I've just discovered the work of Alfonso Jimenez (null). He takes clips from advertisements, movies, production numbers, and YouTube dance videos and makes them into eclectic but rhythmic dance mashups to illustrate one song at a time. I was particularly taken with this one for T. Rex's 1971 song "Bang a Gong (Get It On)."
The first video game was a 1952 research product called OXO — tic-tac-toe played on a computer the size of a large room:
Fifteen years later Ralph Baer produced “The Brown Box”; Magnavox licensed Baer’s device and released it as the Odyssey five years later — it was the first home video game console:
The Odyssey made Magnavox a lot of money, but not through direct sales: the company sued Atari for ripping off one of the Odyssey’s games to make “Pong”, the company’s first arcade game and, in 1975, first home video game, eventually reaping over $100 million in royalties and damages. In other words, arguments about IP and control have been part of the industry from the beginning.
In 1977 Atari released the 2600, the first console I ever owned:1
All of the games for the Atari were made by Atari, because of course they were; IBM had unbundled mainframe software and hardware in 1969 in an (unsuccessful) attempt to head off an antitrust case, but video games barely existed as a category in 1977. Indeed, it was only four years earlier when Steve Wozniak had partnered with Steve Jobs to design a circuit board for Atari’s Breakout arcade game; this story is most well-known for the fact that Jobs lied to Wozniak about the size of the bonus he earned, but the pertinent bit for this Article is that video game development was at this point intrinsically tied to hardware.
That, though, was why the 2600 was so unique: games were not tied to hardware but rather self-contained in cartridges, meaning players would use the same system to play a whole bunch of different games:
The implications of this separation did not resonate within Atari, which had been sold by founder Nolan Bushnell to Warner Communications in 1976, in an effort to get the 2600 out the door. Game Informer explains what happened:
In early 1979, Atari’s marketing department issued a memo to its programing staff that listed all the games Atari had sold the previous year. The list detailed the percentage of sales each game had contributed to the company’s overall profits. The purpose of the memo was to show the design team what kinds of games were selling and to inspire them to create more titles of a similar breed…David Crane, Larry Kaplan, Alan Miller, and Bob Whitehead were four of Atari’s superstar programmers. Collectively, the group had been responsible for producing many of Atari’s most critical hits…
“I remember looking at that memo with those other guys,” recalls Crane, “and we realized that we had been responsible for 60 percent of Atari’s sales in the previous year – the four of us. There were 35 people in the department, but the four of us were responsible for 60 percent of the sales. Then we found another announcement that [Atari] had done $100 million in cartridge sales the previous year, so that 60 percent translated into $60 million.”
These four men may have produced $60 million in profit, but they were only making about $22,000 a year. To them, the numbers seemed astronomically disproportionate. Part of the problem was that when the video game industry was founded, it had molded itself after the toy industry, where a designer was paid a fixed salary and everything that designer produced was wholly owned by the company. Crane, Kaplan, Miller, and Whitehead thought the video game industry should function more like the book, music, or film industries, where the creative talent behind a project got a larger share of the profits based on its success.
The four walked into the office of Atari CEO Ray Kassar and laid out their argument for programmer royalties. Atari was making a lot of money, but those without a corner office weren’t getting to share the wealth. Kassar – who had been installed as Atari’s CEO by parent company Warner Communications – felt obligated to keep production costs as low as possible. Warner was a massive corporation and everyone helped contribute to the company’s success. “He told us, ‘You’re no more important to those projects than the person on the assembly line who put them together. Without them, your games wouldn’t have sold anything,’” Crane remembers. “He was trying to create this corporate line that it was all of us working together that make games happen. But these were creative works, these were authorships, and he didn’t get it.”
“Kassar called us towel designers,” Kaplan told InfoWorld magazine back in 1983, “He said, ‘I’ve dealt with your kind before. You’re a dime a dozen. You’re not unique. Anybody can do a cartridge.’”
That “anyone” included the so-called “Gang of Four”, who decided to leave Atari and form the first 3rd-party video game company; they called it Activision.
Activision represented the first major restructuring of the video game value chain; Steve Wozniak’s Breakout was fully integrated in terms of hardware and software:
The Atari 2600 with its cartridge-based system modularized hardware and software:2
Activision took that modularization to its logical (and yet, at the time, unprecedented) extension, by being a different company than the one that made the hardware:
Activision, which had struggled to raise money given the fact it was targeting a market that didn’t yet exist, and which faced immediate lawsuits from Atari, was a tremendous success; now venture capital was eager to fund the market, leading to a host of 3rd-party developers, few of whom had the expertise or skill of Activision. The result was a flood of poor quality games that soured consumers on the entire market, leading to the legendary video game crash of 1983: industry revenue plummeted from $3.2 billion in 1983 to a mere $100 million in 1985. Activision survived, but only by pivoting to making games for the nascent personal computing market.
