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๐ŸŒณ B-tree Optimization

Database Indexing, Node Splitting, Cache Efficiency, Storage Layout

DeltaCompare 17.0.0 Release: Introducing Multithreading
deltaxignia.comยท2d
โ–ณDelta Compression
The Planet Is Warming, But Our Speech Has Chilled
battellemedia.comยท1d
๐ŸŒก๏ธPreservation Physics
Show HN: A Virtual friend that checks up on you, every morning
jurnai.siteยท2hยท
Discuss: Hacker News
๐Ÿ“กRSS Readers
Applications That Work with Motif/Lesstif (2005)
lesstif.sourceforge.netยท10hยท
Discuss: Hacker News
๐Ÿ“ŸTerminal Typography
We Replaced ETL with MCP
rashidazarang.comยท2dยท
Discuss: Hacker News
๐Ÿ”ŒInterface Evolution
The /o in Ruby regex stands for โ€œoh the humanity!โ€
jpcamara.comยท8hยท
Discuss: Lobsters, Hacker News
๐ŸงชBinary Fuzzing
Show HN: We Built a Serverless GPU Platform with Fast Cold Starts
dat1.coยท2dยท
Discuss: Hacker News
๐Ÿ–ฅ๏ธTerminal Renaissance
[P] FOMO(Faster Objects, More Objects)
reddit.comยท3dยท
Discuss: r/MachineLearning
๐ŸŒธBloom Variants
Zero to Mastery: [July 2025] Python Monthly Newsletter ๐Ÿ
zerotomastery.ioยท2d
โšกHomebrew CPUs
Fixed-Point-Oriented Programming: A Concise and Elegant Paradigm
arxiv.orgยท3d
๐Ÿ’ปProgramming languages
How Nippon India Mutual Fund improved the accuracy of AI assistant responses using advanced RAG methods on Amazon Bedrock
aws.amazon.comยท4d
๐Ÿ“ฅFeed Aggregation
BuildSTG: A Multi-building Energy Load Forecasting Method using Spatio-Temporal Graph Neural Network
arxiv.orgยท4d
๐Ÿ—œ๏ธGraph Compression
DepMicroDiff: Diffusion-Based Dependency-Aware Multimodal Imputation for Microbiome Data
arxiv.orgยท1d
๐Ÿง Machine Learning
Memorization in Fine-Tuned Large Language Models
arxiv.orgยท4d
๐Ÿ’ปLocal LLMs
Charting the Course: Future Innovations for NFT Marketplace dApp
hackernoon.comยท3d
๐ŸŒŠStreaming Systems
Automatic Classification of User Requirements from Online Feedback -- A Replication Study
arxiv.orgยท3d
๐Ÿ“ŠFeed Optimization
MAGIC: A Multi-Hop and Graph-Based Benchmark for Inter-Context Conflicts in Retrieval-Augmented Generation
arxiv.orgยท3d
๐Ÿ“‡Dublin Core
Structured Parsing Is the Key to Making LLMs Work on Large Codebases
hackernoon.comยท4d
๐ŸŒณIncremental Parsing
Efficient Differentially Private Fine-Tuning of LLMs via Reinforcement Learning
arxiv.orgยท2d
๐Ÿ’ปLocal LLMs
RL from Teacher-Model Refinement: Gradual Imitation Learning for Machine Translation
arxiv.orgยท2d
๐ŸŽ™๏ธWhisper
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