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A large part of our civilisation rests on the shoulders of one medieval monk: Thomas Aquinas. Amid the turmoil of life, riddled with wickedness and pain, he would insist that our world is good. And all our success is built on this belief. Note: Before we start, let’s get one thing out of the way: Thomas Aquinas is clearly a Christian thinker, a Saint even. Yet he was also a brilliant philosopher. So even if you consider yourself agnostic or an atheist, stay with me, you will still enjoy his ideas. What is good? Thomas’ argument is rooted in Aristotle’s concept of goodness: Something is good if it fulfills its function. Aristotle had illustrated this idea with a knife. A knife is good to the extent that it cuts well. He made a distinction between an actual knife and its ideal function. That actual thing in your drawer is the existence of a knife. And its ideal function is its essence—what it means to be a knife: to cut well. So everything is separated into its existence and its ideal essence. And this is also true for humans: We have an ideal conception of what the essence of a human […] The post Thomas Aquinas — The world is divine! appeared first on Ralph Ammer.
Should we just live in the moment? In “Matter and Memory” the French philosopher Henri Bergson claims that this is not even possible. 1. Perception is physical First of all: How do we perceive the “current moment” anyway? Bergson suggests that the whole point of perception is action. For example, when some single-cell organism touches an obstacle, it moves away. That is the whole point of perception: to move in the right direction, to find food, to not be food—to survive. Perception serves future action, not insight. Accordingly, our brain is fully embedded in the material world and responds to the movements around it. Bergson refers to such a purely physical reaction as pure perception. Yet he acknowledges that we are more complicated than single-celled organisms. The movements of our environment have to make their way through our complex sensory system with all its twists and turns. And this leaves us more options on how to act. So we don’t just react like a single-celled organism, we can choose from a range of potential movements. But how? We remember. 2. Memory is temporal Bergson distinguishes two kinds of memories: Some memories have become part of our body, they are a […] The post Bergson — Why we live in the past appeared first on Ralph Ammer.
To “animate” means to breathe life into things. In these 5 exercises we make stones come alive. Preparation To get started I suggest this simple setup for you to try at home: Ready? Let’s go! Thinking in time Stop-motion is simple: Take a picture, move the object, take the next picture, move the object, etc. Once you are done, you can play back all those images as a little movie. Tip: You can do the following exercises exactly as shown here or play around with them. Just make sure to have fun! Exercise 1: Timing Turn a stone into a bouncing ball. Start with a stone above the middle of the page and hit the record button. Then move it down a little, take the next frame, move it again, and so on. Once it has reached the bottom, gradually move it up again until it is back to its starting position. Tip: At first you will notice that our steps are too big. As a result the animation plays way too fast! Just start over and make the steps smaller. Another tip: You can make the movement more natural by varying the distances. And you can make the “ball” […] The post A quick beginner’s guide to animation appeared first on Ralph Ammer.
You are awake. You think and you feel. But what is it that is doing all this thinking and feeling? We call it “consciousness” and over 100 years ago the philosopher Edmund Husserl made a bold attempt to uncover its secrets. Subjective experience is private The thing is: Consciousness is not “out there”, it is “in here“. It is personal and subjective. When I say that I like squirrels or that my foot hurts, then you will have to take my word for it. You can’t know what it is like to be me, and I cannot know what it is like to be you. Consciousness can only be observed from the inside, not from the outside. Since we can’t see the world through other peoples’ eyes, their experience remains deeply mysterious to us. Thus we all see the world differently. And this can lead to bitter conflict. Science is based on objective insight One way to overcome such conflict is to take an objective position. We take a neutral view from outside and focus on the things that we can all agree upon. We have learned to see ourselves “from the outside”. In fact, we can build a whole […] The post Edmund Husserl — Consciousness appeared first on Ralph Ammer.