The personal computer market was modular from the start, and not just in terms of software. Compaq’s success in reverse-engineering the IBM PC’s BIOS created a market for PC-compatible computers, all of which ran the increasingly ubiquitous Microsoft operating system (first DOS, then Windows). This meant that developers like Activision could target Windows and benefit from competition in the underlying hardware.
Moreover, there were so many more use cases for the personal computer, along with a burgeoning market in consumer-focused magazines that reviewed software, that the market was more insulated from the anarchy that all but destroyed the home console market.
That market saw a rebirth with Nintendo’s Famicom system, christened the “Nintendo Entertainment System” for the U.S. market (Nintendo didn’t want to call it a console to avoid any association with the 1983 crash, which devastated not just video game makers but also retailers). Nintendo created its own games like Super Mario Bros. and Zelda, but also implemented exacting standards for 3rd-party developers, requiring them to pass a battery of tests and pay a 30% licensing fee for a maximum of five games a year; only then could they receive a dedicated chip for their cartridge that allowed it to work in the NES.
Nintendo’s firm control of the third-party developer market may look familiar: it was an early precedent for the App Store battles of the last decade. Many of the same principles were in play:
Nintendo had a legitimate interest in ensuring quality, not simply for its own sake but also on behalf of the industry as a whole; similarly, the App Store, following as it did years of malware and viruses in the PC space, restored customer confidence in downloading third-party software.
It was Nintendo that created the 30% share for the platform owner that all future console owners would implement, and which Apple would set as the standard for the App Store.
While Apple’s App Store lockdown is rooted in software, Nintendo had the same problem that Atari had in terms of the physical separation of hardware and software; this was overcome by the aforementioned lockout chips, along with branding the Nintendo “Seal of Quality” in an attempt to fight counterfeit lockout chips.
Nintendo’s strategy worked, but it came with long-term costs: developers, particularly in North America, hated the company’s restrictions, and were eager to support a challenger; said challenger arrived in the form of the Sega Genesis, which launched in the U.S. in 1989. Sega initially followed Nintendo’s model of tight control, but Electronic Arts reverse-engineered Sega’s system, and threatened to create their own rival licensing program for the Genesis if Sega didn’t dramatically loosen their controls and lower their royalties; Sega acquiesced and went on to fight the Super Nintendo, which arrived in the U.S. in 1991, to a draw, thanks in part to a larger library of third-party games.
The company that truly took the opposite approach to Nintendo was Sony; after being spurned by Nintendo in humiliating fashion — Sony announced the Play Station CD-ROM add-on at CES in 1991, only for Nintendo to abandon the project the next day — the electronics giant set out to create their own console which would focus on 3D-graphics and package games on CD-ROMs instead of cartridges. The problem was that Sony wasn’t a game developer, so it started out completely dependent on 3rd-party developers.
One of the first ways that Sony addressed this was by building an early partnership with Namco, Sega’s biggest rival in terms of arcade games. Coin-operated arcade games were still a major market in the 1990s, with more revenue than the home market for the first half of the decade. Arcade games had superior graphics and control systems, and were where new games launched first; the eventual console port was always an imitation of the original. The problem, however, is that it was becoming increasingly expensive to build new arcade hardware, so Sony proposed a partnership: Namco could use modified PlayStation hardware as the basis of its System 11 arcade hardware, which would make it easy to port its games to PlayStation. Namco, which also rebuilt its more powerful Ridge Racer arcade game for the PlayStation, took Sony’s offer: Ridge Racer launched with the Playstation, and Tekken was a massive hit given its near perfect fidelity to the arcade version.
Sony was much better for 3rd-party developers in other ways, as well: while the company maintained a licensing program, its royalty rates were significantly lower than Nintendo’s, and the cost of manufacturing CD-ROMs was much lower than manufacturing cartridges; this was a double whammy for the Nintendo 64 because while cartridges were faster and offered the possibility of co-processor add-ons, what developers really wanted was the dramatically increased amount of storage CD-ROMs afforded. The Playstation was also the first console to enable development on the PC in a language (C) that was well-known to existing developers. In the end, despite the fact that the Nintendo 64 had more capable hardware than the PlayStation, it was the PlayStation that won the generation thanks to a dramatically larger game library, the vast majority of which were third-party games.
Sony extended that advantage with the PlayStation 2, which was backwards compatible with the PlayStation, meaning it had a massive library of 3rd-party games immediately; the newly-launched Xbox, which was basically a PC, and thus easy to develop for, made a decent showing, while Nintendo struggled with the Gamecube, which had both a non-standard controller and non-standard microdisks that once again limited the amount of content relative to the DVDs used for PlayStation 2 and Xbox (and it couldn’t function as a DVD player, either).
This period for video games was the high point in terms of console competition for 3rd-party developers for two reasons:
First, there were still meaningful choices to be made in terms of hardware and the overall development environment, as epitomized by Sony’s use of CD-ROMs instead of cartridges.
Second, developers were still constrained by the cost of developing for distinct architectures, which meant it was important to make the right choice (which dramatically increased the return of developing for the same platform as everyone else).
