Amazon S3 Vectors: When Storage Learns to Think
dev.to·2h·
Discuss: DEV
🗂️Vector Search
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A Minimal Route to Transformer Attention
neelsomaniblog.com·1d·
Discuss: Hacker News
🧮Vector Embeddings
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TOPol: Capturing and Explaining Multidimensional Semantic Polarity Fields and Vectors
arxiv.org·1d
🧮Vector Embeddings
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The Structure of Data
theprogrammersparadox.blogspot.com·50m·
Discuss: theprogrammersparadox.blogspot.com
🗂Data structures
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3 Minutes to Start Your Research in Nearest Neighbor Search
romanbikbulatov.bearblog.dev·2d·
Discuss: Hacker News
📏Range Queries
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The Machine Learning Projects Employers Want to See
towardsdatascience.com·6h
🎵Audio ML
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Scalable Knowledge Graph Embedding via Adaptive Dimensionality Reduction & Multi-Objective Optimization
dev.to·10h·
Discuss: DEV
🕸️Graph Embeddings
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New Dataset PerSense-D Enables Model-Agnostic Dense Object Segmentation
hackernoon.com·3d
📊Learned Metrics
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Scaling Embeddings with Feast and KubeRay
feast.dev·1d·
Discuss: Hacker News
📡Feed Archaeology
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Best Open Source Observability Solutions
clickhouse.com·1h·
Discuss: Hacker News
📊Homelab Monitoring
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Amazon Nova Multimodal Embeddings: State-of-the-art embedding model for agentic RAG and semantic search
aws.amazon.com·3d·
Discuss: Hacker News
🧮Vector Embeddings
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Scaling Image Geo-Localization to Continent Level
arxiv.org·16h
🕳️Persistent Homology
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Keyword vs. semantic search with AI
dev.to·2d·
Discuss: DEV
🗂️Vector Search
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Vectorizing for Fun and Performance
ibm.com·2d·
Discuss: Hacker News
⚡SIMD Vectorization
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Everything About Transformers
krupadave.com·1d
📝Text Parsing
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Show HN: Vision-Based, Vectorless RAG for Long Douments
github.com·3h·
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🤖Advanced OCR
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Your Transformer is Secretly an EOT Solver
elonlit.com·15h·
Discuss: Hacker News
🧮Kolmogorov Complexity
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Developing a Multi-task Ensemble Geometric Deep Network for Supply Chain Sustainability and Risk Management
arxiv.org·16h
🌀Riemannian Computing
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[P] I made a tool to search papers from selected AI venues
reddit.com·1d·
Discuss: r/MachineLearning
🌀Brotli Internals
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Neural active manifolds: nonlinear dimensionality reduction for uncertainty quantification
arxiv.org·16h
🌀Riemannian Computing
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