, because using them was inconvenient. The main problems were that I had to turn on two switches manually, and they were too bright to look at. Turning them on doesn't sound like a lot, but doing it every day when you're already struggling can be just enough friction to avoid doing it! The brightness was the biggest issue, because they were blinding to look at and cast this reverse shadow out of my office. The brightness was the point, so now do I deal with that? Shading it Turning on the switches was easy. I put them on some smart outlets, set a schedule, and now they turn on and off at my predetermined times! Then I had to make a shade for the lamps. My main goal here is to diffuse the light a bit, so I was thinking of a small wooden frame wrapped in a light white fabric. That would spread the light out and avoid having any spots that are too bright to look at. I took measurements for where it was going to fit, then headed out to my workshop. Then I ripped a scrap board into 0.75"x0.75" stock. I ended up with just enough for the design. This is what I ended up with, after it was glued up. Here's a bonus detail shot of the extremely unnecessary joinery here. But hey, this joinery was incredibly satisfying, and the whole thing went together without any nails or screws. Joy makes it worthwhile. And then with the fabric attached2, it ended looking pretty nice. In its intended home, you can see that it does its job! It's now not painful to look straight at the lamp. You wouldn't want to do it, but it won't hurt you at least! Waiting for summer Of course, we need these bright lights during the winter, during the dark days. But summer will come again. Not all of us will see the long days. We'll lose some to the winter. But summer will come again, and we'll be able to go outside freely. Soak in the sun. Be ourselves. Dance in sunshowers. It's hard to see that in the darkest of times. I'm writing this for myself as much as I'm writing it for you. But believe me: you are strong, and I am strong, and together, we will survive. It seems like this winter is going to last a long time. And it probably will. But I'm not just talking about the winter, and the dark times are going to end, eventually. 1 Most places are very poorly lit and don't have enough lamps. You should have a lot of lamps in every room to make it as bright and cheery as possible! I refuse to believe otherwise, but my wife, a gremlin of the darkness3, does like rooms quite dim. 2 My wife helped with this step. She works with fabric a lot, and this was our first project combining our respective crafts. Certainly not our last! 3 She approved this phrasing.