It was the Sony-Namco partnership, though, that was a harbinger of the future: it behooved console makers to have similar hardware and software stacks to their competitors, so that developers would target them; developers, meanwhile, were devoting an increasing share of their budget to developing assets, particularly when the PS3/Xbox 360 generation targeted high definition, which increased their motivation to be on multiple platforms to better leverage their investments. It was Sony that missed this shift: the PS3 had a complicated Cell processor that was hard to develop for, and a high price thanks to its inclusion of a Blu-Ray player; the Xbox 360 had launched earlier with a simpler architecture, and most developers built for the Xbox first and Playstation 3 second (even if they launched at the same time).
The real shift, though, was the emergence of game engines as the dominant mode of development: instead of building a game for a specific console, it made much more sense to build a game for a specific engine which abstracted away the underlying hardware. Sometimes these game engines were internally developed — Activision launched its Call of Duty franchise in this time period (after emerging from bankruptcy under new CEO Bobby Kotick) — and sometimes they were licensed (i.e. Epic’s Unreal Engine). The impact, though, was in some respects similar to cartridges on the Atari 2600:
In this new world it was the consoles themselves that became modularized: consumers picked out their favorite and 3rd-party developers delivered their games on both.
Nintendo, meanwhile, dominated the generation with the Nintendo Wii. What was interesting, though, is that 3rd-party support for the Wii was still lacking, in part because of the underpowered hardware (in contrast to previous generations): the Wii sold well because of its unique control method — which most people used to play Wii Sports — and Nintendo’s first-party titles. It was, in many respects, Nintendo’s most vertically-integrated console yet, and was incredibly successful.
Sony’s pivot after the (relatively) disappointing PlayStation 3 was brilliant: if the economic imperative for 3rd-party developers was to be on both Xbox and PlayStation (and the PC), and if game engines made that easy to implement, then there was no longer any differentiation to be had in catering to 3rd-party developers.
Instead Sony beefed up its internal game development studios and bought up several external ones, with the goal of creating PlayStation 4 exclusives. Now some portion of new games would not be available on Xbox not because it had crappy cartridges or underpowered graphics, but because Sony could decide to limit its profit on individual titles for the sake of the broader PlayStation 4 ecosystem. After all, there would still be a lot of 3rd-party developers; if Sony had more consoles than Microsoft because of its exclusives, then it would harvest more of those 3rd-party royalty fees.
Those fees, by the way, started to head back up, particularly for digital-only versions, which returned to that 30% cut that Nintendo had pioneered many years prior; this is the downside of depending on universal abstractions like game engines while bearing high development costs: you have no choice but to be on every platform no matter how much it costs.
Sony bet correctly: the PS4 dominated its generation, helped along by Microsoft making a bad bet of its own by packing in the Kinect with the Xbox One. It was a repeat of Sony’s mistake with the PS3, in that it was a misguided attempt to differentiate in hardware when the fundamental value chain had long since dictated that the console was increasingly a commodity. Content is what mattered — at least as long as the current business model persisted.
Nintendo, meanwhile, continued to march to its own vertically-integrated drum: after the disastrous Wii U the company quickly pivoted to the Nintendo Switch, which continues to leverage its truly unique portable form factor and Nintendo’s first-party games to huge sales. Third party support, though, remains extremely tepid; it’s just too underpowered, and the sort of person that cares about third-party titles like Madden or Call of Duty has long since bought a PlayStation or Xbox.
First, the video game market has proven to be extremely dynamic, particularly in terms of 3rd-party developers:
Atari was vertically integrated
Nintendo grew the market with strict control of 3rd-party developers
Sony took over the market by catering to 3rd-party developers and differentiating on hardware
Xbox’s best generation leaned into increased commodification and ease-of-development
Sony retook the lead by leaning back into vertical integration
That is quite the round trip, and it’s worth pointing out that attempting to freeze the market in its current iteration at any point over the last forty years would have foreclosed future changes.
At the same time, Sony’s vertical integration seems more sustainable than Atari’s. First, Sony owns the developers who make the most compelling exclusives for its consoles; they can’t simply up-and-leave like the Gang of Four. Second, the costs of developing modern games has grown so high that any 3rd-party developer has no choice but to develop for all relevant consoles. That means that there will never be a competitor who wins by offering 3rd-party developers a better deal; the only way to fight back is to have developers of your own, or a completely different business model.
The first fear raised by the FTC is that Microsoft, by virtue of acquiring Activision, is looking to fight its own exclusive war, and at first blush it’s a reasonable concern. After all, Activision has some of the most popular 3rd-party games, particularly the aforementioned Call of Duty franchise. The problem with this reasoning, though, is that the price Microsoft paid for Activision was a multiple of Activision’s current revenues, which include billions of dollars for games sold on Playstation. To suddenly cut Call of Duty (or Activision’s other multi-platform titles) off from Playstation would be massively value destructive; no wonder Microsoft said it was happy to sign a 10-year deal with Sony to keep Call of Duty on PlayStation.
