AI data is centralized and expensive — Perceptron built the decentralized mesh that cuts costs by 92%. Peter Anthony, Co-Founder
About this episode
Peter Anthony discusses how Perceptron is revolutionizing AI training data with a decentralized mesh that significantly reduces costs.
Most AI training data flows through centralized providers like Scale AI and Appen — expensive, slow, and controlled by a handful of platforms. DECENTRALIZED DATA INFRASTRUCTURE is what Perceptron is building, and it's already serving 700,000+ nodes and generating real revenue.n Peter Anthony, Co-Founder of Perceptron Network, breaks down how a mesh of user-run nodes delivers AI training data at 92% lower cost than legacy providers, why the Data Questing Platform is the next frontier for distributed micro-tasking, and how the $10M AI Data Fund is accelerating teams with free data access. Perceptron has 700K+ nodes, 300K daily active users, and live client contracts — and they're about to launch the infrastructure that turns the community into the AI economy's labeling backbone. The decentralized data mesh works because you cut out the middleman; the Data Questing Platform does distributed precision labeling with incentive alignment that Scale AI and Mechanical Turk can't; and the $10M AI Data Fund matters because teams get access with no pre-funding, reshaping how AI training data is sourced. 🔗 https://perceptrons.xyzn 🐦 https://twitter.com/PerceptronLabsn 🔔JOIN OUR FREE…
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