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Pair programming with AI in 2025: habits that stick
vLLM in 2025: the improvements that matter to LLM-serving teams
Microsoft's GraphRAG in enterprise: patterns that work
Alignment evaluation: RLHF, DPO, and recent alternatives
Gemma 2: Google's open model one year later

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Tag: mlops

LLM Fine-Tuning: When It’s Worth Training Your Own

July 13, 2023 javi

Estructuras de datos conectadas representando entrenamiento de IA

Fine-tuning remains expensive and operationally complex. A guide to deciding between RAG, prompt engineering, and your own training.

Desarrollo de Software Inteligencia Artificial

Recent Posts

Pair programming with AI in 2025: habits that stick
vLLM in 2025: the improvements that matter to LLM-serving teams
Microsoft’s GraphRAG in enterprise: patterns that work
Alignment evaluation: RLHF, DPO, and recent alternatives
Gemma 2: Google’s open model one year later
o3 in public: the reasoning leap is confirmed
Gemini 2.0: integrated tools and agent mode
Home lab: self-hosted lab as a testing ground
Full-stack TypeScript in 2025: the good, the meh, the bad
WASI preview 3: threads and async in WebAssembly
AI-assisted code review: an honest adoption story
Llama 3.2 at the edge: Meta bets on small
Cloudflare Workers in 2025: from edge to enterprise
Generics in Go: three years later, what has survived
NPU in the PC: faster, cheaper local AI

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