More in programming
The first in a series of posts about doing things the right way
A deep dive into the Action Cache, the CAS, and the security issues that arise from using Bazel with a remote cache but without remote execution
The best engineering teams take control of their tools. They help develop the frameworks and libraries they depend on, and they do this by running production code on edge — the unreleased next version. That's where progress is made, that's where participation matters most. This sounds scary at first. Edge? Isn't that just another word for danger? What if there's a bug?! Yes, what if? Do you think bugs either just magically appear or disappear? No, they're put there by programmers and removed by the very same. If you want bug-free frameworks and libraries, you have to work for it, but if you do, the reward for your responsibility is increased engineering excellence. Take Rails 8.1, as an example. We just released the first beta version at Rails World, but Shopify, GitHub, 37signals, and a handful of other frontier teams have already been running this code in production for almost a year. Of course, there were bugs along the way, but good automated testing and diligent programmers caught virtually all of them before they went to production. It didn't always used to be this way. Once upon a time, I felt like I had one of the only teams running Rails on edge in production. But now two of the most important web apps in the world are doing the same! At an incredible scale and criticality. This has allowed both of them, and the few others with the same frontier ambition, to foster a truly elite engineering culture. One that isn't just a consumer of open source software, but a real-time co-creator. This is a step function in competence and prowess for any team. It's also an incredible motivation boost. When your programmers are able to directly influence the tools they're working with, they're far more likely to do so, and thus they go deeper, learn more, and create connections to experts in the same situation elsewhere. But this requires being able to immediately use the improvements or bug fixes they help devise. It doesn't work if you sit around waiting patiently for the next release before you dare dive in. Far more companies could do this. Far more companies should do this. Whether it's with Ruby, Rails, Omarchy, or whatever you're using, your team could level up by getting more involved, taking responsibility for finding issues on edge, and reaping the reward of excellence in the process. So what are you waiting on?
(I present to you my stream of consciousness on the topic of casing as it applies to the web platform.) I’m reading about the new command and commandfor attributes — which I’m super excited about, declarative behavior invocation in HTML? YES PLEASE!! — and one thing that strikes me is the casing in these APIs. For example, the command attribute has a variety of values in HTML which correspond to APIs in JavaScript. The show-popover attribute value maps to .showPopover() in JavaScript. hide-popover maps to .hidePopover(), etc. So what we have is: lowercase in attribute names e.g. commandfor="..." kebab-case in attribute values e.g. show-popover camelCase for JS counterparts e.g. showPopover() After thinking about this a little more, I remember that HTML attributes names are case insensitive, so the browser will normalize them to lowercase during parsing. Given that, I suppose you could write commandFor="..." but it’s effectively the same. Ok, lowercase attribute names in HTML makes sense. The related popover attributes follow the same convention: popovertarget popovertargetaction And there are many other attribute names in HTML that are lowercase, e.g.: maxlength novalidate contenteditable autocomplete formenctype So that all makes sense. But wait, there are some attribute names with hyphens in them, like aria-label="..." and data-value="...". So why isn’t it command-for="..."? Well, upon further reflection, I suppose those attributes were named that way for extensibility’s sake: they are essentially wildcard attributes that represent a family of attributes that are all under the same namespace: aria-* and data-*. But wait, isn’t that an argument for doing popover-target and popover-target-action? Or command and command-for? But wait (I keep saying that) there are kebab-case attribute names in HTML — like http-equiv on the <meta> tag, or accept-charset on the form tag — but those seem more like legacy exceptions. It seems like the only answer here is: there is no rule. Naming is driven by convention and decisions are made on a case-by-case basis. But if I had to summarize, it would probably be that the default casing for new APIs tends to follow the rules I outlined at the start (and what’s reflected in the new command APIs): lowercase for HTML attributes names kebab-case for HTML attribute values camelCase for JS counterparts Let’s not even get into SVG attribute names We need one of those “bless this mess” signs that we can hang over the World Wide Web. Email · Mastodon · Bluesky
