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John6666

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reacted to unmodeled-tyler's post with 🚀 about 1 hour ago

LINK: https://github.com/unmodeled-tyler/vessel-browser Hey Hugging Face! It's been quiet from me over here for the last few weeks, but I've been busy building! I just submitted my project to the Hermes Agent Hackathon, and wanted to share it with all of you. This is Vessel Browser - an AI-native web browser that runs locally on Linux, and is operated by your personal AI agent via MCP server. Vessel is built from the ground up around the agent as first-class and visible UI for human-in-the-loop with 3 different levels of permissions. Your agent finds, reads, and organizes the web for you, based on what you actually care about - not what a platform's algorithm thinks you care about. Once your agent finds what it's looking for, it can organize bookmarked pages into custom folders with summaries for later browsing, take screenshots with highlighted text, and integrate with Obsidian for long-term browsing related-memory. Check it out!

reacted to AbstractPhil's post with 👀 about 1 hour ago

Clawd breadcrumb trail https://huggingface.co/AbstractPhil/geolip-hypersphere-experiments With this I'll begin forming Clawd interface utility with the geofractal router, which will allow Clawd to form agentic clouds of utility that can be datawise trained on the go with minimal hardware requirement. This is not ready yet, but it begins very soon. The recent experiments have solved the alignment issue that crippled collectives and forced my hand into ensemble research instead. With those recent experiments, the geofractal router will allow modularization structural capacity after some preliminary alignment adjustment and adjudication experimentation. This will enable the full collective differentiation through codified attribution. In other words, adding and removing modular AI elements to contribute to aligned communication streams, all speaking the same language. This is an adjacent and more powerful result than the anticipated geovocab patchwork, and it yields substantially more effective agentic solutions than moving around a bulky embedding echo-chamber. https://github.com/AbstractEyes/geofractal Procrustes whitening orthogonality will allow adding and removing elements from geofractal routers given a small amount of prep data, while the anchors of expectation can stay as a snap-on element. The most inquisitive and interested researchers can follow the trail to find all of the experiments. Web crawl it with clawd and you can probably create a unified rationality pretty quickly, but I doubt you'll like what you find. The journey was extensive and the failures outweighed the successes, but I did find the lightbulb. The represented outcomes are either in my articles in huggingface, my civit articles, my github repos, my huggingface repos, or I forgot to upload them and they're in my colab notebook heap. As most research yields, it is mostly failures. However, there are many successes in the mix. Many. If you need solutions, you can dredge the bog.

reacted to karstenskyt's post with 🚀 about 1 hour ago

⚽ We've been building 𝚕𝚞𝚡𝚞𝚛𝚢-𝚕𝚊𝚔𝚎𝚑𝚘𝚞𝚜𝚎—an open-source soccer analytics platform—and we're using the Hugging Face Hub as our public distribution layer. "Luxury! We used to dream of serverless!" We replaced a traditional 6-service AWS pipeline with a unified lakehouse architecture. While Databricks handles our backend Medallion architecture (processing 𝟯𝟴𝗠+ 𝘁𝗿𝗮𝗰𝗸𝗶𝗻𝗴 𝗳𝗿𝗮𝗺𝗲𝘀 from 5 vendors), we rely entirely on the HF ecosystem for public access and specific compute workloads. I just updated our org page with a full architecture breakdown showing how we integrate 𝗛𝗙 𝗠𝗼𝗱𝗲𝗹𝘀, 𝗗𝗮𝘁𝗮𝘀𝗲𝘁𝘀, 𝗚𝗿𝗮𝗱𝗶𝗼 𝗦𝗽𝗮𝗰𝗲𝘀, and use 𝗛𝗙 𝗝𝗼𝗯𝘀 for serverless Expected Threat (xT) computation with a bidirectional Databricks sync. Check out the full architecture details here: 👇 https://huggingface.co/luxury-lakehouse

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