LLM training and inference, RAG systems, model evaluation, AI tooling, and engineering workflows.
From fundamental scientific research to practical digital tools and artificial intelligence breakthroughs, explore thoughtful analysis across our four core categories.
Design robust evaluation harnesses for LLM applications: ground truth curation, RAGAS metrics, Promptfoo CI/CD testing, and LLM-as-a-judge bias mitigation.
Engineer a production RAG pipeline: semantic chunking, dense embeddings, BM25 hybrid search, cross-encoder reranking, and hallucination mitigation.
A rigorous mathematical explanation of decoder-only transformers: self-attention mechanisms, RoPE positional embeddings, SwiGLU activations, and KV caching.
A financial and hardware engineering breakdown of frontier AI models: memory bandwidth limits, KV cache sizing, FP8 quantization, and cloud unit economics.