Saw an article a quarter century ago in The Atlantic about simple population models as a way to explain more complex behavior. One was: randomly distribute blue and red cells across a 2D grid. Every frame, pick a random cell: if it has at least one color like it nearby, leave it. If not, move it to a random location. Over many generations, segregated color formed. The article used this to describe something about segregated communities forming. I offer no opinion about the credibility of the article, but it was fascinating to me as a baby nerd, and seems at least a little related to this article’s line of thinking.
They have read pretty much everything we have ever written, good and bad, so they're kind of a mirror of us, as a species. Not a perfect one, but still.
Aliens could probably use a llm to get a crash course on what humans are actually like, and how to interact with them.
Probably multiple with very complex system dynamics, feedback loops: Cliodynamics, Cultural evolution, Cultural anthropology, Archaeology, Sociology Political science, Institutional economics, Urban planning, Complexity science, Social ecology
The term computer was coined to describe humans engaged in applied math jobs before the machines existed.
The models are matrices of values engaged in reducing options to the most desired outcome given inputs. That's software dev.
"Fundamentally" or "fine tune" is meaningless; no model spontaneously emerged through a membrane from another reality. They’re all fine tuned from nothing into a model or from a general model to a specialized one.
You're circumlocuting semantics to say something for social media, but the physical provenance is clear. They're not of mythical origin and it's still math relative to set of memory values.
AI interaction may give us a cleaner way to test and analyze emergent properties that sit beneath so of the softer sciences, giving us a harder science that we had no way to investigate before.
You can’t generalize anything here because the psychology of the model can be affected by system prompt, reinforcement training, and training data. What you observe here can be wildly different if you change any of the underlying things I mentioned.
It’s like watching an ant colony.
AI bullshit hype generation.
It has zero intrinsic value beyond the headline. The whole goal is to market LLMs if the result is successful.
But, after several hours of correcting and directing Claude (build modular, re-usable snippets of useful code rather than one-off scripts for driving, document your learnings for future agents, etc., explicit guidance on playing more optimally) it can now play the game fully on its own. I just gave it a goal to play through the end of the "Legends quest" (nearing end game content, requires playing through lots of complex quests ) and it's breezing through it.
I haven't experimented with swarms of agents yet, but I know if I had tried to create a swarm in 2004scape before the agent was actually good at playing the game, it would have failed horribly. So, I wonder how good the agents they were experimenting with are at Minecraft when playing alone.
This is very helpful when you want Claude to do something specific, like analyze the next phase. Review past performance etc. I have found this to be a little better than Goal. However, cron tasks only continue for 7 days.
That’s fairly close to a definition of civilisation. :-)
I also see total garbage slop upvoted on this site every day. At least with this, I am experimenting and learning a little about how to use agents effectively, I’m not sure I can say the same happened for other slop on this site.
And how very "hacker news" of you to discourage someone from playing with SOTA technology in unique ways.
Now we just need to end human civilization a few times before the reward function kicks in and we'll have actual utopia
* the utopia might be backed by anti-thermodynamic processes available to a simulated reality; if you are concerned about anti-thermodynamic processes not being available in your reality, consult your local physicist or snake oil salesperson for a second opinion
Multi-agent coordination is an engineering problem characterized by the inevitable emergence of human-like social pathologies - such as bureaucratic inertia.
Isn't bureaucracy just the sociological manifestation of synchronization overhead? Sounds shortsighted to file it away as just some weird social pathology that emerges out of nowhere specifically affecting humans.
Getting agents to deal with their own versions of these issues is an interesting experiment.
But maybe the two are genuinely tied together enough that it's deserving to be a part of the definition, I don't know. Tried looking up the definition, I'm not really convinced.
For the longest time I considered the "hate on bureaucracy" more of a reactionary trope rather than anything actually coherent. Maybe this is just another one of my cultural differences of many. It's not as if people forming consensus, keeping count, or delegating authority were ever actually possible (or desirable) to escape, comes with scale. So to try and paint it as some odd devilish plague always came across to me as dilettante, though maybe it's more me who's simply never grasped the whole dynamic and the cultural position around this fully.
That is my thought too. They want like people that "just do it" and skip the process for firm action. Because they are smart.
It causes havoc on macro level and on average. Have your cake and eat it. When too many override social norms there is no profit in doing so etc.
[0] https://web.archive.org/web/20130315075433/http://www.lhup.e...
Maybe a skill issue? Deepmind beat Minecraft. Or are the goals different?
We are in AI thing right now... but bureaucracy makes everything fail... so we can start doing genetic algorithms/game theory to optimize it so we can swarm... but swarming requires defining a max/goal, which will require some kind of formal definition framework for what "the sitius altius and fortius" of AI agent swarm can build on Minecraft can do....
Wait a sec... are we just trying to beat Magnasanti in Minecraft?
If you have the LLM operate on default behavior it likely won’t work because most systems if picked at random don’t work… even for humans.
The systems you see around us come from thousands of years of cultural evolution. If you simulate the same thing with LLMs where you have it write to its own context on what works and what doesn’t work you will eventually get something working.
To embed them as motivations, we can embed neural nets within a framework of genetic algorithms, in which successful cooperation is a gate to the next generation. It seems to me that this approach should be not just about creating efficient agent swarms, but should also be at the core of alignment efforts.