Intended Effect

I never knew what this satellite dish at the corner of Penn Ave and Mathilda St was. The aggressively unlabeled building it was next to suggested something more prosaic than the TV or radio station that I liked to imagine was broadcasting, for some reason, from a ground-level parking lot.

Even in the generally dense east end, Pittsburgh has a real mixture of roughly 60+ year-old pedestrian-focused street-fronting density, and somewhat newer attempts to get with the later 20th century times by creating a more car-friendly landscape. Even now, when most of the architects, neighborhood groups, and city planners would rather skip devoting any more surface area to asphalt, we sometimes get stuck with the decidedly suburban-looking First National Bank branch newly built at the corner of Penn and Negley Avenues. So it was nice that this fairly ugly building with small windows and a large surface parking lot could at least offer a little visual interest in the form of a surprisingly large satellite dish. I’ll miss walking by it.

I haven’t listened to many “general interest” podcasts (or radio shows, or YouTubers) in a while—you know, This American Life, Radio Lab, and their less-famous or non-NPR or more-niche-specific analogs. I’m a curious person, I like learning about things, and I will even admit to enjoying telling other people all about the things I know without them necessarily inviting such a lecture. So what happened?

First, another question: are “unboxing” videos still a a thing? Off the top of my head, I think of them as having started around the time of the early iPhones. They were videos of someone taking a new and generally high-end product out of its packaging. Usually there would be some light editorializing about materials, a dash of plastic film ASMR, and sometimes a brief look at the product itself. But the extent to which these videos did resemble a review was strictly for the purpose of communicating the relative pleasure of experiencing the object purely as a product and not as a tool. That format meant that the only qualification for creating these videos was simply having that hot product before most other people did, and the only thing these videos delivered was the thin, vicarious experience of opening the box.

To me, unboxing videos have always seemed insane. The host was invariably someone without much specific insight into the product category, with YouTube audience thirst oozing out of every pore, and sometimes an undercurrent of desperation spurred by the uncertainty of whether the views will pay enough to justify the expense of purchasing the product. I absolutely recognize the nerdy impulse to dive headfirst into as much content about your interests as possible, but unboxing videos always seemed like a pure “spoiler” to me: congratulations, now if you buy that product yourself, your own reactions will slip into a track already carved out by someone named Josh who is not a fellow obsessive but instead just someone with $1000 and an ambition to make a popular video.

So, yes, to tie this back together, there’s a kind of reporting/essaying common to those podcasts that feels too much like “unboxing the world” to me. Millions of young people will no longer get to have the experience of bumping into the term “desire lines” unprepared! Why? Because there are fleets of self-consciously thoughtful people, armed with microphones, plying the seas of emerging subcultures, niche industries, and overlooked places for anything that could feel like a discovery. Unlike when a friend tells you about something they have recently encountered, each overturned rock is offered with a kind of public act of introspection that seems to close the subject off to further contemplation even while it offers no conclusions. The personal, almost confessional tone of these podcasts becomes more quietly unsettling with each additional episode: learning about epigenetics just blew your mind last week, and now talking to someone from a failed 1960’s commune has you once again awestruck by the complex beauty of existence? Is this a meta-narrative about a personality disorder?

As I have gotten older, moments of genuine wonder—times when something new lets you glimpse a terrain of possibilities—have gotten more rare, and consequently more precious to me. As you age there is more that you (think you) already know, and you also must put in more work to maintain the curious and open mindset that enables these experiences. So I think the strength of my reaction is partly driven by disgust at the formulaic bulk commercialization—however well-intentioned and poorly-compensated—of this kind of feeling. But primarily I stopped listening because however many of those nuggets are still unknown to me, I would prefer to experience discovering them by myself or with friends.

I have been thinking a lot about the internet (the web?) lately, especially vis-a-vis LLMs, and I keep trying and failing to write down my thoughts. So rather than keep attempting to wring a coherent argument out of myself, I’m going to take the coward’s way out and write up some loosely-connected bullet points.

