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Here’s Jony Ive talking to Patrick Collison about measurement and numbers: People generally want to talk about product attributes that you can measure easily with a number…schedule, costs, speed, weight, anything where you can generally agree that six is a bigger number than two He says he used to get mad at how often people around him focused on the numbers of the work over other attributes of the work. But after giving it more thought, he now has a more generous interpretation of why we do this: because we want relate to each other, understand each other, and be inclusive of one another. There are many things we can’t agree on, but it’s likely we can agree that six is bigger than two. And so in this capacity, numbers become a tool for communicating with each other, albeit a kind of least common denominator — e.g. “I don’t agree with you at all, but I can’t argue that 134 is bigger than 87.” This is conducive to a culture where we spend all our time talking about attributes we can easily measure (because then we can easily communicate and work together) and results in a belief that the only things that matter are those which can be measured. People will give lip service to that not being the case, e.g. “We know there are things that can’t be measured that are important.” But the reality ends up being: only that which can be assigned a number gets managed, and that which gets managed is imbued with importance because it is allotted our time, attention, and care. This reminds me of the story of the judgement of King Solomon, an archetypal story found in cultures around the world. Here’s the story as summarized on Wikipedia: Solomon ruled between two women who both claimed to be the mother of a child. Solomon ordered the baby be cut in half, with each woman to receive one half. The first woman accepted the compromise as fair, but the second begged Solomon to give the baby to her rival, preferring the baby to live, even without her. Solomon ordered the baby given to the second woman, as her love was selfless, as opposed to the first woman's selfish disregard for the baby's actual well-being In an attempt to resolve the friction between two individuals, an appeal was made to numbers as an arbiter. We can’t agree on who the mother is, so let’s make it a numbers problem. Reduce the baby to a number and we can agree! But that doesn’t work very well, does it? I think there is a level of existence where measurement and numbers are a sound guide, where two and two make four and two halves make a whole. But, as humans, there is another level of existence where mathematical propositions don’t translate. A baby is not a quantity. A baby is an entity. Take a whole baby and divide it up by a sword and you do not half two halves of a baby. I am not a number. I’m an individual. Indivisible. What does this all have to do with software? Software is for us as humans, as individuals, and because of that I believe there is an aspect of its nature where metrics can’t take you.cIn fact, not only will numbers not guide you, they may actually misguide you. I think Robin Rendle articulated this well in his piece “Trust the vibes”: [numbers] are not representative of human experience or human behavior and can’t tell you anything about beauty or harmony or how to be funny or what to do next and then how to do it. Wisdom is knowing when to use numbers and when to use something else. Email · Mastodon · Bluesky
Exploring diagram.website, I came across The Computer is a Feeling by Tim Hwang and Omar Rizwan: the modern internet exerts a tyranny over our imagination. The internet and its commercial power has sculpted the computer-device. It's become the terrain of flat, uniform, common platforms and protocols, not eccentric, local, idiosyncratic ones. Before computers were connected together, they were primarily personal. Once connected, they became primarily social. The purpose of the computer shifted to become social over personal. The triumph of the internet has also impoverished our sense of computers as a tool for private exploration rather than public expression. The pre-network computer has no utility except as a kind of personal notebook, the post-network computer demotes this to a secondary purpose. Smartphones are indisputably the personal computer. And yet, while being so intimately personal, they’re also the largest distribution of behavior-modification devices the world has ever seen. We all willing carry around in our pockets a device whose content is largely designed to modify our behavior and extract our time and money. Making “computer” mean computer-feelings and not computer-devices shifts the boundaries of what is captured by the word. It removes a great many things – smartphones, language models, “social” “media” – from the domain of the computational. It also welcomes a great many things – notebooks, papercraft, diary, kitchen – back into the domain of the computational. I love the feeling of a personal computer, one whose purpose primarily resides in the domain of the individual and secondarily supports the social. It’s part of what I love about the some of the ideas embedded in local-first, which start from the principle of owning and prioritizing what you do on your computer first and foremost, and then secondarily syncing that to other computers for the use of others. Email · Mastodon · Bluesky
