Theta and AWS Boost AI Research with Yonsei’s Trainium Adoption
The post Theta and AWS Boost AI Research with Yonsei’s Trainium Adoption appeared on BitcoinEthereumNews.com. Theta Network and AWS recently joined forces to launch custom Amazon AI chips Trainium & Inferentia on the EdgeCloud platform. We’re proud to share that one of Korea’s most prestigious institutions, Yonsei University’s Data & Language Intelligence Lab, led by Professor Dongha Lee, will be utilizing the Theta-AWS Trainium infrastructure for a major AI agent project. This marks a significant milestone as Theta Network welcomes Yonsei University as a marquee institution-level user of Trainium-powered instances, reflecting our commitment to offering diverse GPU and next-gen AI chip resources tailored to customer needs. This follows AWS’ approval of Theta EdgeCloud hybrid as the first decentralized AI platform to integrate its cutting-edge AI silicon. Theta is the first blockchain network to deploy Amazon’s next-generation chipsets and deliver unmatched performance for AI, video, and media workloads. Yonsei’s Research with AWS Trainium and Theta EdgeCloud Hybrid Yonsei plans to use AWS Trainium Trn1 instances for high-performance deep learning training, utilizing AI-simulated users and automated evaluation models to develop a scalable, reproducible framework for conversational recommendation agents. The system will refine chatbot models through Direct Preference Optimization (DPO), using pairwise preference signals from simulated conversations without the need for manual labeling. Running on AWS Trainium via the Neuron Kernel Interface (NKI) deployed on Theta EdgeCloud Hybrid, this framework can simulate millions of realistic user interactions per day, evaluate and improve models instantly within a hardware-optimized loop, and ensure deterministic, reproducible training at scale. This vastly accelerates AI R&D cycles in academia. Beyond recommendation systems, it can be extended to support customer service bots, task planners, tutoring systems, and other goal-oriented conversational AI agents, amplifying its potential across industries. This collaboration is significant as: First decentralized platform approved by AWS to integrate its custom AI silicon Trainium and Inferentia. First blockchain network to deploy Amazon’s next-generation AI…
The post Theta and AWS Boost AI Research with Yonsei’s Trainium Adoption appeared on BitcoinEthereumNews.com.
Theta Network and AWS recently joined forces to launch custom Amazon AI chips Trainium & Inferentia on the EdgeCloud platform. We’re proud to share that one of Korea’s most prestigious institutions, Yonsei University’s Data & Language Intelligence Lab, led by Professor Dongha Lee, will be utilizing the Theta-AWS Trainium infrastructure for a major AI agent project. This marks a significant milestone as Theta Network welcomes Yonsei University as a marquee institution-level user of Trainium-powered instances, reflecting our commitment to offering diverse GPU and next-gen AI chip resources tailored to customer needs. This follows AWS’ approval of Theta EdgeCloud hybrid as the first decentralized AI platform to integrate its cutting-edge AI silicon. Theta is the first blockchain network to deploy Amazon’s next-generation chipsets and deliver unmatched performance for AI, video, and media workloads. Yonsei’s Research with AWS Trainium and Theta EdgeCloud Hybrid Yonsei plans to use AWS Trainium Trn1 instances for high-performance deep learning training, utilizing AI-simulated users and automated evaluation models to develop a scalable, reproducible framework for conversational recommendation agents. The system will refine chatbot models through Direct Preference Optimization (DPO), using pairwise preference signals from simulated conversations without the need for manual labeling. Running on AWS Trainium via the Neuron Kernel Interface (NKI) deployed on Theta EdgeCloud Hybrid, this framework can simulate millions of realistic user interactions per day, evaluate and improve models instantly within a hardware-optimized loop, and ensure deterministic, reproducible training at scale. This vastly accelerates AI R&D cycles in academia. Beyond recommendation systems, it can be extended to support customer service bots, task planners, tutoring systems, and other goal-oriented conversational AI agents, amplifying its potential across industries. This collaboration is significant as: First decentralized platform approved by AWS to integrate its custom AI silicon Trainium and Inferentia. First blockchain network to deploy Amazon’s next-generation AI…
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