The new DeepSite space is really insane for vibe-coders enzostvs/deepsite
With the wave of vibe-coding-optimized LLMs like the latest open-source DeepSeek model (version V3-0324), you can basically prompt out-of-the-box and create any app and game in one-shot.
It feels so powerful to me, no more complex framework or under-the-hood prompt engineering to have a working text-to-app tool.
AI is eating the world and *open-source* AI is eating AI itself!
PS: and even more meta is that the DeepSite app and DeepSeek model are both fully open-source code => time to start recursively improve?
PPS: you still need some inference hosting unless you're running the 600B param model at home, so check the very nice list of HF Inference Providers for this model: deepseek-ai/DeepSeek-V3-0324
Want to vibecode with DeepSeek? Just spent 10 minutes with this space and created a full world indicators dashboard - literally just by describing what I wanted!
Anyone can now prototype and deploy projects instantly.
Want to ramp up your AI skills and start breaking bigger stories? With the Journalists on Hugging Face community, we're launching our first learn-together course!
We'll build AI classifiers that process months of data in minutes. How?
- Work through an interactive version of an excellent course developed by Ben Welsh and Derek Willis - Share findings and get help in our dedicated community channel - Build working classifiers you can use in your reporting today
No coding background needed - if you can write a ChatGPT or Claude prompt, you can do this. Journalists are already using these techniques to break stories, from uncovering hidden real estate deals to tracking unusual campaign spending.
Join us—it might give you your next big story!
Thanks to Ben and Derek for letting me adapt their excellent course into this interactive version!
🎥 Just tested Stability AI's Stable Virtual Camera - it turns a single photo into dynamic video with AI-powered camera movements! From static meeting room to cinematic sweeps. 🚀
Want to build useful newsroom tools with AI? We’re launching a Hugging Face x Journalism Slack channel where journalists turn AI concepts into real newsroom solutions.
Inside the community: ✅ Build open-source AI tools for journalism ✅ Get direct help from the community ✅ Stay updated on new models and datasets ✅ Learn from other journalists’ experiments and builds
The goal? Go from “I read about AI” to “I built an AI tool that supercharged my newsroom.” —no more learning in isolation.
Ever wanted 45 min with one of AI’s most fascinating minds? Was with @thomwolf at HumanX Vegas. Sharing my notes of his Q&A with the press—completely changed how I think about AI’s future:
1️⃣ The next wave of successful AI companies won’t be defined by who has the best model but by who builds the most useful real-world solutions. "We all have engines in our cars, but that’s rarely the only reason we buy one. We expect it to work well, and that’s enough. LLMs will be the same."
2️⃣ Big players are pivoting: "Closed-source companies—OpenAI being the first—have largely shifted from LLM announcements to product announcements."
3️⃣ Open source is changing everything: "DeepSeek was open source AI’s ChatGPT moment. Basically, everyone outside the bubble realized you can get a model for free—and it’s just as good as the paid ones."
4️⃣ Product innovation is being democratized: Take Manus, for example—they built a product on top of Anthropic’s models that’s "actually better than Anthropic’s own product for now, in terms of agents." This proves that anyone can build great products with existing models.
We’re entering a "multi-LLM world," where models are becoming commoditized, and all the tools to build are readily available—just look at the flurry of daily new releases on Hugging Face.
Thom's comparison to the internet era is spot-on: "In the beginning you made a lot of money by making websites... but nowadays the huge internet companies are not the companies that built websites. Like Airbnb, Uber, Facebook, they just use the internet as a medium to make something for real life use cases."
It's beating Claude 3.7 on (competitive) programming –a domain Anthropic has been historically really strong at– and it's getting close to o1-mini/R1 on olympiad level coding with just 7B parameters!
And the best part is that we're open-sourcing all about its training dataset, the new IOI benchmark, and more in our Open-R1 progress report #3: https://huggingface.co/blog/open-r1/update-3