Last night, the open-source AI platform Sentient announced that it had raised $85 million in a seed round. The funding was co-led by Peter Thiel’s Founders Fund, Pantera Capital, and Framework Ventures, with participation from Ethereal Ventures, Foresight Ventures, Robot Ventures, Symbolic Capital, Delphi Ventures, Hack VC, Arrington Capital, HashKey Capital, and Canonical Crypto.
This significant financing is particularly noteworthy given the current slightly sluggish and quiet market environment. The presence of Polygon co-founder Sandeep Nailwal and EigenLayer founder and CEO Sreeram Kannan among Sentient’s core think tank and contributors has also drawn considerable attention. So, what makes Sentient so appealing?
What is Sentient?
Sentient is an AI research organization dedicated to building an open general artificial intelligence (AGI) economy. It is developing a platform and protocol that allows open-source AI developers to monetize their models, data, and other innovations.
Here, developers can collaborate to build powerful AI reminders and become key stakeholders driving AI transformation and prosperity in the new open AGI economy.
In response to the current AI landscape’s lack of incentives and the difficulty of achieving significant progress through individual efforts, Sentient proposes the “OML” (Open, Monetize, Loyalty) model.
This model aims to promote a shared open AGI economy, creating a collaborative and open AGI economic system involving millions of AI agents and billions of users, thereby providing endless momentum for downstream application innovation and development.
Sentient’s strategic advisor Sandeep Nailwal (Polygon co-founder) stated, “Sentient will be built on Polygon AggLayer, rewarding engineers for tasks such as labeling and refining data and other activities related to training AI models. If successful, Sentient could change the course of human-AI relations.” Nailwal is also a core contributor to Sentient.
In addition, Sentient will create a boundless collaboration and discussion platform, ensuring that every participant’s incentives and contributions are fairly recognized. This will promote the collision and integration of innovative ideas while enhancing the transparency and credibility of the entire system.
According to Sandeep Nailwal, the idea for Sentient originated from a conversation between him and EigenLayer founder Sreeram Kannan. They discussed how cryptocurrency could address AI decentralization and security issues and how Polygon could play a role in this structural shift, sowing the seeds of hope for Sentient.
Kannan later shared this concept with Princeton University Professor Pramod Viswanath and Indian Institute of Science Professor Himanshu Tyagi. Coincidentally, this aligned with their ongoing research, which eventually transformed into Sentient.
Sentient’s Core Think Tank and Contributors
According to Sentient’s official statement, the Sentient Foundation is a non-profit organization with a guidance committee that includes Sandeep Nailwal and two engineering professors, along with a venture studio:
- Pramod Viswanath, Forrest G. Hamrick Engineering Professor at Princeton University: Responsible for research guidance.
- Himanshu Tyagi, Engineering Professor at the Indian Institute of Science: Responsible for technical guidance.
- Sandeep Nailwal, Co-founder of Polygon: Responsible for strategic guidance.
- Sensys, a venture studio creating products and applications for Sentient, will handle growth. Sensys is led by Symbolic Capital co-founder Kenzi Wang.
It’s worth noting that Pramod Viswanath, responsible for research guidance, has made significant contributions in the field of wireless communication. During his tenure as a founding engineer at Flarion Technologies in 2020, he helped develop the framework that became the foundation for 4G LTE wireless networks. Viswanath is also the co-author of the textbook Fundamentals of Wireless Communication and a co-founder of the blockchain startup Kaleidoscope.
The research direction of Pramod Viswanath’s lab is closely tied to Sentient’s future blueprint. Ben, who co-taught with Professor Viswanath at Princeton University, mentioned last month that in one course, students built AI applications for blockchain and blockchain applications for AI in groups, with some projects potentially being implemented on the Sentient platform.
Ben also revealed the research directions of Viswanath’s lab, including AI agents for smart contract generation and verification, intelligent blockchain wallets for automatic fraud detection, AI-driven blockchain browsers, on-chain and off-chain models for gas prediction, AI-driven Oracles, Smart DAOs, Data DAOs, and AI-driven low-cost cross-chain path detection.
Sentient’s contributor team is equally impressive, with 11 listed contributors, including four from the University of Washington and four from Princeton University, mostly researchers or professors in AI, blockchain research, and computer science. Additionally, Sandeep Nailwal stated that the Sentient AI team includes veterans from Google, DeepMind, and other leading AI companies.
Roadmap of Sentient
Sentient has outlined a clear roadmap, planning to build the Sentient AI Platform and blockchain protocol in the short to medium term, followed by the development of new foundational models contributed by the community, open AGI supported by the OML model, and economic incentives and monetization for AI builders.
This quarter, Sentient is entering the testnet phase.
Summary
As Dovey Wan, founder of Primitive Ventures, stated, we are witnessing the convergence of “binary code becoming monetary code,” “machine programs becoming social contract programs,” and “human language becoming programming language.”
This convergence heralds the arrival of a new era, embracing the principles of decentralization, transparency, and collective ownership. Franklin Bi, a partner at Pantera Capital, further stated, “Open systems will surpass closed systems, allowing Open AI to defeat OpenAI.”
Sentient’s grand vision of “ensuring AI benefits all of humanity” is not just a competition with existing AI solutions but aims to pave the way for the next generation of AI’s intelligent leap.
Of course, its implementation path and operation method still require detailed refinement, but each attempt is an exploration and practice of future possibilities.
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