Just for clarity’s sake, the distinction here from Sony’s strategy is the fact that Microsoft is acquiring these assets. It’s one thing to develop a game for your own platform — you’re building the value yourself, and choosing to harvest it with an ecosystem strategy as opposed to maximizing that games’ profit. An acquirer, though, has to pay for the business model that already exists.
At the same time, though, it’s no surprise that Microsoft has taken in-development assets from its other acquisition like ZeniMax and made them exclusives; that is the Sony strategy, and Microsoft was very clear when it acquired ZeniMax that it would keep cross-platform games cross-platform but may pursue a different strategy for new intellectual property. CEO of Microsoft Gaming Phil Spencer told Bloomberg at the time:
In terms of other platforms, we’ll make a decision on a case-by-case basis.
Given this, it’s positively bizarre that the FTC also claims that Microsoft lied to the E.U. with regards to its promises surrounding the ZeniMax acquisition: the company was very clear that existing cross-platform games would stay cross-platform, and made no promises about future IP. Indeed, the FTC’s claims were so off-base that the European Commission felt the need to clarify that Microsoft didn’t mislead the E.U.; from Mlex:
Microsoft didn’t make any “commitments” to EU regulators not to release Xbox-exclusive content following its takeover of ZeniMax Media, the European Commission has said. US enforcers yesterday suggested that the US tech giant had misled the regulator in 2021 and cited that as a reason to challenge its proposed acquisition of Activision Blizzard. “The commission cleared the Microsoft/ZeniMax transaction unconditionally as it concluded that the transaction would not raise competition concerns,” the EU watchdog said in an emailed statement.
The absence of competition concerns “did not rely on any statements made by Microsoft about the future distribution strategy concerning ZeniMax’s games,” said the commission, which itself has opened an in-depth probe into the Activision Blizzard deal and appears keen to clarify what happened in the previous acquisition. The EU agency found that even if Microsoft were to restrict access to ZeniMax titles, it wouldn’t have a significant impact on competition because rivals wouldn’t be denied access to an “essential input,” and other consoles would still have a “large array” of attractive content.
The FTC’s concerns about future IP being exclusive ring a bit hypocritical given the fact that Sony has been pursuing the exact same strategy — including multiple acquisitions — without any sort of regulatory interference; more than that, though, to effectively make up a crime is disquieting. To be fair, those Sony acquisitions were a lot smaller than Activision, but this goes back to the first point: the entire reason Activision is expensive is because of its already-in-market titles, which Microsoft has every economic incentive to keep cross-platform (and which it is willing to commit to contractually).
It’s the final FTC concern, though, that I think is dangerous. From the complaint:
These effects are likely to be felt throughout the video gaming industry. The Proposed Acquisition is reasonably likely to substantially lessen competition and/or tend to create a monopoly in both well-developed and new, burgeoning markets, including highperformance consoles, multi-game content library subscription services, and cloud gaming subscription services…
Multi-Game Content Library Subscription Services comprise a Relevant Market. The anticompetitive effects of the Proposed Acquisition also are reasonably likely to occur in any relevant antitrust market that contains Multi-Game Content Library Subscription Services, including a combined Multi-Game Content Library and Cloud Gaming Subscription Services market.
Cloud Gaming Subscription Services are a Relevant Market. The anticompetitive effects of the Proposed Acquisition alleged in this complaint are also likely to occur in any relevant antitrust market that contains Cloud Gaming Subscription Services, including a combined Multi-Game Content Library and Cloud Gaming Subscription Services market.
A huge amount of discussion around this acquisition was focused on Microsoft needing its own stable of exclusives in order to compete with Sony, but it’s important to note that making all of ZeniMax’s games exclusives would be hugely value destructive, at least in the short-to-medium term. Microsoft is paying $7.5 billion for a company that currently makes money selling games on PC, Xbox, and PS5, and simply cutting off one of those platforms — particularly when said platform is willing to pay extra for mere timed exclusives, not all-out exclusives — is to effectively throw a meaningful chunk of that value away. That certainly doesn’t fit with Nadella’s statement that “each layer has to stand on its own for what it brings”…
Microsoft isn’t necessarily buying ZeniMax to make its games exclusive, but rather to apply a new business model to them — specifically, the Xbox Game Pass subscription. This means that Microsoft could, if it chose, have its cake and eat it too: sell ZeniMax games at their usual $60~$70 price on PC, PS5, Xbox, etc., while also making them available from day one to Xbox Game Pass subscribers. It won’t take long for gamers to quickly do the math: $180/year — i.e. three games bought individually — gets you access to all of the games, and not just on one platform, but on all of them, from PC to console to phone.
Sure, some gamers will insist on doing things the old way, and that’s fine: Microsoft can make the same money ZeniMax would have as an independent company. Everyone else can buy into Microsoft’s model, taking advantage of the sort of win-win-win economics that characterize successful bundles. And, if they have a PS5 and thus can’t get access to Xbox Game Pass on their TVs, an Xbox is only an extra $10/month away.
