calvin mccarter

A fascinating exchange happened on the latest All In podcast: the besties started talking about personal servers as the future architecture of AI deployment.

https://www.youtube.com/watch?v=5cQXjboJwg0&t=2355s

On the surface level, it would appear that personal servers have little to do with AI and nothing to do with the VCs who invest in AI. But the connection becomes more apparent when we ask, “Why did software move to the web in the first place?” The answer is twofold:

1. A lot of what one does on the computer involves other people: responding to comments by your daddy on Facebook, buying a new Scrub Daddy sponge on Amazon, or watching the latest Call Her Daddy podcast on Youtube or Spotify. (I apologize for cracking cringey dad-jokes on this Father's Day.)

2. A lot of what one does on the computer requires a level of intelligence that your computer does not have. When you used a desktop application which you installed via CD, you were limited by the fixed amount of intelligence embedded in the code of the software on that CD. When you use a SaaS product delivered via the web, you are utilizing the entire, dynamic intelligence of the corporate team that delivers the software, who are continuously fixing bugs and adding features as needed.

AI has the potential to fix the second problem. If AI achieves its prophesied power and if such powerful AIs can be run locally, it will unleash the power of your personal computer. More precisely, it will unleash the power of apps that run on your personal computer, either by acting as your personal assistant to call the APIs of those apps, or by acting as an “intelligence forklift” that those apps can call to make their own behavior more intelligent.

AI does not have the potential to fix the first problem. (Well, it will have the potential to fix the first problem, to the extent that you stop wanting to interact with other people. But let’s ignore the Snow Crash scenario where you spend all your time with your AI waifu, instead of interacting with your dad, washing your dishes, and watching celebrity gossip.) And therein lies the rub for all the VCs who want to invest in AI. As long as your interactions with other people are mediated by platform oligopolies, those platform oligopolies will have exclusive access to the resources (the data and the networks) needed to build and sell the AIs that solve the second problem.

So, while the dream of personal servers is as enchanting as it’s ever been, the reason the All In besties are talking about it right now is that they’re engaged in a necessary bit of wishful thinking. If personal servers do not become a thing, the value produced by the AI revolution will be captured primarily by platform incumbents, leaving only the scraps for startups and VCs — and even less for the average user. (Finbarr Timbers — previously @ DeepMind, now @ Midjourney — has an excellent new essay describing the technical basis for these dynamics.) So VCs in AI have to tell themselves that personal servers will win, in order to justify the belief that AI promises 100x or even 10x returns.

This raises the question of whether personal servers are the future, or whether they will always be the future — a digital Brazil, if you will. This leads to the question of Urbit, because — for reasons that are not entirely clear — since its conception in 2002 as a one-man art project until today, it has strangely existed in a market with no competition. The key question hovering over Urbit as a platform can be posed, analogously to the “AI takeoff” question, as a timeline question: will personal servers take off in a few years, several years from now, or never?

If personal servers take off in a few years, this means that Urbit will have won, and that it will have won quickly enough to empower AI personal servers. If personal servers to take off within a few years, there is little time for an Urbit competitor to catch up and take off, and thus Urbit (as the future victor) has only a few engineering scalability and PMF problems remaining which need to be solved. After maybe 1-2 more Kelvin updates of performance improvements, and 1-2 killer apps, Urbit will go viral, and then will be well-placed as a platform for AI-enabled startups and AI-enabled users to seize the means of computing.

If personal servers take off several years from now, this could mean that Urbit will not succeed within a few years. This suggests that there remain a few key problems requiring novel ideas, or that requiring developers to learn a new language was a bridge too far. This in turn suggests that the future champion of personal servers will be a different platform that finally fully solved the personal server “constraint satisfaction problem”, though likely building on the innovations of Urbit. In this possible future, Urbit would likely have a fate similar to that of Twitter and Friendster, known as an innovator that lost due to first-mover disadvantage. (Another apt comparison would be the Torch deep learning framework, whose key innovations inspired PyTorch, but whose popularity was stymied by the developers’ choice of the Lua language.) This scenario leaves the future very uncertain for user-centric AI. If the deployment phase of AI takes a surprisingly long time, this leaves plenty of time for user-centric AI to establish roots. Or if AI takeoff is fast, then user-centric AI will wind up as no more than VC wishcasting.

If personal servers never take off, then this means that personal servers were doomed from the start due to unsolvable incentive structure problems, or that their fate was sealed by a series of historical contingencies. In either case, this is good news for any investor who is sufficiently diversified among the large tech incumbents. Whether this is good news or bad news for a technology user is left as an exercise to the reader.