• I’m approximately 40, and nearly all of the decision makers driving the recent AI/LLM explosion are roughly my age or older. I think that if you experienced the late 90’s through iPhone explosion of the web—if you were old enough to experience a need and then (still) flexible enough and curious enough to dive into meeting it with new technology—then LLMs can feel like the apotheosis of the internet. If you are old enough, then you have sat with friends wondering what actor was in a film, or what the name of a musician’s side project was, or how to make guacamole, and been entirely unable to answer the question in that moment. And as time went on you would have experienced asking Lycos or Yahoo or AltaVista or Google about more and subtler things, and been delighted as more and more of them had useful results. I think the magic of living through that transformation established a kind of trust in the internet as a communal body of knowledge (even if most of those now-40-year-olds were also posting nonsense on Something Awful or 4chan).

• That content was coming from a wide variety of sources, too. There were central consolidators of information like Wikipedia and The IMDB, but it was also very common to find your answer on someone’s personal webpage on Geocities or Angelfire, or on a dedicated community / fansite, or a phpBB forum, or one of seemingly innumerable university professors’ websites. My recollection is that simply making a website—any website—was fun, and novel, and seemed like a way to build a presumed-to-be useful skill, so people would set out primarily to learn HTML and only secondarily (at least at first) to share their knowledge about fish keeping or making sourdough or the lyrics of The Doors. The hosting was free, the time was an investment, and beyond “maybe put AdWords on it” there wasn’t much of a business case to be made and thus little in the way of an invisible hand forcing consolidation in the market to provide information about the South Jersey ska-punk scene.

• Now much of that kind of personal content has moved within platforms. Some of those, like Reddit or Fandom, are within view of a Google search, but the most devoted “interest community” activity is now enclosed within Instagram, Facebook, Discord, Telegram, TikTok, etc, etc. Self-hosting an open community on the internet has a lot of challenges (technical, financial, moderation, etc) so this is pretty understandable, but it feels like a tragedy to me. To whit, film photography is seeing a resurgence, but if you Google for help with your parent’s old camera the best results will probably be on Flickr from more than a decade ago, because the relevant subreddits are more casual and there’s no easy way to find the right Discords and Facebook Groups when you are new to the hobby.

