Optimizing filtered vector queries from tens of seconds to single-digit milliseconds in PostgreSQL
clarvo.ai·7h
🔍Query Optimization
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An introduction to program synthesis (Part II) - Automatically generating features for machine learning
🎭Program Synthesis
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Dense vs Sparse vs Multi-Vector Embeddings Explained: What Every AI Engineer Should Know
pub.towardsai.net·1d
🧮Embeddings
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Topographical sparse mapping: A training framework for deep learning models
👁️Computer Vision
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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
📈Time-Series Databases
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BoolSkel: Unlocking Boolean Network Efficiency Through Structural Pruning by Arvind Sundararajan
⏭️Skip Lists
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Explore More, Learn Better: Parallel MLLM Embeddings under Mutual Information Minimization
arxiv.org·1d
🧮Embeddings
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Feature Stores 2.0: The Next Frontier of Scalable Data Engineering for AI
hackernoon.com·11h
🎨Design Systems
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Hypergraph Embedding Optimization for Graph Database Query Acceleration via Differential Evolution
🕸️Graph Databases
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Inside Pinecone: Slab Architecture
📋Columnar Storage
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Thoughts on "Static Retrival Revisited"
curiouscoding.nl·1d
#️⃣Hash Tables
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Semantic search with embeddings in PHP: a hands-on guide using Neuron AI and Ollama
🧮Embeddings
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[P] triplet-extract: GPU-accelerated triplet extraction via Stanford OpenIE in pure Python
📝NLP
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Optimizing filtered vector queries from tens of seconds to single-digit milliseconds in PostgreSQL
🗄️Database Internals
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Relation-Aware Bayesian Optimization of DBMS Configurations Guided by Affinity Scores
arxiv.org·2d
🗄️Database Internals
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Real-time stock volatility prediction with deep learning on a time-series DB
💰TigerBeetle
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Geonum – geometric number library for unlimited dimensions with O(1) complexity
📏Linear Types
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The Case Against PGVector
🗄️Database Internals
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