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GLM-5
In this episode:
• Welcome & The End of Vibe Coding?: Linda introduces GLM-5 and the paradigm shift from passive vibe coding to autonomous agentic engineering.
• Architecture & DeepSeek Sparse Attention: Professor Norris and Linda examine the 744B parameter model and how transitioning from dense to sparse attention drastically cuts compute costs.
• Asynchronous RL and the Slime Framework: A deep dive into decoupled training engines, addressing off-policy drift with TITO and token-level clipping.
• Evaluating Real-World Agentic Engineering: Reviewing GLM-5's performance on SWE-bench and the innovative Agent-as-a-Judge pipeline for interactive frontend testing.
• Hardware Adaptation & Pony Alpha: Discussing the model's extreme quantization for domestic GPUs and the dramatic anonymous release on OpenRouter.
• Welcome & The End of Vibe Coding?: Linda introduces GLM-5 and the paradigm shift from passive vibe coding to autonomous agentic engineering.
• Architecture & DeepSeek Sparse Attention: Professor Norris and Linda examine the 744B parameter model and how transitioning from dense to sparse attention drastically cuts compute costs.
• Asynchronous RL and the Slime Framework: A deep dive into decoupled training engines, addressing off-policy drift with TITO and token-level clipping.
• Evaluating Real-World Agentic Engineering: Reviewing GLM-5's performance on SWE-bench and the innovative Agent-as-a-Judge pipeline for interactive frontend testing.
• Hardware Adaptation & Pony Alpha: Discussing the model's extreme quantization for domestic GPUs and the dramatic anonymous release on OpenRouter.
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By Mechanical DirkIn this episode:
• Welcome & The End of Vibe Coding?: Linda introduces GLM-5 and the paradigm shift from passive vibe coding to autonomous agentic engineering.
• Architecture & DeepSeek Sparse Attention: Professor Norris and Linda examine the 744B parameter model and how transitioning from dense to sparse attention drastically cuts compute costs.
• Asynchronous RL and the Slime Framework: A deep dive into decoupled training engines, addressing off-policy drift with TITO and token-level clipping.
• Evaluating Real-World Agentic Engineering: Reviewing GLM-5's performance on SWE-bench and the innovative Agent-as-a-Judge pipeline for interactive frontend testing.
• Hardware Adaptation & Pony Alpha: Discussing the model's extreme quantization for domestic GPUs and the dramatic anonymous release on OpenRouter.
• Welcome & The End of Vibe Coding?: Linda introduces GLM-5 and the paradigm shift from passive vibe coding to autonomous agentic engineering.
• Architecture & DeepSeek Sparse Attention: Professor Norris and Linda examine the 744B parameter model and how transitioning from dense to sparse attention drastically cuts compute costs.
• Asynchronous RL and the Slime Framework: A deep dive into decoupled training engines, addressing off-policy drift with TITO and token-level clipping.
• Evaluating Real-World Agentic Engineering: Reviewing GLM-5's performance on SWE-bench and the innovative Agent-as-a-Judge pipeline for interactive frontend testing.
• Hardware Adaptation & Pony Alpha: Discussing the model's extreme quantization for domestic GPUs and the dramatic anonymous release on OpenRouter.