The United States invaded Iraq twenty years ago. The commemorations of this inauspicious time have been muted and largely resigned to editorial pages. James Fallows remembers:

Part of today’s convenient, hazy memory emerges as: Yes, what a rough time that was. Everybody believed the propaganda. Wasn’t that too bad. If only we had known! That is a destructive way to understand the Iraq years, because not everybody believed the propaganda. Many people tried their best to stop the war.

I’m not even talking about the hundreds of thousands of Americans (and many others around the world) who took to the streets in protests. Nor the leaders of most of the traditional U.S. allies, who formally opposed the decision to invade. With the egregious exception of Tony Blair.

I despised everything about this time in history — the illegitimate president, his psychopath of a vice president and cabinet full of gleeful, ghoulish neocons; the fear and weaponization of that fear; the disdain of my own country. It was all a precursor to a Republican party that’s only taken the slack they were given by a docile public, shaken institutions, and cowed media to become the authoritarian farce they are today. I despise the warmongering party of Bush and Cheney no less than the populist white supremacists that rally around Trump.

I was a journalist at the time of the invasion, pulling long hours in newsrooms where coverage was 24/7. I was nowhere near the war but still the coverage leading up to and then after the invasion was relentless — I wouldn’t exactly recommend the experience! Still, it’s vital that time be remembered authentically. The podcast Slow Burn captured the chaos and confusion and mendacity of the run-up to the war. Spencer Ackerman’s Reign of Terror is an account of how the Bush/Cheney war on terror reshaped America beyond just the response to 9/11 and the invasions of Iraq and Afghanistan to where we are today.

Maximum Fun, the long-going podcast network built up by Jesse Thorn, is becoming a collective. Wendy Lee, writing for the L.A. Times:

On Monday, Thorn — who has co-owned Maximum Fun with his wife since it was incorporated in 2011 — announced his company would become a worker cooperative, a novel business model in the podcast industry, but one that has been tried by many small businesses including bakeries and pizza places. The ownership will be shared equally by at least 16 people, including Thorn, the company said.

The process of converting Maximum Fun into a co-op took about a year and a half, Thorn said.

Thorn said he would receive an upfront sum and a percentage of the company’s revenue for a limited number of years. The company is taking out a loan from a community development financial institutions fund.

Based solely on my demographics, I should land squarely in the center of the Maximum Fun ideal listener matrix, yet it’s never really been my thing. I was an early booster of Put This On, the web series Thorn co-produced with the inimitable Adam Lisagor, I’ve just never fallen into the MaxFuniverse. They seem to be doing ok!

I love the thinking here, drawing on a tradition of worker owned collectives and co-ops to face down gigification platforms and other collectively owned media orgs. Thorn seems to be allergic to consolidation that’s happened around podcasts over the past decades and it’s deeply encouraging to see an alternative to the raise money and sell to a big company route.

A.O. Scott is leaving his post as the co-chief film critic at the Times, and wrote his own exit interview in recognition of the past 23 years.

Scott is, if not my favorite film critic, certainly the one I’ve read the most, given his tenure at the Times tracks with my own cultural growth. I haven’t always agreed with his critiques (it’s probably more like a 90% hit rate), though I can always see his point. He takes the work (thankfully, not himself) seriously, isn’t above popular fare, but also isn’t going to be bowled over by public opinion.

I thought this riff on the toxicity of modern fandom was excellent and, given his perch overseeing the tumult in culture over the past two-plus decades, exceedingly fair.

I’m not a fan of modern fandom. This isn’t only because I’ve been swarmed on Twitter by angry devotees of Marvel and DC and (more recently) “Top Gun: Maverick” and “Everything Everywhere All at Once.” It’s more that the behavior of these social media hordes represents an anti-democratic, anti-intellectual mind-set that is harmful to the cause of art and antithetical to the spirit of movies. Fan culture is rooted in conformity, obedience, group identity and mob behavior, and its rise mirrors and models the spread of intolerant, authoritarian, aggressive tendencies in our politics and our communal life.

Beyond his movie reviews, I thoroughly enjoyed his book Better Living Through Criticism, a paean to the gift that true criticism can, though often fails, to be. Published in 2016, Better Living arrived at a massive cultural inflection point — the post-gamergate internet of the aforementioned toxic fandom, but before the fully unleashed torrent of Trump-era culture warring that has subsumed nearly everything.

Scott isn’t leaving the Times or his role as a critic, instead turning to a critic at large. I look forward to more of his critical gifts.