After publishing my Analysis of Links From The White House’s “Wire” Website, Tina Nguyen, political correspondent at The Verge, reached out with some questions. Her questions made me realize that the numbers in my analysis weren’t quite correct (I wasn’t de-depulicating links across days, so I fixed that problem). More pointedly, she asked about the most popular domain the White House was linking to: YouTube. Specifically, were the links to YouTube 1) independent content creators, 2) the White House itself, or 3) a mix. A great question. I didn’t know the answer but wanted to find out. A little JavaScript code in my spreadsheet and boom, I had all the YouTube links in one place. I couldn’t really discern from the links themselves what I was looking at. A number of them were to the /live/ subpath, meaning I was looking at links to live streaming events. But most of the others were YouTube’s standard /watch?v=:id which leaves the content and channel behind the URL opaque. The only real way to know was to click through to each one. I did a random sampling and found most of the ones I clicked on all went to The White House’s own YouTube channel. I told Tina as much, sent here the data I had, and she reported on it in an article at The Verge. Tina’s question did get me wondering: precisely how many of those links are to the White House’s own YouTube channel vs. other content creators? Once again, writing scripts that process data, talk to APIs, and put it all into 2-dimensional tables in a spreadsheet was super handy. I looked at all the YouTube links, extracted the video ID, then queried the YouTube API for information about the video (like what channel it belongs to). Once I had the script working as expected for a single cell, it was easy to do the spreadsheet thing where you just “drag down” to autocomplete all the other cells with video IDs. The result? From May 8th to July 6th there were 78 links to YouTube from wh.gov/wire, which breaks down as follows: 73 links to videos on the White House’s own YouTube channel 2 links to videos on the channel “Department of Defense” 1 link to a video on the channel “Pod Force One with Miranda Devine” 1 link to a video on the channel “Breitbart News” 1 link to a video that has since been taken down “due to a copyright claim by Sony Music Publishing” (so I’m not sure whose channel that was) Email · Mastodon · Bluesky
There’s a video on YouTube from “Technology Connections” — who I’ve never heard of or watched until now — called Algorithms are breaking how we think. I learned of this video from Gedeon Maheux of The Iconfactory fame. Speaking in the context of why they made Tapestry, he said the ideas in this video would be their manifesto. So I gave it a watch. Generally speaking, the video asks: Does anyone care to have a self-directed experience online, or with a computer more generally? I'm not sure how infrequently we’re actually deciding for ourselves these days [how we decide what we want to see, watch, and do on the internet] Ironically we spend more time than ever on computing devices, but less time than ever curating our own experiences with them. Which — again ironically — is the inverse of many things in our lives. Generally speaking, the more time we spend with something, the more we invest in making it our own — customizing it to our own idiosyncrasies. But how much time do you spend curating, customizing, and personalizing your digital experience? (If you’re reading this in an RSS reader, high five!) I’m not talking about “I liked that post, or saved that video, so the algorithm is personalizing things for me”. Do you know what to get yourself more of? Do you know where to find it? Do you even ask yourself these questions? “That sounds like too much work” you might say. And you’re right, it is work. As the guy in the video says: I'm one of those weirdos who think the most rewarding things in life take effort Me too. Email · Mastodon · Bluesky
More in programming
I'm a big (neo)vim buff. My config is over 1500 lines and I regularly write new scripts. I recently ported my neovim config to a new laptop. Before then, I was using VSCode to write, and when I switched back I immediately saw a big gain in productivity. People often pooh-pooh vim (and other assistive writing technologies) by saying that writing code isn't the bottleneck in software development. Reading, understanding, and thinking through code is! Now I don't know how true this actually is in practice, because empirical studies of time spent coding are all over the place. Most of them, like this study, track time spent in the editor but don't distinguish between time spent reading code and time spent writing code. The only one I found that separates them was this study. It finds that developers spend only 5% of their time editing. It also finds they spend 14% of their time moving or resizing editor windows, so I don't know how clean their data is. But I have a bigger problem with "writing is not the bottleneck": when I think of a bottleneck, I imagine that no amount of improvement will lead to productivity gains. Like if a program is bottlenecked on the network, it isn't going to get noticeably faster with 100x more ram or compute. But being able to type code 100x faster, even with without corresponding improvements to reading and imagining code, would be huge. We'll assume the average developer writes at 80 words per minute, at five characters a word, for 400 characters a minute.What could we do if we instead wrote at 8,000 words/40k characters a minute? Writing fast Boilerplate is trivial Why do people like type inference? Because writing all of the types manually is annoying. Why don't people like boilerplate? Because it's annoying to write every damn time. Programmers like features that help them write less! That's not a problem if you can write all of the boilerplate in 0.1 seconds. You still have the problem of reading boilerplate heavy code, but you can use the remaining 0.9 seconds to churn out an extension that parses the file and presents the boilerplate in a more legible fashion. We can write more tooling This is something I've noticed with LLMs: when I can churn out crappy code as a free action, I use that to write lots of tools that assist me in writing good code. Even if I'm bottlenecked on a large program, I can still quickly write a script that helps me with something. Most of these aren't things I would have written because they'd take too long to write! Again, not