• Personally, I think Google would be better off today if they had invested in solving those problems to enable people to keep such conversations happening out in the open. And not only for LLM purposes; search results are terrible now partly because there is so much keyword spam content, but also because there’s scant new hobbyist content (leaving only the 2010 Flickr threads about that hand-me-down Nikon). There is, as people have found, Reddit, but attempts to game Google through spam on Reddit are already testing the dedication of volunteer moderators.
• I hope that LLM-mania will prompt the tech giants to encourage a return of the kind of self-consciously open knowledge sharing that flowered on the early web—and to be clear, I hope they can encourage that by creating financial support for that knowledge sharing in addition to relying on good UX and public spiritedness. But Google has YouTube, Meta has Facebook and Instagram and Threads, and for the moment OpenAI has ambiguous laws and an Uber-style habit of taking first and only asking for permission later if forced to. While it is true that advances in AI make it easier (or at least possible) to get value out of existing pools of data, I think there is something almost mercantilist in the way companies are focused solely on the value of their proprietary datasets. So I don’t think a Google or a Meta will feel that they have anything to gain from enabling the creation and sharing of data that is not exclusive to their own use.
• Reporter James Surowiecki’s The Wisdom of Crowds turned 20 years old this May. I’ve never read it! But I did it hear highly condensed accounts of it in both more and less formal presentations in the Bay Area in the years immediately following its 2004 release. Such crowds were at their wisest when averaging a number, as in guessing the weight of an ox at a county fair (the anecdote which invariably accompanied any mention of the book), or assessing the quality of a restaurant. So for a time people were very interested in things like tagging systems that might offer a way to make anything from LinkedIn resumes to Flickr photos roughly reducible to something that could be navigated and ranked with simple arithmetic.
• I’m no machine learning PhD, but as I understand it the current explosion of LLMs is enabled by a combination of techniques going back to the likes of Word2Vec that can represent text (among other things) as many-dimensional grids of numbers, and the increasing power of graphics cards to process more of those matrices in much less time. So now an LLM can summarize a page of text, and it is similarly a matter of math. But at a product level, I think people (likely my age!) are mistakenly imagining that recipes can be aggregated with the same kind of deterministic Excel math used to summarize movie review scores. One prank pizza recipe can cause subtler havoc than one prank product rating.
• For now, there are broadly two ways that an LLM can answer your question.
  • One, is for the LLM to answer the question “itself”, drawing from its base dataset (which we can shorthand as “the entire web”) and modulated by whatever training or fine-tuning it received (shorthand as showing it example question/ answer pairs, or people giving proposed answers a thumbs up or thumbs down). This is fun and impressive, because it seems like the internet has become sentient, it feels like talking to an all-knowing demigod, and at its best these answers appear to distill the entirety of human knowledge about a subject into a concise response. On the other hand, because the answer is being sieved out of such an enormous soup of data, these responses sometimes exhibit inaccuracies that weren’t present in the source material.
  • The other way (called Retrieval Augmented Generation, or RAG) is for a process to search a body of content for text likely to have the answer, and then have the LLM answer the question drawing only from the text of those sources. This tends to create responses that hew closer to the source text, but it’s a bit less magical because reading a Wikipedia page and summarizing the first paragraph is something most people could just do themselves, and seeing the sources cited reminds people of how much they may not trust Wikipedia, or a given newspaper, or Reddit, or a blogpost.
• Something that I imagine is tantalizing to founders about the Wisdom of Crowds framing is that each individual contribution is presumed to be almost worthless—so Yelp, for example, is providing more value by aggregating than you do by writing your individual review. I like the idea of a universe where there can be millions of individual pages and conversations about (say) film photography, but I think that (perhaps outdated!) view of the internet may play into the idea that none of those non-professional sources are particularly valuable individually, and that an LLM trained on them summarizing an answer out of so much photography text soup is what is really providing value. Meanwhile, if there really are only a handful of sources to draw from, it becomes clearer that they are the actual resource, that they are providing the value—and that they should probably be paid.
• I will say that I think both answering strategies are and will continue to be useful in practice, and that different people may want different kinds of answers to the same questions—I may want the zeitgeist-thru-LLM’s quick answer to what temperature to bake salmon at, but lots of context around what is the best laser printer; you may want the opposite. But if the authentic human conversations remain in closed communities (maybe even moreso in flight from AI), and the display-ad websites disappear along with their Google traffic, and if everywhere on the internet is flooded by okay-ish AI-generated empty content, then I don’t know where new source material is going to come from. It’s genuinely exciting that we’ve achieved the early 2000’s goal of creating the greatest interactive encyclopedia ever (boy did computer nerds love talking about the Primer in Neal Stephenson’s The Diamond Age). But the information ecosystem of the internet will have to evolve if that encyclopedia is going to continue to be updated into the 2030’s.

A kind of cliché-but-true complaint common among programmers in the late 2010’s was that there were too many new JavaScript things every week. Frameworks, libraries, and bits and pieces of tooling relentlessly arrived, exploded in popularity, and then receded like waves on a beach. My sense is that this pace has slowed over the last few years, so I wonder: was this, too, a ZIRP phonemon, and thus a victim of rising interest rates along with other bubbly curiosities like NFTs, direct-to-consumer startups, food delivery discounts, and SPACs?

I’ll admit: I can’t say I’m basing this on anything but anecdotes and vibes. But the vibes were strong, and they were bubbly. People complained about the proliferation of JS widgets not because of the raw number of projects, but because there was a sense that you had to learn and adopt the new hotness (all of which still seem to be going concerns!) in order to be a productive, modern, hirable developer. I think such FOMO is a good indicator of a bubble.

