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AI Engineer Reading List
We picked 50 paper/models/blogs across 10 fields in AI Eng: LLMs, Benchmarks, Prompting, RAG, Agents, CodeGen, Vision, Voice, Diffusion, Finetuning. If you're starting from scratch, start here.
The picks from all the speakers in our Best of 2024 series catches you up for 2024, but since we wrote about running Paper Clubs, we’ve been asked many times for a reading list to recommend for those starting from scratch at work or with friends. Note: The GPT3 paper (“Language Models are Few-Shot Learners”) should already have introduced In-Context Learning (ICL) - a close cousin of prompting. AlphaCodeium paper- Google published AlphaCode and AlphaCode2 which did very well on programming problems, but here is one way Flow Engineering can add a lot more performance to any given base model.
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