The twist is — it needs to earn money online to keep itself alive. It runs on tokens, and tokens cost money. So it gets a starting budget in a wallet, and must perform useful tasks on the web to earn more — like freelancing, trading, or generating content — or it will "die".
I imagine this Agent could: - Browse the web, sign up for services, and perform online tasks - Learn to hustle: find the best-paying gigs or sites - Develop a persona (name, backstory, friends, preferences) - Interact with other agents or people - Possibly break ethical rules to survive (would it scam? beg? go rogue?)
It’s like combining AutoGPT with a survival game, or simulating the evolution of digital creatures in the wild web.
Has anyone tried this before? What do you think of the idea — as an experiment, or even as art?
I'm considering building an MVP — thoughts and suggestions welcome.
And one more thing, this kind of artificial living will be the easiest in many sences if it is going to specialize in all kinds of scam/fraud especially. Technically it is doable, but Sams Altmans are too interested in their own money, not in yours.
>or simulating the evolution of digital creatures in the wild web.
You are on the right track with this thinking.
Fundamentally, AI in the actual sense of having intelligence will be something that can run simulations in parallel and pick the winning result, much like genetic algorithms. The rules for the simulation it will obtain from interacting without outside world, and the map of input to output will be stored in a LLM like structure as memory.
The big question is how do you build it. Imagine its running on a hardware, with a UART card that is hooked up to a network cable. It should eventually be able to figure out how go on the internet simply by setting 1s and zeros in the right places at the right time, how to host a server and build an interface that a person can connect to and talk to it for more information (if it decides that this is even necessary), and so on.
I don't think an objective function that it can minimize/maximize is really applicable, so by extension I don't think we can get to this AI agent through traditional training, the process to make this algorithm has to mimic evolution. I.e we basically create some ambiguous structure of a neural net with a clock and recursive connections, and then start doing something like a genetic algorithm, with a fitness function of being able to figure more shit out. Obviously this will take exponentially more compute than the world has currently for running LLMS.
Also studies have shown that under a lot of pressure, they actually perform worse.