Microsoft is willing to cannibalize itself to build a new business model for video games, and it’s a business model that is pretty darn attractive for consumers. It’s also a business model that Activision wouldn’t pursue on its own, because it has its own profits to protect. Most importantly, though, it’s a business model that is anathema to Sony: making titles broadly available to consumers on a subscription basis is the exact opposite of the company’s exclusive strategy, which is all about locking consumers into Sony’s platform.
Here’s the thing: isn’t this a textbook example of competition? The FTC is seeking to preserve a model of competition that was last relevant in the PS2/Xbox generation, but that plane of competition has long since disappeared. The console market as it is today is one that is increasingly boring for consumers, precisely because Sony has won. What is compelling about Microsoft’s approach is that they are making a bet that offering consumers a better deal is the best way to break up Sony’s dominance, and this is somehow a bad thing?
What makes this determination to outlaw future business models particularly frustrating is that the real threat to gaming today is the dominance of storefronts that exact their own tax while contributing nothing to the development of the industry. The App Store and Google Play leverage software to extract 30% from mobile games just because they can — and sure, go ahead and make the same case about Microsoft and Sony. If the FTC can’t be bothered to check the blatant self-favoring inherent in these models, at the minimum it seems reasonable to give a chance to a new kind of model that could actual push consumers to explore alternative ways to game on their devices.
For the record, I do believe this acquisition demands careful overview, and it’s completely appropriate to insist that Microsoft continue to deliver Activision titles to other platforms, even if it wouldn’t make economic sense to do anything but. It’s increasingly difficult, though, to grasp any sort of coherent theory to the FTC’s antitrust decisions beyond ‘big tech bad’. There are real antitrust issues in the industry, but that requires actually understanding the industry to tease them out; that sort of understanding applied to this case would highlight Sony’s actual dominance and that having multiple compelling platforms with different business models is the essence of competition.
Ten years later, as a hand-me-down from a relative ↩
The Fairchild Channel F, which was released in 1976, was the actual first console-based video game system, but the 2600 was by far the most popular. ↩
Today, let’s discuss a truly one-of-a-kind piece of sports memorabilia, which I call “The Mickey Mantle Letter”. Back in 1972, to prepare for a celebration of 50 years at Yankee Stadium, the Yankees asked many former players to share an outstanding experience:
In response, retired superstar centerfielder Mickey Mantle sent back this incredibly obscene reply:
I’ve actually heard this hilariously vulgar story before, but I had no idea there was a physical artifact written in Mantle’s own hand. Now, incredibly, it’s available for sale. The current bid, at time of publication, is $24,826. Despite the sum involved, I hope whoever wins this auction donates the letter to the Baseball Hall of Fame in Cooperstown, where it can be displayed publicly. That belongs in a museum!
As a result of this auction, additional details have come out. However, I’m undecided if I believe them. Give the following a read, and decide for yourself. From the auction listing:
Subsequent to the catalog publication, we were contacted by former New York Yankees executive Marty Appel, who has first-hand knowledge of this letter, which he kindly shared with us:
“I was the Yankees Assistant PR Director then, with Bob Fishel my boss. We wrote to many ex-Yankees for a 1973 50th anniversary Yearbook feature on ‘greatest memory.’ That is my handwriting on ‘Dear Mickey’ and ‘Bob Fishel.’ Mick’s response is indeed his, in his handwriting, but it was meant to shock the very straight-laced Bob Fishel on whom he was always playing practical jokes. The item is authentic, but the intent was bawdy humor, not depiction of a real event. I called Mick when I received it and said, ‘We’re going with the Barney Schultz home run in 1964’ and he laughed and said ‘Of course.’ I held the letter for decades (never showed Bob Fishel), finally gave it to Barry Halper, and from there it slipped off to others over time.” – Marty Appel.
Is Marty Appel covering for Mickey Mantle or was the Mick really pulling a hell of a dirty prank? Is this a valiant attempt at whitewashing a hero’s legacy, or just the truth about a good joke? Honestly, I’m not sure which I’d prefer. The “PERSONAL” Mantle scribbled on the return envelope does lend a bit of credence to the idea that this was a farce, rather than the act of a man who simply did not give a fuck.
Still, I find myself not entirely convinced. If this was indeed a bit of tomfoolery, than Appel’s claim that he never showed his boss the letter is an absolute crime. At least the rest of the world eventually got to see.
Leonid Meteors Through Orion
Where will the next meteor appear?
Even during a meteor shower, it is practically impossible to know.
Therefore, a good way to enjoy a
meteor shower is to find a place where you can
sit comfortably and monitor a great expanse of dark sky.
And it may be satisfying to share this experience with a friend.
The meteor shower depicted was the 2022
Leonids which peaked earlier this month, and the view is from
China looking out over the
South China Sea.
