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Theta Labs expands AI analysis partnerships as Kangwon Nationwide College joins Theta EdgeCloud’s decentralized GPU community.
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SAN FRANCISCO, CA – March 5, 2025 – Theta Labs, a world chief in decentralized cloud infrastructure for AI, media, and leisure, declares its newest educational buyer, Kangwon Nationwide College Information Analytics & Machine Intelligence (DAMI) Lab, led by Professor Kyeongpil Kang.
Bringing on board Kangwon Nationwide College as Theta EdgeCloud’s twenty third AI and video buyer marks a big milestone, collectively attaining over 85% GPU utilization charge throughout its worldwide community and over 230 million TFUEL locked by Elite Booster node operators.
Theta EdgeCloud is proud to energy a variety of main enterprises comparable to NHL’s Las Vegas Knights and world esports groups, together with FlyQuest and Evil Geniuses, and top-tier educational establishments, Seoul Nationwide College, KAIST, College of Oregon, Michigan State College, and Singapore’s famend analysis establishment NTU, increasing its function in advancing AI analysis and real-world purposes.
About Professor Kyeongpil Kang and DAMI Lab
Professor Kyeongpil Kang is an Assistant Professor within the Division of Laptop Science and Engineering at Kangwon Nationwide College, specializing in pure language processing (NLP), machine studying, and information mining. He earned his Ph.D. in Laptop Science from Korea College, the place he studied underneath Professor Jaegul Choo, and later labored as a machine studying researcher at SK Telecom AI Heart, Scatter Lab, and Liner earlier than becoming a member of academia.
The Information Analytics & Machine Intelligence (DAMI) Lab at Kangwon Nationwide College focuses on large-scale AI analysis, with experience in pure language processing, multimodal AI, and data extraction.
The lab focuses on:
- Pure Language Processing and Massive Language Fashions (LLMs): Researching LLM fine-tuning, Chain of Thought (CoT), Retrieval-Augmented Technology (RAG), and AI Alignment. DAMI Lab additionally explores LLM Agent efficiency optimization and simulation-based studying.
- Machine Studying and Deep Studying: Addressing domain-specific AI challenges by setting up coaching datasets and creating deep studying options for real-world purposes.
- Information Mining and AI-Pushed Insights: Making use of machine studying and LLM-powered analytics to fields comparable to social sciences and medical AI, uncovering insights to sort out complicated issues.
Advancing AI analysis with Theta EdgeCloud
DAMI Lab will leverage Theta EdgeCloud, the primary hybrid cloud-edge GPU computing platform, to drive innovation in pure language processing (NLP), machine studying, and information mining. By way of this collaboration, DAMI Lab researchers can even achieve entry to Theta’s decentralized GPU infrastructure, offering cost-effective, scalable AI computing energy to advance LLM coaching, multi-agent AI methods, and multimodal studying purposes.
- Improve NLP and LLM fashions: Practice superior language fashions with scalable, high-performance GPU computing.
- Develop sturdy multi-agent AI methods: Experiment with multi-agent debate fashions and adversarial AI.
- Energy AI on the edge: Deploy AI fashions in real-time environments utilizing Theta’s hybrid cloud-edge structure.
- Optimize AI coaching effectivity: Leverage Theta’s distributed computing framework to run cost-efficient, large-scale AI experiments.
Addressing these developments, Professor Kyeongpil Kang states, “We’ve been evaluating EdgeCloud for a variety of weeks already, and we’re deeply impressed by its flexibility and scalability. This may serve us effectively as our college students, researchers and employees proceed to develop over the subsequent few years. We’re excited to leverage EdgeCloud’s distributed GPU structure and see how DAMI Lab can speed up NLP and multimodal AI analysis whereas optimizing mannequin efficiency for real-world purposes.”
Mitch Liu, co-founder and CEO of Theta Labs provides, “Bringing Kangwon Nationwide College onboard as our twenty third buyer is thrilling but in addition provides to our progress challenges. By pushing over 85% utilization charge throughout our GPU community, we have to always increase our GPU infrastructure whereas maximizing value effectiveness. Our aim in 2025 is to 10x our buyer base, drive over 95% utilization charge and lock over 2 billion TFUEL by means of our elite edge node operators.”
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