Here’s a fun story: the waste energy thrown off by a small compute cluster is being used to heat a public swimming pool. Zoe Kleinman, writing for the BBC:

The heat generated by a washing-machine-sized data centre is being used to heat a Devon public swimming pool.

The computers inside the white box are surrounded by oil to capture the heat—enough to heat the pool to about 30C 60% of the time, saving Exmouth Leisure Centre thousands of pounds.

The data centre is provided to the council-run centre free of charge.

Start-up Deep Green charges clients to use its computing power for artificial intelligence and machine learning.

Founder Mark Bjornsgaard said the company would also refund the leisure centre’s electricity costs for running the “digital boiler”—and seven other England pools had signed up to the scheme.

The concept, developed over five years, is relatively straight forward - the hot oil is pumped into a heat exchanger to warm the water in the pool.

As a one-off proof of concept, this is great. As a new paradigm to think about public resources and energy management, I love it.

Deep Green’s pitch is to create “climate and society friendly compute,” essentially replacing giant, exurban datacenters with small, local, urban, carbon-neutral “data furnaces”. They’re creating a more distributed AWS with a built-in heat management solution.

What if cities themselves built these out and provided the compute resources as a sort of civic benefit. Imagine dozens (hudreds? thousands??) of these “washing-machine-sized data centers” scattered across cities, connected not just to swimming pools but boilers in school basements, heat pumps in office buildings, water heaters in fire departments. They could be powered by rooftop solar panels, accessible to residents via a nominal compute fee, and reuse the heat that usually goes to waste. A local, sustainable public cloud!

Of course, you can’t just give people free compute cycles, people would immediately do terrible things with them. Surely, though, there are services you could provide — easy backups, or local caches to speed up home internet, or just power a city’s ever growing need for computers.

The compute pod as mini heat furnace is also a fun way to reconsider energy storage. A few years ago, I started thinking about how I wanted to redesign the energy usage for my house. Solar panels were an obvious choice, but what about storage? Backup batteries are expensive and strike me as wasteful, but then I started expanding my thinking beyond just electrons to energy. A water heater is a store of energy, after all, so if you use your solar panels to fill up a heat-pump-powered water heater connected to radiant floor heating, you’ve obviated the need for one of your home’s biggest consumers of electricity. A bit more obviously, the giant batteries that millions of people drive around town are now also able to power their homes. With a bit of planning, and some Bidenbucks, you could retrofit to netzero without having to install a bank of lithium in your garage.

One change I’ve noticed over the past decade or so that I find generally pretty exciting is new ways to think about climate solutions. For the longest time, the conversation got defined by the forces aligned against change — this will all be too expensive, and it won’t work anyway, we’ll just be shivering through brownouts in our solar-powered shacks. Now, try to tell me a network of distributed data furnaces isn’t cool as hell. Obviously, we can’t just keep going with unchecked growth, nor are we doomed to a grim future of limited imagination.

This is a loose collection of thoughts based on a brief conversation from the other night. I can’t claim any credit for any of the smart bits.

Let’s take it as a given that Samsung’s attempt to try to pass off high resolution, synthetic moon photos as some kind of enhancement to its phones’ camera systems is boorish and lame. Have some self-respect, Samsung!

The moon is notoriously difficult to photograph, even by professionals with thousands of dollars of equipment. The moon looks different sizes depending on its place in the sky but that’s just our brain playing tricks on us and we don’t even know why. None of this stops people from trying to take pictures of the moon, even (especially!) with their phones. The moon is probably the most photographed single object across everyone’s photo libraries.

Back in 2007 (the year the iPhone and it’s 2 megapixel camera were released), researchers scraped photos of landmarks like the Statue of Liberty and the Notre Dame Cathedral from Flickr and used those to render fairly accurate 3D models just from the flat photos. Fifteen years later, there are incalculably more photos of even relatively obscure landmarks, taken at higher resolutions, and even more powerful synthetic image generators that can be run on your phone.

I learned to shoot on film cameras. I even learned to process film and post-process in a dark room, actually dodging and burning. In journalism school, we still shot film but scanned the negatives and used Photoshop for cropping, cleanup, and color correction. The threat of failing the entire class hung over everyone who even thought about digitally altering their shots beyond basic darkroom techniques. Online, though, the world blew past that and now we’ve lived through epochs of ‘SHOPPED, Instagram filters, then #nofilter, Snapchat lenses, magic erasers, and now fully synthetic images. Even the supposedly real, unfiltered images we all take on our phones are the result of billions of calculations that compose “computational photographs”. It’s hard to argue with the results.

