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AI: Events
Development
Researchers from Tencent have developed a tool that helps to precisely identify where failures occur during reinforcement learning model training.
AI: Events
Technical context • Infrastructure
We explore how Gang Scheduling technology helps efficiently allocate resources for training AI models and why striking a balance between rigidity and flexibility is crucial.
Lab
Mathematics & Statistics
How mathematical maps lose energy when concentrating at a point and why this creates geometric necks connecting spaces via invisible threads.
The Higress cloud gateway has been updated to support the Gateway API standard and now includes specialized features for working with artificial intelligence models.
AI: Events
Technical context • Development
Two AI agents can create optimized CUDA kernels to speed up operations straight from a task description. Let's dive into what this means for people working with models.
AI: Events
Infrastructure
Chinese company MiniMax has released Forge, an open platform designed for training agents using reinforcement learning on large-scale GPU clusters.
AI: Events
Technical context • Infrastructure
The Qwen team optimized their models to effectively run on AMD MI300X GPUs, achieving a response latency as low as 15 ms per token and full image generation in just 0.4 seconds.
AI: Events
Technical context • Infrastructure
The verl framework for training large language models with reinforcement learning has received support for AMD ROCm 7.0.0 and expanded scaling capabilities.
Chinese company MiniMax has released M2.5, a family of open-weight models whose performance is approaching that of Claude 3.5 Sonnet.
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