Tag: training tasks
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Hacker News: MIT researchers develop an efficient way to train more reliable AI agents
Source URL: https://news.mit.edu/2024/mit-researchers-develop-efficiency-training-more-reliable-ai-agents-1122 Source: Hacker News Title: MIT researchers develop an efficient way to train more reliable AI agents Feedly Summary: Comments AI Summary and Description: Yes **Summary:** The text discusses an innovative approach developed by MIT researchers to improve the efficiency of reinforcement learning models for decision-making tasks, particularly in traffic signal control. The…
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The Register: Nvidia’s MLPerf submission shows B200 offers up to 2.2x training performance of H100
Source URL: https://www.theregister.com/2024/11/13/nvidia_b200_performance/ Source: The Register Title: Nvidia’s MLPerf submission shows B200 offers up to 2.2x training performance of H100 Feedly Summary: Is Huang leaving even more juice on the table by opting for mid-tier Blackwell part? Signs point to yes Analysis Nvidia offered the first look at how its upcoming Blackwell accelerators stack up…
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Cloud Blog: 65,000 nodes and counting: Google Kubernetes Engine is ready for trillion-parameter AI models
Source URL: https://cloud.google.com/blog/products/containers-kubernetes/gke-65k-nodes-and-counting/ Source: Cloud Blog Title: 65,000 nodes and counting: Google Kubernetes Engine is ready for trillion-parameter AI models Feedly Summary: As generative AI evolves, we’re beginning to see the transformative potential it is having across industries and our lives. And as large language models (LLMs) increase in size — current models are reaching…
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Hacker News: WebRL: Training LLM Web Agents via Self-Evolving Online Reinforcement Learning
Source URL: https://arxiv.org/abs/2411.02337 Source: Hacker News Title: WebRL: Training LLM Web Agents via Self-Evolving Online Reinforcement Learning Feedly Summary: Comments AI Summary and Description: Yes Summary: The paper introduces WebRL, a novel framework that employs self-evolving online curriculum reinforcement learning to enhance the training of large language models (LLMs) as web agents. This development is…