3 weeks ago 13 votes
My writing process, and how I keep it sustainable

Recently, a reader wrote to me and asked about my writing process and burnout. They had an image in their head that I could sit down at a computer and type up a full post on a given topic, but were unsure if that's the right approach when they start blogging. And they were concerned about how to keep things sustainable for themselves, too. I started to write back to them, but decided to ship my answer for everyone else, as well. Now, to be clear: this is my writing process. There are many other very valid approaches, such as what Gabriella wrote. But I think outlining my process here will at least help break some of the mystique around writing, because I certainly do not just sit down and plunk out a post. Well, it often looks like that if you're an outside observer1. But that's only what's visible. How I write The very first piece of any blog post for me is an idea, some inspiration, something I want to share. These ideas come from a variety of places. Some of them are from conversations with friends or coworkers. Others come from problems I'm solving in my own code. Or they come from things I'm reading. Very rarely, they come from just thinking about things, but those are other sources with the connection hidden by the passage of time. After an idea comes to me, I try to capture it quickly. If I don't, it's probably gone! I store these ideas in a note in Obsidian, which currently has 162 ideas in it2. I format this file as a bulleted list, with minimal categorization so that the friction for adding something new is as low as possible. When I revisit this list to plan things to write (I do this every few weeks), I'll remove things which are either completed or which I'm confident I am not interested in anymore. Ideas which are promoted from "want to write" to "definitely going to write" then get moved into my primary task tracking system, LunaTask. When I start typing an article, I move it from "later" or "next" to "in progress". But in reality, I start writing an article far before I start typing it. See, the thing is, I'm almost always thinking about topics I'm going to write about. Maybe this is an element of having ADHD, or maybe it's from my obsessive interests and my deep diving into things I'm curious about. But it started happening more when I started writing on a schedule. By writing on a schedule, having to publish weekly, I've gotten in the habit of thinking about things so that I can hit the ground running when I sit down to type. Once I've picked out an idea, then it sits in the back of my head and some background processing happens. Usually I'm not crystal clear on what I want to say on a topic, so that background process churns through it. After figuring out what I want to say, I move onto a little more active thought on how I want to say it and structure it. This happens while I'm on a run or a walk, while I'm on coffee breaks, between exercises I'm working on for my music lessons. There's a lot of background processing between snatches of active effort. Piece by piece, it crystallizes in my mind and I figure out what I want to say and how to say it. Then, finally, I sit at the keyboard. And this is where it really looks like I just sit down and write posts in one quick sitting. That's because by then, the ideas are fully formed and it's a matter of writing the words out—and after a few years of that, it's something I got pretty quick at. Take this blog post for example. I received the initial email on January 1st, and it sat in my inbox for a few days before I could read it and digest it. I started to write a reply, but realized it would work as a blog post. So it ended up in background processing for a week, then I started actively thinking about what I wanted to write. At that point, I created a blog post file with section headings as an outline. This post ended up being delayed a bit, since I had to practice content-driven development for a project that has a self-imposed deadline. But the core writing (though not the typing) was done in the week after opening the original email. And then when I finally sat down to write it, it was two 20-minute sessions of typing out the words3. Editing and publishing After the first draft of a post is written, there's a lot of detail work remaining. This draft is usually in the approximate shape of the final post, but it may be missing sections or have too much in some. I'll take this time to do a quick read over it by myself. Here I'm not checking for spelling errors, but checking if the structure is good and if it needs major work, or just copy edits. If I'm unsure of some aspects of a post, I ask for feedback. I'll reach out to one or two friends who I think would have useful feedback and would enjoy reading it early, and ask them if they can read it. This request comes with specific feedback requests, since those are easier to fulfill then a broad "what do you think?" These are something along the lines of "was it clear? what parts stuck out to you positively or negatively? is there anything you found unclear or inaccurate?" Once people get me feedback, I add an acknowledgement for them (with explicit consent for if/how to share their name and where to link). After I'm more sure of the structure and content of a post, I'll go through and do copy edits. I read through it, with a spellchecker enabled4, and fix any misspellings and improve the wording of sentences. Then it's just the final details. I write up the blurb that goes in my newsletter and on social media (Mastodon, Bluesky, and LinkedIn, currently). I make sure the date is correct, the title is a decent one, and the slug mostly matches the title. And I make sure I did do things like acknowledgements and spellchecking. Here's the full checklist I use for every post before publishing. - [ ] Edited? - [ ] Newsletter blurb written? - [ ] Spellchecked? - [ ] Is the date correct? - [ ] Is the title updated? - [ ] Does the slug match the title? - [ ] Are tags set? - [ ] Draft setting removed? - [ ] Are acknowledgements added? Once that checklist is complete, it's ready to go! That means that on Monday morning, I just have to run make deploy and it'll build and push out the article. Making it sustainable I've been writing at least one post a week since September 2022—over two years at this point, and about 200,000 words. I've avoided burning out on it, so far. That's an interesting thing, since I've burned out on personal projects in the past. What makes this different? One aspect is that it's something that's very enjoyable for me. I like writing, and the process of it. I've always liked writing, and having an outlet for it is highly motivating for me. I thrive in structure, so the self-imposed structure of publishing every week is helpful. This structure makes me abandon perfection and find smaller pieces that I can publish in a shorter amount of time, instead of clinging to a big idea and shipping all of it at once, or never. This is where content-driven development comes in for me, and the consistent schedule also leads me to create inspiration. I also don't put pressure on myself besides the deadline. That's the only immovable thing. Everything else—length, content, even quality5—is flexible. Some of my earliest posts from 2022 are of the form "here's what I did this week!" which got me into a consistent rhythm. The most important thing for me is to keep it fun. If I'm not finding something fun, I just move on to a different post or a different topic. I have some posts that would be good but have sat in my backlog for over a year, waiting to be written. Whenever I sit down to write those, my brain decides to find a bunch of other, better, posts to write instead! So far, it's been fun and motivating to write weekly. If that ever stops, and it becomes a job and something I dread, I'll change the format to be something that works better for me instead! 1 If this is what it looks like then hey, stop peeking through my window. 2 I keep them in a bulleted list, each starting with -, so I can find the count via: grep "\s*-" 'Blog post ideas.md' | wc -l 3 Drafting documents is where I feel like my typing speed is actually a real benefit. On a typing test this evening, I got 99% accuracy at 120wpm. This lets me get through a lot of words quickly. This is a big plus for me both as a writer and as a principal engineer. 4 I leave my spellchecker disabled the vast majority of the time, since the squiggles are distracting! It's not a big deal to misspell things most of the time, and I'd rather be able to focus on getting words out than noticing each mistake as I make it—talk about discouraging! 5 That said, I think it's hard to judge your own quality in the moment. As writers, we can be very critical of ourselves. We think we wrote something boring but others find it interesting. Or something we think is quite clever, others find uninspiring. Sometimes, when I push out something I think is lazy and quick and low-quality, I'm surprised to find a very eager reception.

