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MiniMax Sparse Attention (MSA): a Two-Branch Block-Sparse Attention Trained on a 109B-Parameter MoE With a 3T-Token Budget
MiniMax released MSA (MiniMax Sparse Attention), a sparse attention method built directly on Grouped Query Attention (GQA). It targets one bottleneck: the quadratic cost of…
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LLM Fallbacks Break Agent Pipelines — I Built the Missing Recovery Layer
TL;DR don’t just pause your agents. They ruin your data structure if…
Meet Qwen-RobotSuite: Three Embodied AI Models for VLA Manipulation, Video World Modeling, and Navigation
The Qwen team has released three embodied AI models, grouped as Qwen-Robot-Suite.…
Drilling Into AI’s Financial Sustainability
In my April column, I talked about of the true cost of AI…
How to Build a Parsing Pipeline with Docling Parse for Layout-Aware Document Intelligence
def create_demo_image(path): img = Image.new("RGB", (320, 180), "white") draw = ImageDraw.Draw(img) draw.rectangle(,…
Run a Local LLM with OpenClaw on Your Mac Mini
You bought the Mac Mini for Openclaw. Perfect. late, Anthropic has pushed…
Meet Atoms: A Vibe Coding Tool That Uses AI Agents to Build, Deploy, and Market Your App (No Code)
The concept of vibe coding is interesting; you don’t need to be…
RAG Questions Need Parsing Too: Turn the User’s String Into Briefs for Retrieval and Generation
Tquestion-parsing brick of Enterprise Document Intelligence, a series that builds an enterprise…
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