Binary Optimization, LLVM Tool, Profile-Guided, Layout Optimization

Shader Basics
bobacupcake.com·4h·
Discuss: Hacker News
Gleam
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You Win Some, You Lose Some: On Papercraft and More
noteflakes.com·15h·
🎨Creative Coding
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LLM-Driven Robots Risk Enacting Discrimination, Violence, and Unlawful Actions
link.springer.com·16h·
Discuss: Hacker News
💬Prompt Engineering
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For devs/engineers naysaying LLM tools, which ones have you tried?
news.ycombinator.com·1d·
Discuss: Hacker News
💬Prompt Engineering
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VoxCPM Text-to-Speech running or Apple Neural Engine ANE
reddit.com·1d·
Discuss: r/LocalLLaMA
🚀Performance
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What Prompt Engineering in 2025 Actually Looks Like (When You’re Trying to Build for Real)
dev.to·2d·
Discuss: DEV
💬Prompt Engineering
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Monitoring Autonomous Systems Telemetry: Building an HFT-Grade Network Analysis Pipeline for UDP-based Protocols
dev.to·1d·
Discuss: DEV
🔭Tracing
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From COBOL to Cloud: How Kiro's Spec-Driven Development Transformed Legacy Modernization
dev.to·1d·
Discuss: DEV
🔧DevOps
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Kimi infra team: Quantization is not a compromise, it's the next paradigm
reddit.com·2d·
Discuss: r/LocalLLaMA
📱Edge AI
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CAE: Character-Level Autoencoder for Non-Semantic Relational Data Grouping
arxiv.org·3h
🧮Vector Databases
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LLMs vs. Traditional Sentiment Tools in Psychology: An Evaluation on Belgian-Dutch Narratives
arxiv.org·3h
💬Natural Language Processing
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💻Your GitHub Speaks Louder Than Your Resume: A Tiger Cloud Story🐅
dev.to·2d·
Discuss: DEV
ClickHouse
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Building a Producer–Consumer Pipeline in Go Using Goroutines and Channels
dev.to·1d·
Discuss: DEV
🔵Go
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A Practical Guide to AI Voice Agent Observability: Debugging Latency with VideoSDK Traces
dev.to·1d·
Discuss: DEV
📊Performance Tools
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Atomic State Management in React: Zustand vs Jotai vs Recoil ⚛️
dev.to·35m·
Discuss: DEV
⚛️React
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Crushing IR-Drop: How Smart Software is Revolutionizing AI Hardware Performance
dev.to·3d·
Discuss: DEV
Hardware Acceleration
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From Semantic Roles to Opinion Roles: SRL Data Extraction for Multi-Task and Transfer Learning in Low-Resource ORL
arxiv.org·3h
📝Parsing
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MCP-RiskCue: Can LLM infer risk information from MCP server System Logs?
arxiv.org·1d
🦙Ollama
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Attention and Compression is all you need for Controllably Efficient Language Models
arxiv.org·2d
🤖Transformers
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