Hacker News
- Anti-hype LLM reading list https://gist.github.com/veekaybee/be375ab33085102f9027853128dc5f0e 0 comments
- Anti-AI Hype LLM Reading List https://gist.github.com/veekaybee/be375ab33085102f9027853128dc5f0e 52 comments
- Super cool collection of resources on learning more about LLMs without the AI hype train https://gist.github.com/veekaybee/be375ab33085102f9027853128dc5f0e 2 comments programming
Linking pages
- GitHub - oscinis-com/Awesome-LLM-Productization: Awesome-LLM-Productization: a curated list of tools/tricks/news/regulations about AI and Large Language Model (LLM) productization https://github.com/oscinis-com/Awesome-LLM-Productization 1 comment
- Why Voice Failed as a Platform - by Dustin Coates https://talkingtocomputers.substack.com/p/why-voice-failed-as-a-platform 0 comments
- GitHub - nlpfromscratch/nlp-llms-resources: Master list of curated resources on NLP and LLMs https://github.com/nlpfromscratch/nlp-llms-resources 0 comments
Linked pages
- What Is ChatGPT Doing … and Why Does It Work?—Stephen Wolfram Writings https://writings.stephenwolfram.com/2023/02/what-is-chatgpt-doing-and-why-does-it-work/ 1074 comments
- The Bitter Lesson http://incompleteideas.net/IncIdeas/BitterLesson.html 366 comments
- Mixtral of experts | Mistral AI | Open source models https://mistral.ai/news/mixtral-of-experts/ 300 comments
- How is LLaMa.cpp possible? https://finbarr.ca/how-is-llama-cpp-possible/ 227 comments
- Prompt Engineering vs. Blind Prompting – Mitchell Hashimoto https://mitchellh.com/writing/prompt-engineering-vs-blind-prompting 216 comments
- [2005.14165] Language Models are Few-Shot Learners https://arxiv.org/abs/2005.14165 201 comments
- The Best GPUs for Deep Learning in 2023 — An In-depth Analysis https://timdettmers.com/2023/01/30/which-gpu-for-deep-learning/ 167 comments
- Why Chatbots Are Not the Future of Interfaces https://wattenberger.com/thoughts/boo-chatbots 158 comments
- [2212.03551] Talking About Large Language Models https://arxiv.org/abs/2212.03551 149 comments
- GitHub - dair-ai/Prompt-Engineering-Guide: 🐙 Guides, papers, lecture, notebooks and resources for prompt engineering https://github.com/dair-ai/Prompt-Engineering-Guide 149 comments
- [1706.03762] Attention Is All You Need https://arxiv.org/abs/1706.03762 145 comments
- Building LLM applications for production https://huyenchip.com/2023/04/11/llm-engineering.html 136 comments
- Why host your own LLM? http://marble.onl/posts/why_host_your_own_llm.html 134 comments
- Extracting Training Data from ChatGPT https://not-just-memorization.github.io/extracting-training-data-from-chatgpt.html 134 comments
- All the Hard Stuff Nobody Talks About when Building Products with LLMs | Honeycomb https://www.honeycomb.io/blog/hard-stuff-nobody-talks-about-llm 126 comments
- [2310.06825] Mistral 7B https://arxiv.org/abs/2310.06825 124 comments
- Phi-2: The surprising power of small language models - Microsoft Research https://www.microsoft.com/en-us/research/blog/phi-2-the-surprising-power-of-small-language-models/ 121 comments
- GitHub - ray-project/llm-numbers: Numbers every LLM developer should know https://github.com/ray-project/llm-numbers 113 comments
- GitHub - rasbt/LLMs-from-scratch: Implementing a ChatGPT-like LLM from scratch, step by step https://github.com/rasbt/LLMs-from-scratch 98 comments
- Natural Language Is an Unnatural Interface - by Varun https://varunshenoy.substack.com/p/natural-language-is-an-unnatural 88 comments
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