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Building Meta's GenAI infrastructure(engineering.fb.com)
636 points by mootpt | 291 comments
Meta engineering blog post describing its large GPU training clusters for generative AI, including RDMA and InfiniBand networking, Grand Teton hardware, and storage.
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Training LLMs from ground zero as a startup(yitay.net)
360 points by swyx | 92 comments
Yi Tay's blog post on the experience of training large language models from scratch at a startup (Reka), covering compute, infrastructure, and lessons learned.
Meta AI announces Massive Multilingual Speech code, models for 1000+ languages(github.com)
615 points by crakenzak | 193 comments
GitHub directory in Meta's fairseq repository containing code and models for Massive Multilingual Speech (MMS), covering ASR, TTS, and language ID for 1000+ languages.
Train Your Own LLM from Scratch(github.com)
376 points by kristianpaul | 43 comments
GitHub repository by angelos-p providing code and docs for training your own large language model from scratch.
Learning to Reason with LLMs(openai.com)
1573 points by fofoz | 1186 comments
OpenAI research post introducing o1, a large language model trained with reinforcement learning to reason using a long internal chain of thought before answering.
Efficient streaming language models with attention sinks(github.com)
401 points by guywithabowtie | 65 comments
GitHub repository from MIT HAN Lab for StreamingLLM, code for efficient streaming language models using attention sinks.
AI Made Writing Code Easier. It Made Being an Engineer Harder(ivanturkovic.com)
343 points by saikatsg | 242 comments
Blog post by Ivan Turkovic arguing that AI tools make producing code easier while making the broader job of being a software engineer harder.