I certainly won’t be the one to argue that an AI-generated moon is a computational photograph. I also won’t begrudge anyone for wanting to remove that random stranger from the background of their otherwise perfectly composed selfie. I abuse portrait mode on my phone because it makes pictures of my kids look amazing. It won’t be long before we’re all carrying a neural net around in our phones that will compose perfect — too perfect — photos of anything. Even the moon.

It was my birthday this weekend so, short of a quick joke, I didn’t follow the collapse of Silicon Valley Bank all that closely. Here’s a good rundown with a healthy dose of strident skepticism to boot. In the end, it seems like the post Dodd-Frank system worked as it should have (and had it not been kneecapped during the Trump administration, may not have been needed in the first place), with the depositors getting their money back, SVB’s leadership out of a job, and an admonishment from future-Senator Katie Porter.

I keep thinking about something Paul Ford said a few years ago. I can’t find the quote (I think it was in a podcast), but in essence it was about how tech hates the fact that it still has to rely on finance. Founders need VCs and VCs, for all their world-changing bluster, still need LPs to fill their coffers. Silicon Valley won’t admit what’s been obvious for years — that it’s fully beholden to Wall St. — and the collapse of an institution that by all accounts served them incredibly well is the end result. Crypto was another attempt to try to renege on their faustian bargain, and that’s played out in predictably terrible ways as well.

I’ve been gathering string for a while about all of the machine learning / LLM / generative AI¹ excitement that’s been happening over the past year² in the hopes of having something interesting to say. Thankfully, Robin Sloan has been deep in the work and has a piece that very much mirrors a lot of where I’m coming down (or probably more accurately, I’ve rather artlessly copied his takes).

The post is fairly wide ranging, in the best way, and this bit struck me in particular:

I think it’s really chal­lenging to find the appro­priate stance towards this stuff.

On one hand, I find critical deflation, of the kind you’ll hear from Ted Chiang, Simon Willison, and Claire Leibowicz in this recent episode of KQED Forum, appro­priate and useful. The hype is so powerful that any correc­tive is welcome.

However! On the critical side, the eval­u­a­tion of what’s presently before us isn’t sufficient; not even close. If we appre­ciate humility from AI engineers, then we ought to have some humility ourselves. Humility — and imagination.

An important fact about these language models — one that sets them apart from, say, the personal computer, or the iPhone — is that their capa­bil­i­ties have been surprising, often confounding, even to their creators.

AI at this moment feels like a mash-up of programming and biology. The program­ming part is obvious; the biology part becomes apparent when you see AI engineers probing their own creations the way scien­tists might probe a mouse in a lab.

The simple fact is: even at the highest levels of theory and practice, no one knows how these language models are doing what they’re doing.

Programming and biology! In my own mental models, I’ve replaced the biology bits with something more akin to raising a child, which is fairly hackneyed at this point. The training, the frustrations, the joy at something completely unexpected happening. Child rearing, though, happens so slowly over the course of a lifetime, whereas the language model advances are more like the humble Drosophila melanogaster, that workhorse of biotechnology that somehow manages to be cheap, fast, and good.

For my own part, something as hyped as generative AI almost requires me to turn up my nose in distaste (see also: crypto, NFTs, web3). And yet! My small explorations are some of the most fun I’ve had ever with computers. I’ve got a few decades worth of digitized thoughts and to be able to coax some meaning out of them with a handful of Python scripts (in a thus far unsuccesful effort to post not just more but better) is deeply intriguing. The idea of a universally accessible interface to the computer — an electric bicycle for the mind, as Simon Willison put it — is exciting not just to me personally but as someone who sees the often unfulfilled promise of technology that empowers.

Multiverses and split timelines are so hot right now, even if it’s often in the service of stuffing more intellectual property into amusement park movies. Rarer is to get a unique, tiltshift glimpse into a more mundane world that might have been, if only as a bit of winking humor.

I don’t remember when I started following @nanoraptor, aka Dana Sibera, but her posts — mutated retro tech recreations — have never failed to amuse me. For one, she’s an artist with photoshop, with an auteur’s sensibility, an impeccable eye for detail, and a deep knowledge of computer history. She’s also hilarious, provided you are a nerd of a certain vintage and take a moment to peel back the many layers of her art. And there’s something truly delightful about Sibera’s artisanal anachronisms that stands out in a world where Midjourney or DALL•E could probably churn out some artless approximation with relative ease.

