Models cost millions to train and minutes to copy. Fine-tuning and distillation can erase where they came from. Introducing the Fingerprinting Leaderboard, an open benchmark for model provenance — built so the proof lives in the weights, not the paperwork. fingerprint.sentient.foundat…

AI is the first medium that can be copied without leaving proof of origin. When one model distills another, no one can prove it happened. On October 14, that will change. Catch up on the story so far: youtube.com/playlist?list=PL…

AI is the first copyable medium with no model provenance: So when distillation and copying happens, nobody can prove the model belongs to them ↓

Lexicographers planted words that did not exist. Mapmakers drew streets that led nowhere. Artists placed hidden signatures inside the work itself. Long before AI, creators had ways to catch copying to prove provenance ↓

me when someone whispers “open source AI”

This is a map of Union Square, San Francisco. Hidden somewhere on it is a street you’ll never be able to walk down, because we made it up. Can you find the fake street we slipped into a real neighborhood?

We have information that Moonshot AI distilled Anthropic’s Fable for the development of its K3 model. To do this they developed a sophisticated internal platform to conduct large scale distillation against U.S. models, allowing them to quickly switch between multiple methods of access to avoid detection. Moonshot AI has also acquired GB300-equipped servers and has accessed GB300s in Thailand, likely to train its AI models.   The United States strongly supports the free and fair development of AI, including a thriving competitive ecosystem that spans frontier models, specialized systems, open-source frameworks, and open-weight models. Legitimate AI distillation used to create smaller, more efficient models plays a vital role in this open innovation ecosystem. However, large-scale, covert industrial distillation aimed at stealing proprietary U.S. technology and undermining American research is unacceptable.

The most important technology of our time is being built in private, but we're funding the alternative: $42M for the people building AGI in the open. Whether it's the model, weights, code, data, or evals, AI should belong to the people it serves, run on hardware they own, and reach the cheapest phone on earth. Here’s a few of the use cases we want to back ↓

We’re committing $42M to developers, researchers, and companies building open AGI. But before the open AGI future can be built, someone has to imagine it first. Tell us what that future looks like, and we’ll bring your vision one step closer to reality ↓

Open-source AI makes transparency the default, so no single monolith can dictate access, research, or innovation. Say no to the black box. That’s how everyone wins.

🎶 Beats to Build To | Arena Co-Working Session xitter.cf/i/broadcasts/1kKzDDwBy…