a month ago 39 votes

More in programming

When to give up

Most of our cultural virtues, celebrated heroes, and catchy slogans align with the idea of "never give up". That's a good default! Most people are inclined to give up too easily, as soon as the going gets hard. But it's also worth remembering that sometimes you really should fold, admit defeat, and accept that your plan didn't work out. But how to distinguish between a bad plan and insufficient effort? It's not easy. Plenty of plans look foolish at first glance, especially to people without skin in the game. That's the essence of a disruptive startup: The idea ought to look a bit daft at first glance or it probably doesn't carry the counter-intuitive kernel needed to really pop. Yet it's also obviously true that not every daft idea holds the potential to be a disruptive startup. That's why even the best venture capital investors in the world are wrong far more than they're right. Not because they aren't smart, but because nobody is smart enough to predict (the disruption of) the future consistently. The best they can do is make long bets, and then hope enough of them pay off to fund the ones that don't. So far, so logical, so conventional. A million words have been written by a million VCs about how their shrewd eyes let them see those hidden disruptive kernels before anyone else could. Good for them. What I'm more interested in knowing more about is how and when you pivot from a promising bet to folding your hand. When do you accept that no amount of additional effort is going to get that turkey to soar? I'm asking because I don't have any great heuristics here, and I'd really like to know! Because the ability to fold your hand, and live to play your remaining chips another day, isn't just about startups. It's also about individual projects. It's about work methods. Hell, it's even about politics and societies at large. I'll give you just one small example. In 2017, Rails 5.1 shipped with new tooling for doing end-to-end system tests, using a headless browser to validate the functionality, as a user would in their own browser. Since then, we've spent an enormous amount of time and effort trying to make this approach work. Far too much time, if you ask me now. This year, we finished our decision to fold, and to give up on using these types of system tests on the scale we had previously thought made sense. In fact, just last week, we deleted 5,000 lines of code from the Basecamp code base by dropping literally all the system tests that we had carried so diligently for all these years. I really like this example, because it draws parallels to investing and entrepreneurship so well. The problem with our approach to system tests wasn't that it didn't work at all. If that had been the case, bailing on the approach would have been a no brainer long ago. The trouble was that it sorta-kinda did work! Some of the time. With great effort. But ultimately wasn't worth the squeeze. I've seen this trap snap on startups time and again. The idea finds some traction. Enough for the founders to muddle through for years and years. Stuck with an idea that sorta-kinda does work, but not well enough to be worth a decade of their life. That's a tragic trap. The only antidote I've found to this on the development side is time boxing. Programmers are just as liable as anyone to believe a flawed design can work if given just a bit more time. And then a bit more. And then just double of what we've already spent. The time box provides a hard stop. In Shape Up, it's six weeks. Do or die. Ship or don't. That works. But what's the right amount of time to give a startup or a methodology or a societal policy? There's obviously no universal answer, but I'd argue that whatever the answer, it's "less than you think, less than you want". Having the grit to stick with the effort when the going gets hard is a key trait of successful people. But having the humility to give up on good bets turned bad might be just as important.

