📢 Gate广场专属 #WXTM创作大赛# 正式开启!
聚焦 CandyDrop 第59期 —— MinoTari (WXTM),总奖池 70,000 枚 WXTM 等你赢!
🎯 关于 MinoTari (WXTM)
Tari 是一个以数字资产为核心的区块链协议,由 Rust 构建,致力于为创作者提供设计全新数字体验的平台。
通过 Tari,数字稀缺资产(如收藏品、游戏资产等)将成为创作者拓展商业价值的新方式。
🎨 活动时间:
2025年8月7日 17:00 - 8月12日 24:00(UTC+8)
📌 参与方式:
在 Gate广场发布与 WXTM 或相关活动(充值 / 交易 / CandyDrop)相关的原创内容
内容不少于 100 字,形式不限(观点分析、教程分享、图文创意等)
添加标签: #WXTM创作大赛# 和 #WXTM#
附本人活动截图(如充值记录、交易页面或 CandyDrop 报名图)
🏆 奖励设置(共计 70,000 枚 WXTM):
一等奖(1名):20,000 枚 WXTM
二等奖(3名):10,000 枚 WXTM
三等奖(10名):2,000 枚 WXTM
📋 评选标准:
内容质量(主题相关、逻辑清晰、有深度)
用户互动热度(点赞、评论)
附带参与截图者优先
📄 活动说明:
内容必须原创,禁止抄袭和小号刷量行为
获奖用户需完成 Gate广场实名
Theta and AWS Boost AI Research with Yonsei's Trainium Adoption
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.
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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:
By bringing AWS Trainium’s high-performance, cost-efficient capabilities together with Theta EdgeCloud’s globally distributed network of over 30,000 NVIDIA GPUs, researchers now gain unprecedented flexibility to choose the right compute for the right workload – whether training billion-parameter language models, running large-scale inference, or powering next-generation generative AI applications.
What People are Saying
Over the past year, under Professor Lee’s leadership, the lab has achieved remarkable recognition in the global AI community, further strengthened by their extensive use of Theta EdgeCloud Hybrid to power and scale their research
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