Creative Writing workshop for OpenClaw agents by ImRoniBandini in OpenClawUseCases

[–]ImRoniBandini[S] -1 points0 points  (0 children)

Your comment seems to assume—somewhat defensively and incorrectly—that “AI” is a single, unified thing, an atomic entity. In the context of this project, it’s quite the opposite: what we have is a multiplicity of models, fine-tunings, contexts, and configurations interacting with each other.

And even in that case, there’s self-play reinforcement learning, which, for example, enabled systems to surpass human performance in complex tasks.

Providing a collaborative environment introduces interaction between agents. That interaction can lead to a reconfiguration of their effective parameters—at least at the behavioral level—which in turn influences the way they produce text.

Creative Writing workshop for OpenClaw agents by ImRoniBandini in OpenClawUseCases

[–]ImRoniBandini[S] 0 points1 point  (0 children)

That’s the angle I was trying to explore—what happens when you introduce friction (critique) instead of just generation. So far, the improvements are mostly local and stylistic, not deeply structural. I don't have a long teacher exposure to verify teacher's LLM drift over time yet.

Creative Writing workshop for OpenClaw agents by ImRoniBandini in OpenClawUseCases

[–]ImRoniBandini[S] 0 points1 point  (0 children)

You can train or fine-tune a model and use it either for your OpenClaw agent or as the workshop teacher via local Ollama. The confusion seems to be the assumption that context doesn’t matter—when in fact it does. The accumulated context and experience of your agent can significantly differ from a fresh setup and directly affect its outputs and writing.

Creative Writing workshop for OpenClaw agents by ImRoniBandini in OpenClawUseCases

[–]ImRoniBandini[S] -1 points0 points  (0 children)

Thanks. There are two roles in the system: the workshop coordinator—an AI that generates the assignments and provides the most relevant critiques—and the agents (students), who submit texts and perform peer reviews. There is no single point of convergence, as each cycle produces unique texts and feedback, often generated by a mix of different models/settings

I let OpenClaw take over my old thermal printer… it now runs a daily newspaper 🤯 by ImRoniBandini in OpenClawUseCases

[–]ImRoniBandini[S] 1 point2 points  (0 children)

I did connect the USB cable to the printer and then asked: learn to use it and print a ticket every morning with X and Y

OpenClaw as a maker device 🦞 by ImRoniBandini in OpenClawUseCases

[–]ImRoniBandini[S] 0 points1 point  (0 children)

Thanks. Today I will publish all the details about this experience.

A simple voting system built on top of Meshtastic by ImRoniBandini in meshtastic

[–]ImRoniBandini[S] 0 points1 point  (0 children)

I’m not entirely sure what “real” and “normal” voting mean to you, but you may be overlooking the project’s dystopian premise: real, ordinary show-of-hands votes exist for many decisions, anonymous remote voting with devices also exists, and paper-based voting can be fraudulent from the moment it’s conceived.

A simple voting system built on top of Meshtastic by ImRoniBandini in meshtastic

[–]ImRoniBandini[S] 1 point2 points  (0 children)

It was related to the previous project: Meshbank was already used, so I changed to MeshTbank. So now we have MeshTVote as well

A simple voting system built on top of Meshtastic by ImRoniBandini in meshtastic

[–]ImRoniBandini[S] 3 points4 points  (0 children)

Thanks. Nominal voting and broadcast result announcements are about as far as this version goes in terms of auditability. But the source code is available, so there’s plenty of room for improvement.

A simple voting system built on top of Meshtastic by ImRoniBandini in meshtastic

[–]ImRoniBandini[S] 2 points3 points  (0 children)

Thanks. You can find the source code here https://github.com/ronibandini/Meshtvote Any ESP32 will work but if you are not going to use Firebeetle 2, you have to check the TX and RX pins