Yonsei University Advances AI Research with AWS Trainium on Theta EdgeCloud
Friday, August 8, 2025 12:00 AM
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Yonsei University has embarked on a groundbreaking initiative by integrating AWS Trainium with Theta EdgeCloud to enhance its AI agent research. This collaboration signifies a pivotal moment as Theta Network becomes the first blockchain to deploy Amazon’s advanced AI chips. The Data & Language Intelligence Lab, led by Professor Dongha Lee, aims to scale AI research while optimizing performance and reducing costs. The use of AWS Trainium allows the lab to leverage a decentralized infrastructure for high-performance deep learning, providing specialized hardware that enables training AI models at significantly lower costs, thus enhancing efficiency and reproducibility in large-scale experiments.
The innovative research at Yonsei focuses on developing conversational recommendation agents that simulate human-like interactions. Instead of traditional human evaluators, the lab employs AI-simulated users with distinct memory and personality traits to assess models in real-time. This approach utilizes Direct Preference Optimization (DPO) for model training, which allows agents to refine their responses without manual labeling. Consequently, the research team can simulate millions of user interactions daily, expediting the evaluation and improvement of their AI models, leading to faster iterations and increased accuracy.
The partnership between Theta Network and AWS not only provides a cost-effective solution for AI research but also enhances scalability. With AWS Trainium instances designed specifically for deep learning tasks, institutions like Yonsei can experiment with large models and extensive datasets without incurring significant financial burdens. The integration of Trainium with Theta EdgeCloud’s extensive network of over 30,000 NVIDIA GPUs offers researchers the flexibility to select optimal computing resources for their workloads. This collaboration marks a new era in AI research, showcasing how decentralized infrastructure and advanced AI hardware can revolutionize academic research and development in the field of artificial intelligence.
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