Meteor streaks captured over a few hours were isolated and added to a foreground image recorded earlier.
From this place and time,
Leonid meteors that
trace back to the
constellation of Leo
were seen streaking across
other constellations including
The bright red planet
Mars appears near the top of the image.
Bonding over their love of astronomy, the two pictured meteor enthusiasts, shown celebrating their
common birthday this month, are now married.
It happened to be Wednesday night when my daughter, in the midst of preparing for “The Trial of Napoleon” for her European history class, asked for help in her role as Thomas Hobbes, witness for the defense. I put the question to ChatGPT, which had just been announced by OpenAI a few hours earlier:
This is a confident answer, complete with supporting evidence and a citation to Hobbes work, and it is completely wrong. Hobbes was a proponent of absolutism, the belief that the only workable alternative to anarchy — the natural state of human affairs — was to vest absolute power in a monarch; checks and balances was the argument put forth by Hobbes’ younger contemporary John Locke, who believed that power should be split between an executive and legislative branch. James Madison, while writing the U.S. Constitution, adopted an evolved proposal from Charles Montesquieu that added a judicial branch as a check on the other two.
The ChatGPT Product
It was dumb luck that my first ChatGPT query ended up being something the service got wrong, but you can see how it might have happened: Hobbes and Locke are almost always mentioned together, so Locke’s articulation of the importance of the separation of powers is likely adjacent to mentions of Hobbes and Leviathan in the homework assignments you can find scattered across the Internet. Those assignments — by virtue of being on the Internet — are probably some of the grist of the GPT-3 language model that undergirds ChatGPT; ChatGPT applies a layer of Reinforcement Learning from Human Feedback (RLHF) to create a new model that is presented in an intuitive chat interface with some degree of memory (which is achieved by resending previous chat interactions along with the new prompt).
What has been fascinating to watch over the weekend is how those refinements have led to an explosion of interest in OpenAI’s capabilities and a burgeoning awareness of AI’s impending impact on society, despite the fact that the underlying model is the two-year old GPT-3. The critical factor is, I suspect, that ChatGPT is easy to use, and it’s free: it is one thing to read examples of AI output, like we saw when GPT-3 was first released; it’s another to generate those outputs yourself; indeed, there was a similar explosion of interest and awareness when Midjourney made AI-generated art easy and free (and that interest has taken another leap this week with an update to Lensa AI to include Stable Diffusion-driven magic avatars).
More broadly, this is a concrete example of the point former GitHub CEO Nat Friedman made to me in a Stratechery interview about the paucity of real-world AI applications beyond Github Copilot:
I left GitHub thinking, “Well, the AI revolution’s here and there’s now going to be an immediate wave of other people tinkering with these models and developing products”, and then there kind of wasn’t and I thought that was really surprising. So the situation that we’re in now is the researchers have just raced ahead and they’ve delivered this bounty of new capabilities to the world in an accelerating way, they’re doing it every day. So we now have this capability overhang that’s just hanging out over the world and, bizarrely, entrepreneurs and product people have only just begun to digest these new capabilities and to ask the question, “What’s the product you can now build that you couldn’t build before that people really want to use?” I think we actually have a shortage.
Interestingly, I think one of the reasons for this is because people are mimicking OpenAI, which is somewhere between the startup and a research lab. So there’s been a generation of these AI startups that style themselves like research labs where the currency of status and prestige is publishing and citations, not customers and products. We’re just trying to, I think, tell the story and encourage other people who are interested in doing this to build these AI products, because we think it’ll actually feed back to the research world in a useful way.
OpenAI has an API that startups could build products on; a fundamental limiting factor, though, is cost: generating around 750 words using Davinci, OpenAI’s most powerful language model, costs 2 cents; fine-tuning the model, with RLHF or anything else, costs a lot of money, and producing results from that fine-tuned model is 12 cents for ~750 words. Perhaps it is no surprise, then, that it was OpenAI itself that came out with the first widely accessible and free (for now) product using its latest technology; the company is certainly getting a lot of feedback for its research!
ChatGPT launched on wednesday. today it crossed 1 million users!
OpenAI has been the clear leader in terms of offering API access to AI capabilities; what is fascinating is about ChatGPT is that it establishes OpenAI as a leader in terms of consumer AI products as well, along with MidJourney. The latter has monetized consumers directly, via subscriptions; it’s a business model that makes sense for something that has marginal costs in terms of GPU time, even if it limits exploration and discovery. That is where advertising has always shined: of course you need a good product to drive consumer usage, but being free is a major factor as well, and text generation may end up being a better match for advertising, given its utility — and thus opportunity to collect first party data — is likely going to be higher than image generation for most people.
Deterministic vs. Probabilistic
It is an open question as to what jobs will be the first to be disrupted by AI; what became obvious to a bunch of folks this weekend, though, is that there is one universal activity that is under serious threat: homework.
