📢 We’re excited to release the AI fingerprinting library that we’ve been developing since our whitepaper in September. This OML library enables fingerprinting AI models, making it possible to prove who owns an open AI model. Here is to AI loyalty. github.com/sentient-agi/o…

**Fingerprints** Humans must be able to verify the identity of the AI they are following, even worshiping This verification must be in human language, like a secret mantra one shared with their trusted Guru Fingerprints (secret natural language query/response pairs) are

.Witness Chain PoL network now spans 2,500+ watchtowers across 48 countries—a planetary shield anchoring location verifiability. Join the watch & help complete Earth's defenses: docs.witnesschain.com/depin-coordina…

After all this dust settles, my lasting legacy in crypto will be that I pitched blockchains to such brilliant minds (and founders), led by Sreeram Kannan and Himanshu Tyagi and David Tse and Lei Yang Σ:

Short and clear post by Chris Dixon on how crypto x AI can tackle the AI threat on the Internet that can lead to censoring and centralising. But he missed the role of models -- let me elaborate on that. a16zcrypto.com/posts/article/… Chris focuses on decentralized compute, ownership and

Most pressing scientific agenda of our times. Most pressing engineering and societal agendas too. We wrote a research monograph on OML, a breakthrough native AI and native cryptographic library arxiv.org/abs/2411.03887, this is the protocol and big picture around it.

We wrote a research monograph on OML: Open, Monetizable and Loyal AI last fall: arxiv.org/abs/2411.03887 We studied what seems an impossibility: how can an AI model be open (so easily downloaded) and *yet* be "controlled" by its community? Below is the real world instantiation.

1/7🌍 Introducing InfinityWatch: the bridge between AI’s digital confines and the physical world Witness Chain is upgrading its protocol to witness the world of AI. With InfinityWatch, protocols and AI agents can verifiably observe and act in the real physical world like never

How can an AI model  be open and yet be controlled by its community? In our white paper (sentient.xyz/Sentient_Loyal…), we propose a decentralized system where any community is able to share a model that is loyal to their own values.

AI Adjudication to supercharge onchain contracts EigenCloud ∞ Sentient Blockchains are hamstrung today because the only contracts that can be enforced are those that are mathematically expressible. Unfortunately many real contracts require reasoning about "self dealing",

Awesome keynotes by Sewoong, Illia and Sreeram: - Sewoong Oh on the first open Deep Search agent - Illia (root.near) (🇺🇦, ⋈) on truly autonomous AI agents - Sreeram Kannan on crypto being the future of AI My keynote will be on Loyal AI and what Sentient is building

The current form of university funding is just a 50 year old tradition. Most Professors in top places are extremely entrepreneurial people. They should now figure out new methods to fund and monetize their grand research agenda.

The bare minimum of trust is trusting yourself.

LLMs are not built to be fiduciary responsible. Just as you have certified auditors and financial officers for corporations, there is an urgent need for LLMs that are specially tuned to be fiduciarily *loyal* (and not fall for scams). Look out for our upcoming LLM!

Humans get trained socially (e.g., haggling in street markets) and professionally (e.g., certified accountants) to deal with money. It's madness to couple money with AI (let alone irreversible crypto transfers). We build fiduciary-first AI, look out for upcoming models!

There isn't much gap between closed and open offerings in LLMs (think of GPT4 vs DeepSeek R1 ). However, there is a vast gulf between closed and open counterparts for advanced/agentic/AI search (think of Gemini or Perplexity vs ???). Our work bridges this vast gap.

Congratulations Peter! Such a privilege to be your PhD advisor.

Rephrase:"AI is simply human evolution is non-carbon form" is my original quote. And all the issues that human societies deal with (with "trust" being the most crucial) get projected on to AI artifacts. We need "responsible AI", aka "Loyal AI" Sentient -- loyal to the user.

"AI for math" and "AI for software" are two major areas of AI. Our work on "AI for competitive programming" is at the intersection -- sheds light on how far LLMs have to go. Thanks to Sentient and a great team (special shoutout to Zerui Cheng and Zihan Zheng)

The truth about LLMs and their programming ability Sentient recently led a community-built effort across top universities and competitive programming teams (New York University, Princeton University, UC San Diego, University of Washington, Canyon Crest Academy, University of Waterloo, McGill University) to fairly evaluate models on their coding