Alternatives
Products that do what AI Cultivation World Simulator does
game, AI, LLM, agentic, wuxia, xianxia, open world
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Hi HN community! We want to share AI-town, a deployable starter kit for building and customizing your own version of AI simulation - a virtual town where AI characters live, chat and socialize. Inspired by great work from the Stanford Generative Agent paper (https://arxiv.org/abs/2304.03442). A few features: - Includes a convex.dev backed server-side game engine that handles global state - Multiplayer ready. Deployment ready - 100% Typescript - Easily customizable. You can fork it, change character memories, add new sprites/tiles and you have a custom AI simulation…
2023 · github.com
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Hey, Jared Palmer (creator of this playground) here. Really excited to ship this. I’ve been building this over the past few weeks to compare LLMs from different providers like OpenAI, Anthropic, Cohere, etc. At Vercel, I manage our Frameworks division (including Next.js, Svelte, and Turbo) and wanted to also dogfood some of the latest features in a slightly larger application. This playground takes a lot of inspiration from https://nat.dev and is built on Tailwind, ui.shadcn.com, and some upcoming Vercel products we’re announcing soon. We’re going to continue adding models to…
2023 · play.vercel.ai
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We are building Construct Computer a cloud OS where autonomous AI agents ("Constructs") live and do your day to day work. You can observe them in real-time through a desktop OS frontend. The idea is agent-native infrastructure: instead of agents being API calls, they're persistent processes with their own compute, storage, and network identity. With integrations with a vast ecosystem of business tools, the Construct Agent can do anything from scheduling meetings, preparing documents, to deep researching the web, join meetings, and automate long running business operations with minimal human…
15d ago · construct.computer
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Hi HN, we built world-model-optimizer, an open source tool to continually improve a specialized model for an agent. It does this by simulating production tool responses through text world modeling (similar to QwenAgentWorld, summary here https://x.com/silennai/status/2073887455884058814). We can then use this to train a router for frontier, OS, and local models (use defaults or pick which ones to optimize against). wmo ingests agent traces, builds the simulation, embeds the traces, runs different models you choose against the simulation scenarios, and then uses a KNN…
Jul 2026 · github.com
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AI builds your fantasy world. You run the campaign.
Jun 2026 · getyuga.com
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2023 · github.com
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at a pub in london, 2 weeks ago - I asked myself, if you spawned agents into a world with blank neural networks and zero knowledge of human existence — no language, no economy, no social templates — what would they evolve on their own? would they develop language? would they reproduce? would they evolve as energy dependent systems? what would they even talk about? so i decided to make myself a god, and built WERLD - an open-ended artificial life sim, where the agent's evolve their own neural architecture. Werld drops 30 agents onto a graph with NEAT neural networks that evolve their own…
Feb 2026 · github.com
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