- Sogang University’s Language & Data Intelligence Laboratory becomes EdgeCloud’s twentieth academic and enterprise customer.
- The partnership expands Theta’s academic network in South Korea, joining institutions like Seoul National University and KAIST.
- Professor Buru Chang’s laboratory specializes in natural language processing and multimodal machine learning research.
- The collaboration will focus on advancing AI workflows through Theta’s hybrid GPU infrastructure.
- EdgeCloud provides decentralized computing resources for AI research and development initiatives.
Theta Labs’ EdgeCloud platform continues to expand its academic presence in South Korea, announcing Sogang University’s Language & Data Intelligence Laboratory as its latest customer. The laboratory, led by Professor Buru Chang, joins a network of twenty customers across academia and enterprise sectors, strengthening Theta’s position in the AI research infrastructure market.
The partnership marks a significant expansion of Theta’s academic network in South Korea, which includes prestigious institutions like Seoul National University, KAIST, Korea University, and Yonsei University. These institutions utilize EdgeCloud’s hybrid cloud-edge GPU computing platform for advanced AI research and development.
Professor Chang, who holds a Ph.D. in Computer Science from Korea University and previously worked as a machine learning research scientist at Hyperconnect, brings substantial expertise to the collaboration. His laboratory has gained recognition through publications in major AI conferences, including AAAI, CVPR, ECCV, EMNLP, and WSDM.
“We selected the EdgeCloud platform by introduction from my fellow colleagues in academia,” states Professor Chang, noting the platform’s significant market presence in both the United States and South Korea. He particularly emphasized the platform’s ease of use and scalability as key factors in their decision.
The laboratory’s research focuses on natural language processing (NLP), a field of AI that enables computers to understand and process human language, and multimodal machine learning, which combines different types of data inputs like text, images, and audio. Their recent work includes the development of ESREAL, a framework addressing hallucinations in vision-language models.
Through EdgeCloud’s decentralized infrastructure, the laboratory aims to accelerate its research in generative AI, edge computing, and efficient AI workflows. This collaboration represents a growing trend of academic institutions leveraging blockchain-based computing solutions for resource-intensive AI research.
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