GPT, Prompt Engineering, Fine-tuning, Embeddings

LLM Concepts (Explained Without Making Your Brain Hurt): What Every Developer Should Know
dev.to·6h·
Discuss: DEV
🤖AI
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Quantifying Edits Decay in Fine-tuned LLMs
arxiv.org·18h
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MoM – Mixture of Model Service
github.com·8h·
Discuss: Hacker News
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Vibe-tuning: creating custom models with a prompt
distillabs.ai·1d·
Discuss: Hacker News
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Andrej Karpathy on LLM cognitive deficits
lesswrong.com·1d
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Running high-scale reinforcement learning (RL) for LLMs on GKE
cloud.google.com·1d
💻Software development
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So-called reasoning models are more efficient but not more capable than regular LLMs, study finds
the-decoder.com·4h
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I Read Sam Bhagwat's AI Agents Bible So You Don't Have to (But Probably Should)
kuber.studio·7h·
Discuss: Hacker News
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From Zero to LLMOps Hero: Your 101 Guide to Running LLMs in Production
analyticsvidhya.com·1d
🤖AI
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Training GPT in Sheets
zalex.co·6h·
Discuss: Hacker News
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Synth: The New Data Frontier
pleias.fr·18h·
Discuss: Hacker News
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LLM-Driven Robots Risk Enacting Discrimination, Violence, and Unlawful Actions
link.springer.com·8h·
Discuss: Hacker News
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Context rot: the emerging challenge that could hold back LLM progress
understandingai.org·1d
🤖AI
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4 open‑source apps I use to run AI locally
xda-developers.com·8h
🤖AI
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AGRAG: Advanced Graph-based Retrieval-Augmented Generation for LLMs
arxiv.org·18h
🤖AI
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Apple's LLM Breakthrough
xray.greyb.com·11h·
Discuss: Hacker News
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Evaluating LLMs' Reasoning Over Ordered Procedural Steps
arxiv.org·1d
🤖AI
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Looking for feedback on inference optimization - are we solving the right problem? [D]
reddit.com·4h·
Discuss: r/LLM
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TAI #178: Kimi K2 Thinking Steals the Open-Source Crown With a New Agentic Contender
pub.towardsai.net·8h
🤖AI
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