About 25 results
https://luminary.blog/techs/01-rag-vs-llm · 31 Oct 2025
Understanding the differences between RAG and MCP, when to use each, and how they work together
https://luminary.blog/techs/llm-loss-function · 8 Sep 2025
Exploring Cross-Entropy Loss in Large Language Models.
https://luminary.blog/techs/matryoshka-representation-learning · 4 Sep 2025
Nesting Power and Flexibility into ML Embeddings
https://luminary.blog/techs/deep-seek-ue8m0-fp8 · 26 Aug 2025
Training LLMs without H100 using UE8M0 FP8 number format.
https://luminary.blog/techs/numbers-in-machine-learning · 25 Aug 2025
Understanding INT4, INT8, FP16, BF16, and TF32 formats in machine learning - their precision, speed, and memory trade-offs for training and inference.
https://luminary.blog/techs/gptoss-and-gemma3 · 19 Aug 2025
GPT-OSS and Gemma 3: two new small-but-powerful language models pushing the boundaries.
https://luminary.blog/techs/positional-embeddings · 4 Aug 2025
The mathematical technique that teaches AI models where each word sits in a sequence.
https://luminary.blog/techs/09-token-to-embedding · 31 Jul 2025
How language models convert token IDs into meaningful vector representations that capture semantic relationships.
https://luminary.blog/techs/08-subword-tokenization-algorithms · 30 Jul 2025
Understanding the algorithms behind tokenization in Large Language Models.
https://luminary.blog/techs/07-llm-inference · 29 Jul 2025
Understanding how Large Language Models generate text through the inference process.