Compiled by: Scof, ChainCatcher
Editor: Nianqing, ChainCatcher
Today, the centralized open source AI platform OpenGradient announced the completion of a $8.5 million seed round of financing. a16z Crypto Startup Accelerator, Foresight Ventures, SV Angel, Coinbase Ventures, SALT Fund and Symbolic Capital participated in the investment. Angel investors Balaji Srinivasan, NEAR founder Illia Polosukhin and Polygon founder Sandeep Nailwal and other well-known industry figures also participated as angel investors.
The funds will be used to continue building decentralized infrastructure, deploying solutions and tools for AI and Web3 developers, and advancing applied ML research to grow the open source AI ecosystem on blockchain. OpenGradient's testnet is expected to be open to developers in the fourth quarter of 2024.
In early September, OpenGradient was also selected for the a16z Crypto Fall Crypto Startup Accelerator (CSX) program. a16z CSX will invest at least $500,000 in each selected company, and the program will be trained for 8 weeks in New York City, gain first-hand experience with top crypto founders, receive guidance and support from the a16z crypto investment and operations team, and connect with other companies and the broader a16z network.
According to the official website, OpenGradient is the first decentralized platform for open source AI model hosting, secure execution, proxy reasoning, and application deployment. OpenGradient's new heterogeneous AI computing architecture (HACA) enables permissionless AI reasoning, statistical analysis, data processing, and proxy execution to run securely and scalably end-to-end through smart contracts, while building a web platform designed to accelerate AI research. OpenGradient enables developers to seamlessly leverage open source models and use computing to implement risk management, ML optimization, AI agents, anti-sybil, defi mechanism design and other functions.
The following introduction is compiled from the OpenGradient official blog, with some deletions and additions:
The integration of artificial intelligence and blockchain
Artificial intelligence has become an integral part of our daily lives: from driving smartphone assistants and recommendation algorithms to conversational robo-advisors that advise on stock recommendations, AI has impacted nearly every aspect of modern society. However, the current state of AI is not only centralized and controlled by a few tech giants who can arbitrarily restrict access to AI models, but its computational processes lack sufficient assurance and security to be suitable for applications that require a high degree of verifiability, such as blockchain applications. As a result, while AI has become ubiquitous in augmenting traditional applications, Web3 protocols lag behind Web2 in terms of complexity, optimization, and user experience.
The main obstacles to integrating AI into Web3:
Blockchain is limited by virtual machine limitations and computing power
Off-chain reasoning is trustworthy but vulnerable to attack
The hardware requirements and computational costs of hosting and serving AI models are high
Requires custom infrastructure to be built for trust-minimized reasoning (via zkML, trusted execution environments, etc.), which is complex
Lack of research exploring the design space of AI-driven Web3 applications
The emergence of OpenGradient
OpenGradient is a solution that combines blockchain and artificial intelligence to solve their respective problems. OpenGradient is the first permissionless platform for open source model hosting, secure reasoning, proxy reasoning, and application deployment. By developing AI tools, feature-rich libraries, and an innovative decentralized platform based on blockchain, OpenGradient not only makes the integration of AI workflows into Web3 applications secure and seamless, but also decentralizes and popularizes access to AI models.
OpenGradient is building an EVM-compatible blockchain network designed to be a scalable and secure execution layer for AI. The network takes a revolutionary approach to reshaping blockchain architecture, allowing developers to infer AI models directly from their Solidity smart contracts with simple function calls.
Because the OpenGradient Network provides access to inference AI models directly through pre-compilation in smart contracts, it is able to maximize the composability of smart contracts.
Core products and programs include:
Web3 AI Research - OpenGradient's research team is driving innovation in open source AI in crypto by building models for DeFi risk analysis, AMM dynamic fee optimization, DePIN reputation, and more.
Model Hub - OpenGradient’s Model Hub is the Web3 version of HuggingFace: an easy-to-use web portal where any developer can upload, download, or access any AI model in our decentralized and censorship-resistant file storage.
OG SDK - The OG Python SDK provides seamless access to OpenGradient functionality, including model access, secure reasoning, proof/certification retrieval, and more.
NeuroML - NeuroML allows developers to leverage models for ML optimization, systemic risk management, AI agents, Sybil defense, DeFi mechanism design, and more, built seamlessly into our AI application ecosystem.
HACA Infrastructure - OpenGradient’s proprietary Hybrid AI Computing Architecture (HACA) scales and protects on-chain AI workflows through node specialization, providing capabilities such as inference, proxy reasoning, statistical analysis, and more.
Team Information
OpenGradient is headquartered in New York City, and its team is composed of global talents with deep expertise in AI/ML, blockchain, cryptocurrency, and Web3 ecosystem. Team members come from technology companies such as Google, Coinbase, Ripple, Intel, Palantir, etc.
Co-founder and CEO Matthew Wang holds a bachelor’s degree in computer engineering from Northwestern University and is a research engineer at Two Sigma with experience in quantitative modeling and machine learning research.
Co-founder and CTO Adam Balogh was previously the head of the AI platform at Palantir Technologies and has seven years of experience in the industry. He holds a master's degree in advanced computing from Imperial College London.