And I think other ZIRP-y factors helped sustain that sense that everyone else was participating in the permanent JavaScript revolution. What could interest rates possibly have to do with JavaScript? Let’s say you have $100 to invest in either a startup that will return a modest 2x your investment in 10 years, or a bank account. If interest rates are 7%, your bank account will also have (very nearly) doubled, and of course it’s much less risky than a startup! If interest rates are 2%, your $100 bank account will only end up about $22 richer after a decade, so you might as well take a chance on Magic Leap. It also means that a big company sitting on piles of cash might as well borrow more, even if they don’t particularly know what to do with it. So all of that is to say: low interest rates meant there was cheap money for startups and tech giants alike.

Startups, for their part, are exactly the kind of fresh start where it really does make sense to try something new and exciting for your interactive demo MVP. If you’re a technical founder with enough of a not-invented-here bias—a bias I’ll admit to being guilty of—then you might well survey the JavaScript landscape and decide that what it lacks is your particular take on solving some problem or other. Here’s that XKCD link you knew was coming.

As for the acronymous tech giants, there’s been recent public accusations that larger firms spent much of the 2010s over-hiring to keep talent both stockpiled for future needs and also safely away from competitors (searches aren’t finding me much beyond VC crank complaints, but I’d also gotten this sense pre-pandemic). Everyone loves a good “paid to do nothing” story, but I think most programmers do want to actually contribute at work. A well-intentioned, ambitious, and opinionated programmer might well pick up some slack by refactoring or reimplementing some existing code into a brand new library to share with world. If nothing else, a popular library is a great artifact to present at your performance review.

I started thinking about this in part because it frustrates me how much programming “content” (for lack of a better word) seems to be geared towards either soldiers in corporate programmer armies or individuals who are only just starting their company or their career: processes so hundreds can collaborate, how-to’s fit only for a blank page, or advice for your biannual job change. There’s probably good demographic reasons for this; large firms with many programmers have many programmers reading Hacker News. But something still feels off about this balance of perspectives, and you know what? Maybe it’s all been a bubble, my opinions are correct, and it’s the children who are wrong.

As interest rates proved to be less transient and some software-adjacent trends were thus shown to have been bubbles, a popular complaint was to compare something like crypto currency to the US railroad boom (and bust) of the 19th century—the punchline being that at least the defunct railroads left behind a quarter-million miles of perfectly usable tracks.

So what did we get for the 2010’s JavaScript bubble? Hardware (especially phones), browsers, ECMAScript, HTML, and CSS all gained a tremendous amount of performance, functionality, and complexity over the decade, and for the most part a programmer can now take advantage of all that comparatively easily. The Hobbesian competition of libraries left us with the strongest, and it’s now presumably less complicated trying to decide what to use to format dates.

Then again, abandonware is now blindly pulled into critical software via onion-layered dependency chains, and big companies have taken frontend development from being something approachable by an eager hobbyist armed with a text editor, and remade it in their own image as something to be practiced by continuously-churning replaceable-parts engineers aided by a rigid exoskeleton of frameworks and compilers and processes.

So yes, “in conclusion, web development is a land of contrasts“. To end on a more interesting note, there are two projects that I think could hint at what the next decade will bring. Microsoft’s Blazor is directly marketed as a way to avoid JavaScript altogether by writing frontend code in C# and just compiling it to WebAssembly (yes, that’s not always true because as usual Microsoft gave the same name to four different things). Meanwhile htmx tries to avoid this whole JavaScript mess by adding some special attributes to HTML to enable just enough app-ness on web pages. I would never bet against JavaScript, but it’s noteworthy that both are clearly geared towards people frustrated with contemporary JS development, and it’ll be interesting to see how much of a following they or similar attempts find over the next few years.