Hackernews posts about LLMs
LLMs is an acronym for Large Language Models, which refers to artificial intelligence language processing systems that can understand and generate human-like text.
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- I love LLMs, I hate hype (geohot.github.io)
- Jamesob's guide to running SOTA LLMs locally (github.com)
- I think I have LLM burnout (www.alecscollon.com)
- Mesh LLM: distributed AI computing on iroh (www.iroh.computer)
- The gap between open weights LLMs and closed source LLMs (blog.doubleword.ai)
- Stop Telling Me to Ask an LLM (blog.yaelwrites.com)
- Good results fine tuning a local LLM like Qwen 3:0.6B to categorize questions (www.teachmecoolstuff.com)
- LLMs Are Complicated Now (ianbarber.blog)
- Claude-real-video － any LLM can watch a video (github.com)
- Inkling – Open-Weights 975B Parameter LLM (thinkingmachines.ai)
- No LLM Code in Dependencies (joeyh.name)
- Why current LLM costs are not sustainable (aditya.patadia.org)
- DSLs Enable Reliable Use of LLMs (martinfowler.com)
- Ornith-1.0: Self-scaffolding LLMs for agentic coding (deep-reinforce.com)
- Do LLMs pass the mirror test? (blog.pascalschuster.de)
- Regression to the Mean: on LLMs and the quiet death of the new (rruxandra.github.io)
- LLM Networking with MikroTik (blog.greg.technology)
- I canceled my French tutor and built an LLM tool that does it better (alshe.substack.com)
- Building Food Metadata with LLM Juries (careersatdoordash.com)
- Comparing Fable and 10 other LLMs on refactoring a LangGraph god node (wtf.korridzy.com)
- What I'm Finding About LLM Code Style and Token Costs (www.jimmont.com)