11 hours ago 3 votes
Humanity's Last Exam

Humanity's Last Exam by Center for AI Safety (CAIS) and Scale AI

9 hours ago 3 votes
Cosmetic updates to this site

As well as changing the way I organise my writing, last year I made some cosmetic improvements to this site. I design everything on this site myself, and I write the CSS by hand – I don’t use any third-party styles or frameworks. I don’t have any design training, and I don’t do design professionally, so I use this site as a place to learn and practice my design skills. It’s a continual work-in-progress, but I’d like to think it’s getting better over time. I design this site for readers. I write long, text-heavy posts with the occasional illustration or diagram, so I want something that will be comfortable to read and look good on a wide variety of browsers and devices. I get a lot of that “for free” by using semantic HTML and the default styles – most of my CSS is just cosmetic. Let’s go through some of the changes. Cleaning up the link styles This is what links used to look like: Every page has a tint colour, and then I was deriving different shades to style different links – a darker shade for visited links, a lighter shade for visited links in dark mode, and a background that appears on hover. I’m generating these new colours programatically, and I was so proud of getting that code working that I didn’t stop to think whether it was a good idea. In hindsight, I see several issues. The tint colour is meant to give the page a consistent visual appearance, but the different shades diluted that effect. I don’t think their meaning was especially obvious. How many readers ever worked it out? And the hover styles are actively unhelpful – just as you hover over a link you’re interested in, I’m making it harder to read! (At least in light mode – in dark mode, the hover style is barely legible.) One thing I noticed is that for certain tint colours, the “visited” colour I generated was barely distinguishable from the text colour. So I decided to lean into that in the new link styles: visited links are now the same colour as regular text. This new set of styles feels more coherent. I’m only using one shade of the tint colour, and I think the meaning is a bit clearer – only new-to-you links will get the pop of colour to stand out from the rest of the text. I’m happy to rely on underlines for the links you’ve already visited. And when you hover, the thick underline means you can see where you are, but the link text remains readable. Swapping out the font I swapped out the font, replacing Georgia with Charter. The difference is subtle, so I’d be surprised if anyone noticed: I’ve always used web safe fonts for this site – the fonts that are built into web browsers, and don’t need to be downloaded first. I’ve played with custom fonts from time to time, but there’s no font I like more enough to justify the hassle of loading a custom font. I still like Georgia, but I felt it was showing its age – it was designed in 1993 to look good on low-resolution screens, but looks a little chunky on modern displays. I think Charter looks nicer on high-resolution screens, but if you don’t have it installed then I fall back to Georgia. Making all the roundrects consistent I use a lot of rounded rectangles for components on this site, including article cards, blockquotes, and code blocks. For a long time they had similar but not identical styles, because I designed them all at different times. There were weird inconsistencies. For example, why does one roundrect have a 2px border, but another one is 3px? These are small details that nobody will ever notice directly, but undermine the sense of visual together-ness. I’ve done a complete overhaul of these styles, to make everything look more consistent. I’m leaning heavily on CSS variables, a relatively new CSS feature that I’ve really come to like. Variables make it much easier to use consistent values in different rules. I also tweaked the appearance: I’ve removed another two shades of the tint colour. (Yes, those shades were different from the ones used in links.) Colour draws your attention, so I’m trying to use it more carefully. A link says “click here”. A heading says “start here”. What does a blockquote or code snippet say? It’s just part of the text, so it shouldn’t be grabbing your attention. I think the neutral background also makes the syntax highlighting easier to read, because the tint colour isn’t clashing with the code colours. I could probably consolidate the shades of grey I’m using, but that’s a task for another day. I also removed the left indent on blockquotes and code blocks – I think it looks nicer to have a flush left edge for everything, and it means you can read more text on mobile screens. (That’s where I really felt the issues with the old design.) What’s next? By tidying up the design and reducing the number of unique elements, I’ve got a bit of room to add something new. For a while now I’ve wanted a place at the bottom of posts for common actions, or links to related and follow-up posts. As I do more and more long-form, reflective writing, I want to be able to say “if you liked this, you should read this too”. I want something that catches your eye, but doesn’t distract from the article you’re already reading. Louie Mantia has a version of this that I quite like: I’ve held off designing this because the existing pages felt too busy, but now I feel like I have space to add this – there aren’t as many clashing colours and components to compete for your attention. I’m still sketching out designs – my current idea is my rounded rectangle blocks, but with a coloured border instead of a subtle grey, but when I did a prototype, I feel like it’s missing something. I need to try a few more ideas. Watch this space! [If the formatting of this post looks odd in your feed reader, visit the original article]

