Taming the Data Beast: Build Pipelines That Bend, Not Break by Arvind Sundararajan
🚂Cranelift Backend
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Show HN: Lite³ – A JSON-Compatible Zero-Copy Serialization Format in 9.3 KB of C
🔢Binary Formats
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How LLM Inference Works
arpitbhayani.me·1d
🚀Tokenizer Performance
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Concept-Based Generic Programming -- Bjarne Stroustrup
isocpp.org·8h
🗂️Type Indexing
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Show HN: I ended up vibecoding a full fledged interpreter when ads annoyed me
🌱Minimal Interpreters
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Making SLH-DSA 10x-100x Faster
conduition.io·5h
🔗Hash Algorithms
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I Thought TOON Was Hype. Then I Tested It…
📋JSON Parsers
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<p>**서론** 후성유전체학은 DNA 염기서열 변화 없이 유전자 발현을 조절하는 메커니즘을 연구하는 분야이며, ATAC-seq (Assay for Transposase-Accessible Chromatin using sequencing)와 ChIP-seq (Chromatin Immun...
freederia.com·1d
⚡Tokenizer Optimization
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10000
jro.sg·17h
📦Executable Size
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Automated High-Throughput Functional Protein Screening via Graph-Neural Network Enhanced Microfluidics
🗺️Region Inference
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10 Essential Java Libraries - How Essential Are They Really?
hackernoon.com·1d
🔧API Design
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Taming the Beast: The Move To Declarative API Validation in Kubernetes - Yongrui Lin, Google
youtube.com·1d
🔧Nickel
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The Offline Data Engineer: Building Resilient API Pipelines that Work on an Airplane
📋JSON Parsers
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September 2024 Progress in Guaranteed Safe AI
lesswrong.com·2d
🗺️Region Inference
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Show HN: Another JSON Alternative
📋JSON Parsers
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Building an AWS-Based RAG Pipeline
⚡Parallel Parsing
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AMS-KV: Adaptive KV Caching in Multi-Scale Visual Autoregressive Transformers
arxiv.org·2d
🗺️Region Inference
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