NeurochainAI launches new platform for building AI dApps

NeurochainAI has introduced a new platform to make AI development more accessible worldwide. 

This platform aims to simplify the process of creating, releasing, and utilizing AI-powered decentralized applications (dApps) by combining machine learning with blockchain technology. NeurochainAI hopes that this integration will improve the scalability, transparency, and data security in AI applications.

NeurochainAI’s platform has 82,000 registered users and 48,000 connected wallets. It is designed to foster community participation in AI model creation and validation. Their community-driven approach ensures the accuracy of AI models and enhances their performance, offering a unique advantage in the competitive AI market. 

“Our platform brings the world a step closer to inclusive, democratic AI development,” said Julius Serenas, CEO of NeurochainAI. “We empower developers with a number of tools and resources from our decentralized AI infrastructure that places Consumer-grade GPU DePIN at the center of our operations to provide ever more precious GPU compute in the age of AI paired with other tools essential for streamlining AI solution development.”

The platform reduces the time-to-market for AI dApps by up to 24 times compared to traditional methods.

Global AI

The global AI market is valued at $500 billion and is projected to reach $1.8 trillion by 2030. This growth is primarily driven by technological advancements and significant sector investments. 

NeurochainAI builds off this growth by offering AI infrastructure, including the first decentralized consumer-grade GPU DePIN for AI computing, community-powered data collection and validation. They also optimize AI model marketplaces and interoperability tools for integration for any tech stack across Web2 and Web3.

NeurochainAI employs a layered approach to provide decentralized AI-as-a-Service (DAIAS), which reduces barriers to entry and empowers developers to create and launch AI applications with greater efficiency.