an hour ago 1 votes
Five Kinds of Nondeterminism

No newsletter next week, I'm teaching a TLA+ workshop. Speaking of which: I spend a lot of time thinking about formal methods (and TLA+ specifically) because it's where the source of almost all my revenue. But I don't share most of the details because 90% of my readers don't use FM and never will. I think it's more interesting to talk about ideas from FM that would be useful to people outside that field. For example, the idea of "property strength" translates to the idea that some tests are stronger than others. Another possible export is how FM approaches nondeterminism. A nondeterministic algorithm is one that, from the same starting conditions, has multiple possible outputs. This is nondeterministic: # Pseudocode def f() { return rand()+1; } When specifying systems, I may not encounter nondeterminism more often than in real systems, but I am definitely more aware of its presence. Modeling nondeterminism is a core part of formal specification. I mentally categorize nondeterminism into five buckets. Caveat, this is specifically about nondeterminism from the perspective of system modeling, not computer science as a whole. If I tried to include stuff on NFAs and amb operations this would be twice as long.1 1. True Randomness Programs that literally make calls to a random function and then use the results. This the simplest type of nondeterminism and one of the most ubiquitous. Most of the time, random isn't truly nondeterministic. Most of the time computer randomness is actually pseudorandom, meaning we seed a deterministic algorithm that behaves "randomly-enough" for some use. You could "lift" a nondeterministic random function into a deterministic one by adding a fixed seed to the starting state. # Python from random import random, seed def f(x): seed(x) return random() >>> f(3) 0.23796462709189137 >>> f(3) 0.23796462709189137 Often we don't do this because the point of randomness is to provide nondeterminism! We deliberately abstract out the starting state of the seed from our program, because it's easier to think about it as locally nondeterministic. (There's also "true" randomness, like using thermal noise as an entropy source, which I think are mainly used for cryptography and seeding PRNGs.) Most formal specification languages don't deal with randomness (though some deal with probability more broadly). Instead, we treat it as a nondeterministic choice: # software if rand > 0.001 then return a else crash # specification either return a or crash This is because we're looking at worst-case scenarios, so it doesn't matter if crash happens 50% of the time or 0.0001% of the time, it's still possible. 2. Concurrency # Pseudocode global x = 1, y = 0; def thread1() { x++; x++; x++; } def thread2() { y := x; } If thread1() and thread2() run sequentially, then (assuming the sequence is fixed) the final value of y is deterministic. If the two functions are started and run simultaneously, then depending on when thread2 executes y can be 1, 2, 3, or 4. Both functions are locally sequential, but running them concurrently leads to global nondeterminism. Concurrency is arguably the most dramatic source of nondeterminism. Small amounts of concurrency lead to huge explosions in the state space. We have words for the specific kinds of nondeterminism caused by concurrency, like "race condition" and "dirty write". Often we think about it as a separate topic from nondeterminism. To some extent it "overshadows" the other kinds: I have a much easier time teaching students about concurrency in models than nondeterminism in models. Many formal specification languages have special syntax/machinery for the concurrent aspects of a system, and generic syntax for other kinds of nondeterminism. In P that's choose. Others don't special-case concurrency, instead representing as it as nondeterministic choices by a global coordinator. This more flexible but also more inconvenient, as you have to implement process-local sequencing code yourself. 3. User Input One of the most famous and influential programming books is The C Programming Language by Kernighan and Ritchie. The first example of a nondeterministic program appears on page 14: For the newsletter readers who get text only emails,2 here's the program: #include /* copy input to output; 1st version */ main() { int c; c = getchar(); while (c != EOF) { putchar(c); c = getchar(); } } Yup, that's nondeterministic. Because the user can enter any string, any call of main() could have any output, meaning the number of possible outcomes is infinity. Okay that seems a little cheap, and I think it's because we tend to think of determinism in terms of how the user experiences the program. Yes, main() has an infinite number of user inputs, but for each input the user will experience only one possible output. It starts to feel more nondeterministic when modeling a long-standing system that's reacting to user input, for example a server that runs a script whenever the user uploads a file. This can be modeled with nondeterminism and concurrency: We have one execution that's the system, and one nondeterministic execution that represents the effects of our user. (One intrusive thought I sometimes have: any "yes/no" dialogue actually has three outcomes: yes, no, or the user getting up and walking away without picking a choice, permanently stalling the execution.) 4. External forces The more general version of "user input": anything where either 1) some part of the execution outcome depends on retrieving external information, or 2) the external world can change some state outside of your system. I call the distinction between internal and external components of the system the world and the machine. Simple examples: code that at some point reads an external temperature sensor. Unrelated code running on a system which quits programs if it gets too hot. API requests to a third party vendor. Code processing files but users can delete files before the script gets to them. Like with PRNGs, some of these cases don't have to be nondeterministic; we can argue that "the temperature" should be a virtual input into the function. Like with PRNGs, we treat it as nondeterministic because it's useful to think in that way. Also, what if the temperature changes between starting a function and reading it? External forces are also a source of nondeterminism as uncertainty. Measurements in the real world often comes with errors, so repeating a measurement twice can give two different answers. Sometimes operations fail for no discernable reason, or for a non-programmatic reason (like something physically blocks the sensor). All of these situations can be modeled in the same way as user input: a concurrent execution making nondeterministic choices. 5. Abstraction This is where nondeterminism in system models and in "real software" differ the most. I said earlier that pseudorandomness is arguably deterministic, but we abstract it into nondeterminism. More generally, nondeterminism hides implementation details of deterministic processes. In one consulting project, we had a machine that received a message, parsed a lot of data from the message, went into a complicated workflow, and then entered one of three states. The final state was totally deterministic on the content of the message, but the actual process of determining that final state took tons and tons of code. None of that mattered at the scope we were modeling, so we abstracted it all away: "on receiving message, nondeterministically enter state A, B, or C." Doing this makes the system easier to model. It also makes the model more sensitive to possible errors. What if the workflow is bugged and sends us to the wrong state? That's already covered by the nondeterministic choice! Nondeterministic abstraction gives us the potential to pick the worst-case scenario for our system, so we can prove it's robust even under those conditions. I know I beat the "nondeterminism as abstraction" drum a whole lot but that's because it's the insight from formal methods I personally value the most, that nondeterminism is a powerful tool to simplify reasoning about things. You can see the same approach in how I approach modeling users and external forces: complex realities black-boxed and simplified into nondeterministic forces on the system. Anyway, I hope this collection of ideas I got from formal methods are useful to my broader readership. Lemme know if it somehow helps you out! I realized after writing this that I already talked wrote an essay about nondeterminism in formal specification just under a year ago. I hope this one covers enough new ground to be interesting! ↩ There is a surprising number of you. ↩

