This repository provides a curated list of research papers and blog posts aimed at helping software engineers transition into AI Engineering roles. It covers foundational concepts, advanced techniques, and practical applications in areas like natural language processing, computer vision, and large language model development.

How It Works

The resource list is organized thematically, covering key areas of AI Engineering. It highlights seminal papers and recent advancements in areas such as tokenization, vectorization, attention mechanisms, mixture-of-experts, reinforcement learning from human feedback (RLHF), chain-of-thought prompting, and efficient inference techniques like FlashAttention and SSMs. The selection emphasizes practical relevance for engineers seeking to understand and implement modern AI systems.

Quick Start & Requirements

• Access to the resources requires no installation.
• Prerequisites include an interest in AI Engineering and access to academic paper repositories (e.g., arXiv) or online blogs.
• Links to official resources are provided within the README for further exploration.

Highlighted Details

• Comprehensive coverage of Transformer architectures and their optimizations (FlashAttention, Multi-Query Attention, Grouped-Query Attention).
• Detailed sections on advanced LLM techniques like RLHF, Chain-of-Thought prompting, and reasoning capabilities.
• Inclusion of efficient inference methods and alternative architectures like State Space Models (SSMs) and RWKV.
• Case studies on practical AI applications in industry, such as automated unit testing and retrieval-augmented generation.

Maintenance & Community

• The resource list is maintained by InterviewReady.
• Further resources and curated lists can be found at https://interviewready.io/resources/.

Licensing & Compatibility

• The repository itself is not licensed for distribution; it serves as a curated list of external resources.
• Individual papers and blogs are subject to their respective licenses and terms of use.

Limitations & Caveats

This repository is a static list of resources and does not include code implementations or interactive tutorials. The rapidly evolving nature of AI means some information may become dated, requiring users to seek out the latest research.