the best comparison, because LLMs also shortcut learning the relevant APIs, so also optimize the "understanding code" part. Then again, if I could type real fast I could more quickly whip up experiments on new apis to learn them faster. We can do practices that slow us down in the short-term Something like test-driven development significantly slows down how fast you write production code, because you have to spend a lot more time writing test code. Pair programming trades speed of writing code for speed of understanding code. A two-order-of-magnitude writing speedup makes both of them effectively free. Or, if you're not an eXtreme Programming fan, you can more easily follow the The Power of Ten Rules and blanket your code with contracts and assertions. We could do more speculative editing This is probably the biggest difference in how we'd work if we could write 100x faster: it'd be much easier to try changes to the code to see if they're good ideas in the first place. How often have I tried optimizing something, only to find out it didn't make a difference? How often have I done a refactoring only to end up with lower-quality code overall? Too often. Over time it makes me prefer to try things that I know will work, and only "speculatively edit" when I think it be a fast change. If I could code 100x faster it would absolutely lead to me trying more speculative edits. This is especially big because I believe that lots of speculative edits are high-risk, high-reward: given 50 things we could do to the code, 49 won't make a difference and one will be a major improvement. If I only have time to try five things, I have a 10% chance of hitting the jackpot. If I can try 500 things I will get that reward every single time. Processes are built off constraints There are just a few ideas I came up with; there are probably others. Most of them, I suspect, will share the same property in common: they change the process of writing code to leverage the speedup. I can totally believe that a large speedup would not remove a bottleneck in the processes we currently use to write code. But that's because those processes are developed work within our existing constraints. Remove a constraint and new processes become possible. The way I see it, if our current process produces 1 Utils of Software / day, a 100x writing speedup might lead to only 1.5 UoS/day. But there are other processes that produce only 0.5 UoS/d because they are bottlenecked on writing speed. A 100x speedup would lead to 10 UoS/day. The problem with all of this that 100x speedup isn't realistic, and it's not obvious whether a 2x improvement would lead to better processes. Then again, one of the first custom vim function scripts I wrote was an aid to writing unit tests in a particular codebase, and it lead to me writing a lot more tests. So maybe even a 2x speedup is going to be speed things up, too. Patreon Stuff I wrote a couple of TLA+ specs to show how to model fork-join algorithms. I'm planning on eventually writing them up for my blog/learntla but it'll be a while, so if you want to see them in the meantime I put them up on Patreon.
There's no country on earth that does hype better than America. It's one of the most appealing aspects about being here. People are genuinely excited about the future and never stop searching for better ways to work, live, entertain, and profit. There's a unique critical mass in the US accelerating and celebrating tomorrow. The contrast to Europe couldn't be greater. Most Europeans are allergic to anything that even smells like a commercial promise of a better tomorrow. "Hype" is universally used as a term to ridicule anyone who dares to be excited about something new, something different. Only a fool would believe that real progress is possible! This is cultural bedrock. The fault lines have been settling for generations. It'll take an earthquake to move them. You see this in AI, you saw it in the Internet. Europeans are just as smart, just as inventive as their American brethren, but they don't do hype, so they're rarely the ones able to sell the sizzle that public opinion requires to shift its vision for tomorrow. To say I have a complicated relationship with venture capital is putting it mildly. I've spent a career proving the counter narrative. Proving that you can build and bootstrap an incredible business without investor money, still leave a dent in the universe, while enjoying the spoils of capitalism. And yet... I must admit that the excesses of venture capital are integral to this uniquely American advantage on hype. The lavish overspending during the dot-com boom led directly to a spectacular bust, but it also built the foundation of the internet we all enjoy today. Pets.com and Webvan flamed out such that Amazon and Shopify could transform ecommerce out of the ashes. We're in the thick of peak hype on AI right now. Fantastical sums are chasing AGI along with every dumb derivative mirage along the way. The most outrageous claims are being put forth on the daily. It's easy to look at that spectacle with European eyes and roll them. Some of it is pretty cringe! But I think that would be a mistake. You don't have to throw away your critical reasoning to accept that in the face of unknown potential, optimism beats pessimism. We all have to believe in something, and you're much better off believing that things can get better than not. Americans fundamentally believe this. They believe the hype, so they make it come to fruition. Not every time, not all of them, but more of them, more of the time than any other country in the world. That really is exceptional.
A hands-on guide to general-purpose registers and data movement in x86-64
In the early 1990s, three companies pioneered online transactions, facing challenges of security and user accessibility. They are hardly known today. The post Three attempts at making payments secure appeared first on The History of the Web.