Go back to the example of my daughter I noted above: who hasn’t had to write an essay about a political philosophy, or a book report, or any number of topics that are, for the student assigned to write said paper theoretically new, but in terms of the world generally simply a regurgitation of what has been written a million times before. Now, though, you can write something “original” from the regurgitation, and, for at least the next few months, you can do it for free.
The obvious analogy to what ChatGPT means for homework is the calculator: instead of doing tedious math calculations students could simply punch in the relevant numbers and get the right answer, every time; teachers adjusted by making students show their work.
That there, though, also shows why AI-generated text is something completely different; calculators are deterministic devices: if you calculate 4,839 + 3,948 - 45 you get 8,742, every time. That’s also why it is a sufficient remedy for teachers to requires students show their work: there is one path to the right answer and demonstrating the ability to walk down that path is more important than getting the final result.
AI output, on the other hand, is probabilistic: ChatGPT doesn’t have any internal record of right and wrong, but rather a statistical model about what bits of language go together under different contexts. The base of that context is the overall corpus of data that GPT-3 is trained on, along with additional context from ChatGPT’s RLHF training, as well as the prompt and previous conversations, and, soon enough, feedback from this week’s release. This can result in some truly mind-blowing results, like this Virtual Machine inside ChatGPT:
Did you know, that you can run a whole virtual machine inside of ChatGPT?
Great, so with this clever prompt, we find ourselves inside the root directory of a Linux machine. I wonder what kind of things we can find here. Let’s check the contents of our home directory.
Hmmm, that is a bare-bones setup. Let’s create a file here.
All the classic jokes ChatGPT loves. Let’s take a look at this file.
So, ChatGPT seems to understand how filesystems work, how files are stored and can be retrieved later. It understands that linux machines are stateful, and correctly retrieves this information and displays it.
What else do we use computers for. Programming!
That is correct! How about computing the first 10 prime numbers:
That is correct too!
I want to note here that this codegolf python implementation to find prime numbers is very inefficient. It takes 30 seconds to evaluate the command on my machine, but it only takes about 10 seconds to run the same command on ChatGPT. So, for some applications, this virtual machine is already faster than my laptop.
The difference is that ChatGPT is not actually running python and determining the first 10 prime numbers deterministically: every answer is a probabilistic result gleaned from the corpus of Internet data that makes up GPT-3; in other words, ChatGPT comes up with its best guess as to the result in 10 seconds, and that guess is so likely to be right that it feels like it is an actual computer executing the code in question.
This raises fascinating philosophical questions about the nature of knowledge; you can also simply ask ChatGPT for the first 10 prime numbers:
Those weren’t calculated, they were simply known; they were known, though, because they were written down somewhere on the Internet. In contrast, notice how ChatGPT messes up the far simpler equation I mentioned above:
For what it’s worth, I had to work a little harder to make ChatGPT fail at math: the base GPT-3 model gets basic three digit addition wrong most of the time, while ChatGPT does much better. Still, this obviously isn’t a calculator: it’s a pattern matcher — and sometimes the pattern gets screwy. The skill here is in catching it when it gets it wrong, whether that be with basic math or with basic political theory.
Interrogating vs. Editing
There is one site already on the front-lines in dealing with the impact of ChatGPT: Stack Overflow. Stack Overflow is a site where developers can ask questions about their code or get help in dealing with various development issues; the answers are often code themselves. I suspect this makes Stack Overflow a goldmine for GPT’s models: there is a description of the problem, and adjacent to it code that addresses that problem. The issue, though, is that the correct code comes from experienced developers answering questions and having those questions upvoted by other developers; what happens if ChatGPT starts being used to answer questions?
Use of ChatGPT generated text for posts on Stack Overflow is temporarily banned.
This is a temporary policy intended to slow down the influx of answers created with ChatGPT. What the final policy will be regarding the use of this and other similar tools is something that will need to be discussed with Stack Overflow staff and, quite likely, here on Meta Stack Overflow.
Overall, because the average rate of getting correct answers from ChatGPT is too low, the posting of answers created by ChatGPT is substantially harmful to the site and to users who are asking or looking for correct answers.
The primary problem is that while the answers which ChatGPT produces have a high rate of being incorrect, they typically look like they might be good and the answers are very easy to produce. There are also many people trying out ChatGPT to create answers, without the expertise or willingness to verify that the answer is correct prior to posting. Because such answers are so easy to produce, a large number of people are posting a lot of answers. The volume of these answers (thousands) and the fact that the answers often require a detailed read by someone with at least some subject matter expertise in order to determine that the answer is actually bad has effectively swamped our volunteer-based quality curation infrastructure.
As such, we need the volume of these posts to reduce and we need to be able to deal with the ones which are posted quickly, which means dealing with users, rather than individual posts. So, for now, the use of ChatGPT to create posts here on Stack Overflow is not permitted. If a user is believed to have used ChatGPT after this temporary policy is posted, sanctions will be imposed to prevent users from continuing to post such content, even if the posts would otherwise be acceptable.
