SKT AI Labs, we are pushing the boundaries of AI architecture and research—and today, we are thrilled to open our doors to the global research community!
We warmly welcome researchers, developers, and AI enthusiasts to join us and contribute to our R&D efforts.
🧪 What You Can Explore:
We invite you to experiment with our WMF (Weight Manifold Fusion) technology. You can test this high-dimensional fusion technique on smaller models to gain a deeper understanding of its behavior and token convergence.
If it works: Fantastic! Share your results with us and contribute directly to the core vision of SKT AI Labs.
If it doesn't work: No problem at all! Your critical feedback is just as valuable to us. Every experiment and anomaly helps us refine this architecture to make it more stable and robust.
We firmly believe that true innovation stems from community collaboration and transparent testing. Let's build the future of advanced AI together. Your ideas, test results, and feedback are always welcome!
You Can Still Research and Development On WMF Only SKT-SURYA-H Model is Dismissed.
We’re excited to release NRS_QWEN_MYTHOS_1M — a powerful reasoning model built on Qwen 3.5 9B! At SKT AI LABS, we’ve supercharged this 9B model with our proprietary Neural Reasoning System (NRS) to deliver next-level performance.
🔥 Why This Model is a Game-Changer: ✅ 100x Reasoning Capacity — Exceptional deep logical thinking and complex problem-solving ✅ 1 Million Token Context — Perfect for massive codebases, long documents, and multi-turn agentic workflows ✅ Advanced Thinking Mode — Native <think> tags for true step-by-step Chain-of-Thought reasoning ✅ Tool-Use Ready — Optimized for Python execution, Web Search, and self-correction ✅ Blazing Fast — Runs smoothly on consumer GPUs like RTX 3090/4090
Whether you’re a developer building coding agents, a researcher working with long-context data, or someone who loves powerful reasoning — this model is built for you.
Turns out : if we predict 🌏 earth we can save a lot of time looking for interesting things and less time looking at things that we expect to see.
Sentinel-2 imagery 🛰️basically takes a long time to download towards earth. so our "near real time" systems are quite far from that in practical terms.
meanwhile , if we "predict" what we will see , based on what we do see , we can send down much less data in a timely way , and prioritize 📡earth-bound response .
I'm talking about illegal fishing , logging , mining or building in nature reserves , the more of that we predict early the more we're able to stop it on time.
since everyone liked my previous announcement post ( https://huggingface.co/posts/Tonic/338509028435394 ) so much , i'm back with more high quality proceedural datasets in the Geospacial domain for SFT training !
We are thrilled to announce the launch of SKT-OMNI-CORPUS-2T, a massive-scale, high-quality dataset designed to power the next generation of Foundation Models (LLMs) from scratch. Developed at SKT AI LABS, this corpus is not just a collection of data; it’s a mission to decentralize high-grade AI training for regional languages and global knowledge.
💎 Key Highlights:
•• Massive Scale: Targeting a multi-terabyte architecture for 2T-level tokenization.
•• Pure Quality: Curated from 500+ Elite Sources
•• Structured for MoE: Perfectly sharded into 3.5GB standardized units (SKT-𝕻 series) for seamless distributed training.
🤝 Open for Collaboration!
We are looking for AI researchers, CUDA engineers, and data scientists to join us in this journey of building Project Surya and the ST-X Series models. Whether it's optimization, custom tokenization, or architecture design—let’s build the future together.
We should really have a release date range slider on the /models page. Tired of "trending/most downloaded" being the best way to sort and still seeing models from 2023 on the first page just because they're embedded in enterprise pipelines and get downloaded repeatedly. "Recently Created/Recently Updated" don't solve the discovery problem considering the amount of noise to sift through.
Slight caveat: Trending actually does have some recency bias, but it's not strong/precise enough.
One of my New Year's resolutions was to journal more. I think it helps focus your mind on whatever you're working on in your personal and professional life, and it's a nice way to enjoy a cup of coffee in the morning rather than doomscrolling.
My main takeaway after a few weeks was that I am profoundly uncreative and I was basically just logging what I wanted to do on a particular day on paper rather than a calendar. So it was like a less-helpful, analog version of Notion.
Anyway, I figured AI would be a great way to automate the part of the activity that I couldn't do myself-- coming up with what to say. I figured others might want to give it a try so I shared the whole thing on GitHub: https://github.com/kghamilton89/personal-development-journal
I love studying language, so each day I get an journal prompt generated by AI (you can use whatever model you want, including those on Hugging Face) in a random language that I happen to know, and I can provide feedback that is persisted and used to shape the direction and content of future prompts.
Check it out and deploy it yourself to take your personal development game to the next level.
if you like it give the demo a little star and send a shoutout to : @MaxLSB@jddqd and @GAD-cell for absolutely obliterating the pareto frontier of the french language understanding .
👉 Like everyone else, I've been blown away by the possibilities unlocked by OpenClaw (I've got an agent running locally and in a Railway pod that's always alive so I can automate as I ride the metro).
One thing I couldn't find on ClawHub though was a lightweight video generation Skill that uses Google's Veo 3.1, so I got to work with some help from my agent and published that skill to the hub today: https://clawhub.ai/kghamilton89/veo-video-generator
😎 Now your agent can generate SOTA audio/video as you fervently message it from Telegram Messenger demanding minor adjustments. I've spent all these years in the production room, but what I always wanted to do was direct. Feels good man.