yesterday 6 votes
Europe must become dangerous again

Trump is doing Europe a favor by revealing the true cost of its impotency. Because, in many ways, he has the manners and the honesty of a child. A kid will just blurt out in the supermarket "why is that lady so fat, mommy?". That's not a polite thing to ask within earshot of said lady, but it might well be a fair question and a true observation! Trump is just as blunt when he essentially asks: "Why is Europe so weak?". Because Europe is weak, spiritually and militarily, in the face of Russia. It's that inherent weakness that's breeding the delusion that Russia is at once both on its last legs, about to lose the war against Ukraine any second now, and also the all-potent superpower that could take over all of Europe, if we don't start World Word III to counter it. This is not a coherent position. If you want peace, you must be strong. The big cats in the international jungle don't stick to a rules-based order purely out of higher principles, but out of self-preservation. And they can smell weakness like a tiger smells blood. This goes for Europe too. All too happy to lecture weaker countries they do not fear on high-minded ideals of democracy and free speech, while standing aghast and weeping powerlessly when someone stronger returns the favor. I'm not saying that this is right, in some abstract moral sense. I like the idea of a rules-based order. I like the idea of territorial sovereignty. I even like the idea that the normal exchanges between countries isn't as blunt and honest as those of a child in the supermarket. But what I like and "what is" need separating. Europe simply can't have it both ways. Be weak militarily, utterly dependent on an American security guarantee, and also expect a seat at the big-cat table. These positions are incompatible. You either get your peace dividend -- and the freedom to squander it on net-zero nonsense -- or you get to have a say in how the world around you is organized. Which brings us back to Trump doing Europe a favor. For all his bluster and bullying, America is still a benign force in its relation to Europe. We're being punked by someone from our own alliance. That's a cheap way of learning the lesson that weakness, impotence, and peace-dividend thinking is a short-term strategy. Russia could teach Europe a far more costly lesson. So too China. All that to say is that Europe must heed the rude awakening from our cowboy friends across the Atlantic. They may be crude, they may be curt, but by golly, they do have a point. Get jacked, Europe, and you'll no longer get punked. Stay feeble, Europe, and the indignities won't stop with being snubbed in Saudi Arabia.

yesterday 3 votes