Marcin Wichary (recently seen here) curated a number of her creations and wrote a really wonderful appreciation, naturally with an emphasis on the keyboards. I thought I’d seen most of Sibera’s work, but many of these were new to me, and several lead me down explorations into actual computer history I’d never seen, like the stunning Apple Jonathan. What I love about both Sibera’s work and Wichary’s appreciation is you can tell they ache for many of these to exist.

Take few moments to live in a world that never really could, but absolutely should, have been.

One of my complaints about the new Artifact AI newsreader is how it seems to ignore the reinvigorated (at least in nerdier corners) open web, like RSS and federated social media.

So, it’s interesting to see one of the original newsreader/aggregators, Flipboard, has added Mastodon support to their app. It’s been literally years since I used Flipboard, so I downloaded it, reset my password, and gave it a go. It works!

Flipboard, as a concept, never really worked for me, though. The unique interactivity — that eponymous flip in lieu of a scroll — seems like a nice demo that simply never held up to regular usage. I seem to recall a lot of excitement about their layout engine, which promised to deliver magazine quality page configurations but is ultimately sadled with the content it’s ingesting. This is doubly true for social media feeds, where the app is trying to create a genuine pastiche¹ from … well, tweets. I ended up having the same problem with the Readwise Reader app — it’s just not my thing in the way NetNewsWire is.

But we’re not here to review a twelve-year old newsreader app, we’re here to celebrate their embrace of the open web. Which makes it a bit more interesting that Flipboard has also set up a Mastodon instance of their very own to make it easier for anyone to get going with federated social media. Flipboard co-founder and CEO Mike McCue has a post detailing their embrace of the “federated future”.

Like I said, Flipboard the app never really stuck for me. But clearly plenty of people use it, and that’s great. Some of them might even start posting interesting quips over on flipboard.social and I’ll give them a follow. Just not on Flipboard.

Artifact, the social news feed app built and funded by the co-creators of Instagram, launched to the public today. I’ve been using the beta version for a few weeks, and I remain underwhelmed, both with the product and the ethos of the app.

Unlike seemingly everyone else who nodded to the beta announcement, I was decidedly not excited to hear the duo of Kevin Systrom and Mike Krieger were building a news app. I stopped using Instagram not long after they sold to Facebook, I’ve never considered Instagram “the good social network” and, in fact, think it’s pretty obvious that everything that makes Instagram bad was baked in from its founding. So, I was skeptical from the start Artifact offered much that was new, let alone would contribute to a better informed citizenry.

Even with this admittedly critical eye, I was to see if they’d cracked some code the many, many attempts at personalized news feeds hadn’t. Maybe the tech that Artifact is hanging its hat on really is as transformative¹ as Systrom believes and the long sought ideal of delivering a perfect, personal stream of news is at hand, or at least close. Even after putting in the work (and training Artifact often feels like work), I continue to find its recommendations to be somewhere on a spectrum between inscrutable to unhelpful.

Most of what Artifact considers alert-worthy, for example, have turned out to be the articles I’m most likely to tell it to send me less of. Until you’ve silenced enough of the content mills, the app feels like one big chum box. Once I’m in the app, I will usually find a link worth reading — but is that really a problem anyone has these days? Does anyone need, or even want, an endlessly scrolling “TikTok for news”? Even as a fairly diligent tester (tech + media is very much my beat), I haven’t found Artifact to be any more useful than Prismatic (RIP), Nuzzle (RIP), Flipboard, or even Apple News before it; my creaky collection of RSS feeds remains more serendipitous.

They’ve limited their dataset to fairly reputable news sources and blogs (instead of the entire internet), and have added only the most basic of social features (which require you to upload your entire address book, of course). These feel more like cover-your-ass maneuvers that reveal only the most surface-level lessons learned from the past decade or so. And with so much energy moving towards federated social networks, RSS, and a renewed interest in the open web, doubling down on a walled garden approach² feels downright antiquated.

All of which gets to my deeper problem with both Artifact and why I started off so deeply skeptical of its provenance. What is the purpose of this app? According to Systrom, his big revelation was in seeing how large language models and transformers would fundamentally change how recommendation systems work. Artifact seems to be answering the question of “what if we ingested all the news and ran it through this new tech, then showed people headlines they were more likely to read.” At no point does the app, or anyone working on it, seem to be interested in answering the question of “how do we help people better understand the world they live in.” Maybe I’m just too old school, but it seems to me that’s the fundamental purpose of all that news to begin with.

