From a Curious Outsider to a GreptimeDB Advocator Journey into Contribution
👁️Observability
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Fine-Tuning an AI – Part I
zwischenzugs.com·16h
📱Edge AI
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original ↗
blog.robbowley.net·9h
📱Edge AI
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Demo: Statistically Significant Results On Biases and Errors of LLMs Do Not Guarantee Generalizable Results
arxiv.org·4h
💬NLP
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It Doesn’t Need to Be a Chatbot
towardsdatascience.com·1d
📱Edge AI
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BRAINS: A Retrieval-Augmented System for Alzheimer's Detection and Monitoring
arxiv.org·4h
🧠Neural Architecture
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The Infrastructure of Modern Ran king Systems, Part 2: The Data Layer - Fueling the Models with Feature and Vector Stores
shaped.ai·2d
🗄️Databases
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Sherlock: Reliable and Efficient Agentic Workflow Execution
arxiv.org·1d
👁️Observability
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LangChain vs LangGraph: A Beginner’s Guide to Building Smarter AI Workflows
hackernoon.com·1d
📱Edge AI
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How multi-agent collaboration is redefining real-world problem solving
infoworld.com·14m
🧠AI
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Sable and Able: A Tale of Two ASIs
lesswrong.com·3h
📱Edge AI
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Auditable-choice reframing unlocks RL-based verification for open-ended tasks
arxiv.org·4h
🧠AI
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AI Progress Should Be Measured by Capability-Per-Resource, Not Scale Alone: A Framework for Gradient-Guided Resource Allocation in LLMs
arxiv.org·1d
📱Edge AI
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