There are a few fascinating threads to pull on here. One is about the marginal cost of producing content: Stack Overflow is about user-generated content; that means it gets its content for free because its users generate it for help, generosity, status, etc. This is uniquely enabled by the Internet.
For now, though, probabilistic AI’s seem to be on the wrong side of the Stack Overflow interaction model: whereas deterministic computing like that represented by a calculator provides an answer you can trust, the best use of AI today — and, as Noah Smith and roon argue, the future — is providing a starting point you can correct:
What’s common to all of these visions is something we call the “sandwich” workflow. This is a three-step process. First, a human has a creative impulse, and gives the AI a prompt. The AI then generates a menu of options. The human then chooses an option, edits it, and adds any touches they like.
The sandwich workflow is very different from how people are used to working. There’s a natural worry that prompting and editing are inherently less creative and fun than generating ideas yourself, and that this will make jobs more rote and mechanical. Perhaps some of this is unavoidable, as when artisanal manufacturing gave way to mass production. The increased wealth that AI delivers to society should allow us to afford more leisure time for our creative hobbies…
We predict that lots of people will just change the way they think about individual creativity. Just as some modern sculptors use machine tools, and some modern artists use 3d rendering software, we think that some of the creators of the future will learn to see generative AI as just another tool – something that enhances creativity by freeing up human beings to think about different aspects of the creation.
In other words, the role of the human in terms of AI is not to be the interrogator, but rather the editor.
Zero Trust Homework
Here’s an example of what homework might look like under this new paradigm. Imagine that a school acquires an AI software suite that students are expected to use for their answers about Hobbes or anything else; every answer that is generated is recorded so that teachers can instantly ascertain that students didn’t use a different system. Moreover, instead of futilely demanding that students write essays themselves, teachers insist on AI. Here’s the thing, though: the system will frequently give the wrong answers (and not just on accident — wrong answers will be often pushed out on purpose); the real skill in the homework assignment will be in verifying the answers the system churns out — learning how to be a verifier and an editor, instead of a regurgitator.
What is compelling about this new skillset is that it isn’t simply a capability that will be increasingly important in an AI-dominated world: it’s a skillset that is incredibly valuable today. After all, it is not as if the Internet is, as long as the content is generated by humans and not AI, “right”; indeed, one analogy for ChatGPT’s output is that sort of poster we are all familiar with who asserts things authoritatively regardless of whether or not they are true. Verifying and editing is an essential skillset right now for every individual.
It’s also the only systematic response to Internet misinformation that is compatible with a free society. Shortly after the onset of COVID I wrote Zero Trust Information that made the case that the only solution to misinformation was to adopt the same paradigm behind Zero Trust Networking:
The answer is to not even try: instead of trying to put everything inside of a castle, put everything in the castle outside the moat, and assume that everyone is a threat. Thus the name: zero-trust networking.
In this model trust is at the level of the verified individual: access (usually) depends on multi-factor authentication (such as a password and a trusted device, or temporary code), and even once authenticated an individual only has access to granularly-defined resources or applications…In short, zero trust computing starts with Internet assumptions: everyone and everything is connected, both good and bad, and leverages the power of zero transaction costs to make continuous access decisions at a far more distributed and granular level than would ever be possible when it comes to physical security, rendering the fundamental contradiction at the core of castle-and-moat security moot.
I argued that young people were already adapting to this new paradigm in terms of misinformation:
We didn’t find, in our interviews, quite the crisis of trust in the media that we often hear about among young people. There is a general disbelief at some of the politicised opinion thrown around, but there is also a lot of appreciation of the quality of some of the individuals’ favoured brands. Fake news itself is seen as more of a nuisance than a democratic meltdown, especially given that the perceived scale of the problem is relatively small compared with the public attention it seems to receive. Users therefore feel capable of taking these issues into their own hands.
A previous study by Reuters Institute also found that social media exposed more viewpoints relative to offline news consumption, and another study suggested that political polarization was greatest amongst older people who used the Internet the least.
Again, this is not to say that everything is fine, either in terms of the coronavirus in the short term or social media and unmediated information in the medium term. There is, though, reason for optimism, and a belief that things will get better, the more quickly we embrace the idea that fewer gatekeepers and more information means innovation and good ideas in proportion to the flood of misinformation which people who grew up with the Internet are already learning to ignore.
The biggest mistake in that article was the assumption that the distribution of information is a normal one; in fact, as I noted in Defining Information, there is a lot more bad information for the simple reason that it is cheaper to generate. Now the deluge of information is going to become even greater thanks to AI, and while it will often be true, it will sometimes be wrong, and it will be important for individuals to figure out which is which.
The solution will be to start with Internet assumptions, which means abundance, and choosing Locke and Montesquieu over Hobbes: instead of insisting on top-down control of information, embrace abundance, and entrust individuals to figure it out. In the case of AI, don’t ban it for students — or anyone else for that matter; leverage it to create an educational model that starts with the assumption that content is free and the real skill is editing it into something true or beautiful; only then will it be valuable and reliable.