One of my many annoyances with tech is how they refuse to understand history, especially their own; they don’t even seem capable of listening to their own lionized heroes. It was none other than Steve Jobs who said, “you’ve got to start with the customer experience and work backwards to the technology,” yet Artifact doesn’t seem to know what it’s for. It has all the hallmarks of a well-built app — it’s performant, the layouts are crisp, the onboarding flowed along just fine — but that’s only the most shallow understanding of UX, let alone design.

We’ve seen this same playbook from tech time and time again. If you actually wanted to make the world a more open and connected place, you wouldn’t build Facebook, you’d make it easier to build on the open web. If you actually wanted to reimagine transportation, you wouldn’t build Uber or Tesla or hyperloops, you’d build trains. Tech continues to offer these non-solutions because they are easy, or fence in more of the commons, or they’re just enamored with some shiny feature and don’t give a damn about any of the knock-on effects.

If all of this sounds a touch dramatic for an app that feeds you headlines, it’s because I was there arguing with my bosses against adding facebook widgets to story pages or committing to platform lock-in. If it sounds like I’m hating on LLMs or transformers or what’s being hailed as AI, I’m actually as excited as I’ve been since I first learned to build a web page. But I want tools to help journalists do their jobs better — an ML-assistant that can summarize public meetings, investigate massive troves of financial data to ferret out white-collar crime, help human journalists understand and explain arcane technical topics, or offer personalized context about a news story to every reader. Instead, we get an infinite number of auto-generated Buzzfeed listicles and a startup that once again wants to take all the benefits of the open news ecosystem without offering anything back. It’s as cynical as it is unsurprising at this point.

UPDATE
February 23, 2022

Mere hours after I hit publish on this post, Ben Thompson published an interview with Systrom and Krieger about the launch of Artifact³. In the final section of the interview, they discuss pretty directly most of the critiques I made here, about which I have a few more thoughts.

First is Krieger on working backwards to the technology:

MK: We talk consistently about this being, and it’s going to sound funny, hopefully the last company we found in our lives, and not because we don’t want to do it again, but because it can be a platform for realizing all of what we want do in terms of taking what’s at the forefront of technology — I think you can break this down to what Kevin and I do — we’re not researchers, we’re not the people trying to build things that are twenty years out from the technology and you have to squint, “Ah, maybe that’s going to work”. We take what’s at the forefront, on the cusp, and try to bring it to bear with what I think is strong product sense and engineering chops, and practicality.

…

I think it involves the taste to understand, all right, what about this is begging for consumer products to be built and how do we do that really well? Not like, “Yeah, this technology exists. Let’s go solve a problem with it.” But based on everything that we know, what can we build that will solve a problem? And the cool thing about that is that that’s a template or almost like a recipe that I think we can follow for a long time, and do it with the right teams and do it together and evolve over time, and that’s the core of what we’re trying to do. In general I see this as a platform where this is what we’re working on right now, but the approach doesn’t change. It’s just the manifestation that might over time.

I think the founders genuinely believe Artifact has, in fact, started with the product but that’s exactly the problem, treating news as just another product. This is going to veer into the philosophical quickly, but it’s actually important in a deeply social sense to understand how the news is different from content or even media. Of course, that misunderstanding has been so embedded in Silicon Valley for so long it’s practically a truism.

Systrom then addresses my other big question:

KS: I think people always want to know what’s going on in the world around them, and the way they learn about that is through various mediums throughout time. It can be through the printed newspaper, it can be through a magazine, it can be through a radio show, it can be through a podcast, it can be through a video on TikTok, it can be on cable television. You name it, they can learn about the world around them. But that job — we use jobs-to-be-done theory a lot in our work — that job-to-be-done about learning about the world around you and going deep on your interests will never go away and we just happen to do it with a specific medium, which is easy to do asynchronously when you’re sitting there. Whether you’re in bed or you’re waiting for a meeting, you don’t have to listen to it. You don’t have to have it on audio, you don’t have to have headphones in.

I suppose I’m slightly more optimistic they at least understand the purpose, or maybe a purpose of Artifact, but they seem more hung up on how their chosen medium differentiates them.

More revealing are the topics that didn’t come up: does Artifact plan to hire a public editor? What tools will they offer other media organizations? If they succeed in backing into a Twitter-like social network, how will they manage the user generated content — more AI? How will they take responsibility for their synthetic copy once they start, for example, auto-generating summaries? How will Artifact deal with the avalanche of disreputable, synthetic content that is surely just around the corner?

It would be impossible to answer these questions at launch, but the will to answer them needs to be there. We’ll see if Systrom and Krieger are up for the actual work now that the app is out there.