POKT Network has recently unveiled its AI Litepaper, which delves into the utilization of Large Language Models (LLMs) on its platform to deliver reliable and scalable AI inference services. Since its launch on Mainnet in 2020, POKT Network has processed over 750 billion requests across a network of around 15,000 nodes spanning 22 countries. This extensive infrastructure puts POKT Network in a prime position to improve the accessibility and commercialization of AI models within its ecosystem.
The AI Litepaper emphasizes the alignment of interests among model researchers (Sources), hardware operators (Suppliers), API providers (Gateways), and users (Applications) through the innovative Relay Mining algorithm. This algorithm establishes a transparent marketplace where costs and earnings are determined by verified usage through cryptography. The protocol’s quality of service competes with centralized entities, solidifying its status as a sophisticated permissionless network for top-tier inference applications.
Unveiling: POKT Network’s AI Litepaper
The document investigates the feasibility of deploying Large Language Models on the platform to deliver robust and scalable AI inference services.
Read more here
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— POKT Network (@POKTnetwork)
June 19, 2024
The incorporation of LLMs on POKT Network enables seamless AI inference services without interruptions, leveraging the existing decentralized structure. AI researchers and scholars can monetize their models by deploying them on the network, earning revenue based on usage without the hassle of managing access infrastructure or creating demand. The Relay Mining algorithm ensures a fair marketplace, motivating Suppliers to uphold a high level of Service Quality.
Permissionless LLM Inference
The AI Litepaper, titled “Decentralized AI: Permissionless LLM Inference on POKT Network,” was crafted by Daniel Olshansky, Ramiro Rodríguez Colmeiro, and Bowen Li. Their diverse expertise spans augmented reality, autonomous vehicle interaction analysis, medical image analysis, and AI/ML infrastructure development, enriching the paper with comprehensive insights.
Daniel Olshansky brings experience from Magic Leap’s Augmented Reality cloud and Waymo’s autonomous vehicle planning. Ramiro Rodríguez Colmeiro, a PhD in signal analysis and system optimization, specializes in machine learning and medical image analysis. Bowen Li, formerly an engineering manager at Apple AI/ML, spearheaded the development of Apple’s initial LLM inferencing platform.
POKT Network’s AI Litepaper underscores its potential to propel innovation, adoption, and commercialization of open-source models, establishing the network as a significant player in permissionless LLM inference. For a more in-depth exploration, the complete AI Litepaper is accessible online.
Tags: AI