Greetings everyone! You might have noticed that it's September and I don't have the next version of Logic for Programmers ready. As penance, here's ten free copies of the book. So a few months ago I wrote a newsletter about how we use nondeterminism in formal methods. The overarching idea: Nondeterminism is when multiple paths are possible from a starting state. A system preserves a property if it holds on all possible paths. If even one path violates the property, then we have a bug. An intuitive model of this is that for this is that when faced with a nondeterministic choice, the system always makes the worst possible choice. This is sometimes called demonic nondeterminism and is favored in formal methods because we are paranoid to a fault. The opposite would be angelic nondeterminism, where the system always makes the best possible choice. A property then holds if any possible path satisfies that property.1 This is not as common in FM, but it still has its uses! "Players can access the secret level" or "We can always shut down the computer" are reachability properties, that something is possible even if not actually done. In broader computer science research, I'd say that angelic nondeterminism is more popular, due to its widespread use in complexity analysis and programming languages. Complexity Analysis P is the set of all "decision problems" (basically, boolean functions) can be solved in polynomial time: there's an algorithm that's worst-case in O(n), O(n²), O(n³), etc.2 NP is the set of all problems that can be solved in polynomial time by an algorithm with angelic nondeterminism.3 For example, the question "does list l contain x" can be solved in O(1) time by a nondeterministic algorithm: fun is_member(l: List[T], x: T): bool { if l == [] {return false}; guess i in 0..<(len(l)-1); return l[i] == x; } Say call is_member([a, b, c, d], c). The best possible choice would be to guess i = 2, which would correctly return true. Now call is_member([a, b], d). No matter what we guess, the algorithm correctly returns false. and just return false. Ergo, O(1). NP stands for "Nondeterministic Polynomial". (And I just now realized something pretty cool: you can say that P is the set of all problems solvable in polynomial time under demonic nondeterminism, which is a nice parallel between the two classes.) Computer scientists have proven that angelic nondeterminism doesn't give us any more "power": there are no problems solvable with AN that aren't also solvable deterministically. The big question is whether AN is more efficient: it is widely believed, but not proven, that there are problems in NP but not in P. Most famously, "Is there any variable assignment that makes this boolean formula true?" A polynomial AN algorithm is again easy: fun SAT(f(x1, x2, …: bool): bool): bool { N = num_params(f) for i in 1..=num_params(f) { guess x_i in {true, false} } return f(x_1, x_2, …) } The best deterministic algorithms we have to solve the same problem are worst-case exponential with the number of boolean parameters. This a real frustrating problem because real computers don't have angelic nondeterminism, so problems like SAT remain hard. We can solve most "well-behaved" instances of the problem in reasonable time, but the worst-case instances get intractable real fast. Means of Abstraction We can directly turn an AN algorithm into a (possibly much slower) deterministic algorithm, such as by backtracking. This makes AN a pretty good abstraction over what an algorithm is doing. Does the regex (a+b)\1+ match "abaabaabaab"? Yes, if the regex engine nondeterministically guesses that it needs to start at the third letter and make the group aab. How does my PL's regex implementation find that match? I dunno, backtracking or NFA construction or something, I don't need to know the deterministic specifics in order to use the nondeterministic abstraction. Neel Krishnaswami has a great definition of 'declarative language': "any language with a semantics has some nontrivial existential quantifiers in it". I'm not sure if this is identical to saying "a language with an angelic nondeterministic abstraction", but they must be pretty close, and all of his examples match: SQL's selects and joins Parsing DSLs Logic programming's unification Constraint solving On top of that I'd add CSS selectors and planner's actions; all nondeterministic abstractions over a deterministic implementation. He also says that the things programmers hate most in declarative languages are features that "that expose the operational model": constraint solver search strategies, Prolog cuts, regex backreferences, etc. Which again matches my experiences with angelic nondeterminism: I dread features that force me to understand the deterministic implementation. But they're necessary, since P probably != NP and so we need to worry about operational optimizations. Eldritch Nondeterminism If you need to know the ratio of good/bad paths, the number of good paths, or probability, or anything more than "there is a good path" or "there is a bad path", you are beyond the reach of heaven or hell. Angelic and demonic nondeterminism are duals: angelic returns "yes" if some choice: correct and demonic returns "no" if !all choice: correct, which is the same as some choice: !correct. ↩ Pet peeve about Big-O notation: O(n²) is the set of all algorithms that, for sufficiently large problem sizes, grow no faster that quadratically. "Bubblesort has O(n²) complexity" should be written Bubblesort in O(n²), not Bubblesort = O(n²). ↩ To be precise, solvable in polynomial time by a Nondeterministic Turing Machine, a very particular model of computation. We can broadly talk about P and NP without framing everything in terms of Turing machines, but some details of complexity classes (like the existence "weak NP-hardness") kinda need Turing machines to make sense. ↩
