Vector Embeddings Hit Mathematical Limits: Google DeepMind Report
pub.towardsai.net·22h
⚡Low-latency
ML Systems: Motivating Dense Models
jacobkahn.me·16h·
Discuss: Hacker News
⚡Low-latency
Integrated Multivariate Segmentation Tree for the Analysis of Heterogeneous Credit Data in Small and Medium-Sized Enterprises
arxiv.org·1d
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How big are our embeddings now and why?
newsletter.vickiboykis.com·17h·
Discuss: Lobsters, Hacker News
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Hyper-Efficient Approximate Nearest Neighbor Search via Quantized Graph Embeddings
dev.to·1d·
Discuss: DEV
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K-means is an essential algorithm for Data Science.
threadreaderapp.com·3h
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Improving Performance of Vector Indexes Via VECTOR Columns
dolthub.com·1d
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The maths you need to start understanding LLMs
gilesthomas.com·1d·
Discuss: Hacker News
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Structure Transfer: an Inference-Based Calculus for the Transformation of Representations
arxiv.org·10h
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NeurStore: Efficient In-database Deep Learning Model Management System
arxiv.org·10h
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What Every Data Scientist Should Know About Graph Transformers
unite.ai·1d·
Discuss: Hacker News
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🔥Embeddings: The Hidden Power Behind AI & Search
dev.to·1d·
Discuss: DEV
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Diverse Unionable Tuple Search: Novelty-Driven Discovery in Data Lakes [Technical Report]
arxiv.org·1d
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Unveiling Hidden Geometry: How Problem Shape Impacts AI Solver Performance by Arvind Sundararajan
dev.to·20h·
Discuss: DEV
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Guide to Visual Data Mining using Parallel Coordinates
analyticsvidhya.com·4h
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A Continuous Encoding-Based Representation for Efficient Multi-Fidelity Multi-Objective Neural Architecture Search
arxiv.org·1d
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Google's RankEmbed system forced to share secrets in antitrust remedy
ppc.land·8h·
Discuss: r/ppcland
💱HFT
How a 20-Year-Old Algorithm Can Help Us Understand Transformer Embeddings
ai.stanford.edu·3d·
Discuss: r/LLM
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Cluster and then Embed: A Modular Approach for Visualization
arxiv.org·10h
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Structured Basis Function Networks: Loss-Centric Multi-Hypothesis Ensembles with Controllable Diversity
arxiv.org·10h
⚡Low-latency