AGRAG: Advanced Graph-based Retrieval-Augmented Generation for LLMs
arxiv.org·13h
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LLM Concepts (Explained Without Making Your Brain Hurt): What Every Developer Should Know
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From Zero to LLMOps Hero: Your 101 Guide to Running LLMs in Production
analyticsvidhya.com·1d
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[D] Choosing a thesis topic in ML
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TAI #178: Kimi K2 Thinking Steals the Open-Source Crown With a New Agentic Contender
pub.towardsai.net·3h
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DiagnoLLM: A Hybrid Bayesian Neural Language Framework for Interpretable Disease Diagnosis
arxiv.org·13h
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The Three Ages of Data Science: When to Use Traditional Machine Learning, Deep Learning, or an LLM (Explained with One Example)
towardsdatascience.com·3h
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Andrej Karpathy on LLM cognitive deficits
lesswrong.com·21h
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Running high-scale reinforcement learning (RL) for LLMs on GKE
cloud.google.com·1d
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Non-Negative Stiefel Approximating Flow: Orthogonalish Matrix Optimization for Interpretable Embeddings
arxiv.org·13h
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Unlocking the future of the Automotive Industry (Part 2): Implementing Scalable Geospatial Analytics & AI
databricks.com·1h
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Building powerful RAG pipelines with Docling and OpenSearch
opensearch.org·12h
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Deep Learning for Molecules and Materials
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Training GPT in Sheets
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Deploying ML Models to Production: AWS Lambda vs ECS vs EKS - A Data-Driven Comparison
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MoM – Mixture of Model Service
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Synth: The New Data Frontier
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