Ollama Local LLM Server, Ollama Model Management, Ollama API Server and Inference Engine

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Efficient Evaluation of LLM Performance with Statistical Guarantees
arxiv.org·15h
🔧LLVM
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Building "Devwrite": A Local, Agentic Writing Assistant with Ollama & Node.js
dev.to·1d·
Discuss: DEV
🥖Bun
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Researchers Find 175,000 Publicly Exposed Ollama AI Servers Across 130 Countries
thehackernews.com·2h
🎯Microservices
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Implementing local-first agentic AI: A practical guide
blog.logrocket.com·6h
📡Event-Driven Architecture
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**Abstract:** The burgeoning field of large language models (LLMs) presents transformative potential across various sectors, yet their development and deploy...
freederia.com·7h
🌳Tree-sitter
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How MIT’s new framework solve LLM's memory barrier and 'context rot' problem
bdtechtalks.substack.com
·2d
🌳Tree-sitter
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LLM-AutoDP: Automatic Data Processing via LLM Agents for Model Fine-tuning
arxiv.org·15h
🌳Tree-sitter
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The AI Control Plane: Observability, Cost Governance, and Policy for LLM Applications
hackernoon.com·7h
📊Observability
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pollinations.ai
pollinations.ai·1h
🎲Procedural Generation
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You can make a self-hosted AI server with LM Studio 0.4.0
howtogeek.com·1d
🏗️MLIR
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RSSDeck- A TweetDeck inspired RSS Reader + AI + Telegram bot
github.com·11h·
Discuss: r/rss
🌳Tree-sitter
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LLM-Enabled Software Engineering Tools Advance Energy Efficiency Throughout The SDLC
quantumzeitgeist.com·7h
🔧LLVM
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How I Used GenAI to Rapidly Prototype MaestroML (and Why FastAPI Won)
keithalexanderashe.substack.com·46m·
Discuss: Substack
⚙️JIT Compilation
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Deploy Kimi K2.5 on a Mac mini M4 Cluster and Call Penligent.ai: The Minimal Local-First Agentic Hacker Tutorial
penligent.ai·11h·
Discuss: Hacker News
📦Nixpkgs
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LLM Inference Optimization
pub.towardsai.net
·1d
💾Cache Optimization
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API Platform | API Platform for Laravel Projects
api-platform.com·5h
🌐Web Development
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2025: The Definitive Year of Large Language Models (LLMs)
eu.36kr.com·21h
🌳Tree-sitter
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I tried local AI on my M1 Mac, and the experience was brutal - here's why
zdnet.com·6h
⚙️Performance Profiling
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Building AI-native backends – RAG pipelines, function calling, prompt versioning, LLM observability
dev.to·1d·
Discuss: DEV
🏗️MLIR
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