Optimizing Generative AI with Vector Databases: A Deep Dive into Search Algorithms and TechniquesThe explosion of Generative AI (GenAI) models has significantly transformed fields like natural language processing, computer vision, and…Sep 14, 2024Sep 14, 2024
OpenAI o1- think before they speakThe OpenAI o1 models are designed to “think before they speak,” which means they spend more time reasoning through problems before…Sep 14, 2024Sep 14, 2024
Tokenization and Subword Tokenization in Generative AI: A Complete GuideIntroduction to TokenizationSep 8, 2024Sep 8, 2024
Unlocking Efficiency and Scale: The Mixture of Experts (MoE) and Sparse MoE (SMoE) Architectures…Think of a hospital with a team of specialist doctors — each doctor is an expert in a different area, such as cardiology, neurology, or…Aug 24, 2024Aug 24, 2024
Published inData Science at MicrosoftExploring quantization in Large Language Models (LLMs): Concepts and techniquesLarge Language Models (LLMs) such as GPT have transformed natural language processing (NLP), with GPT-3 featuring an impressive 175 billion…Aug 20, 2024Aug 20, 2024
RAGAS for RAG in LLMs: A Comprehensive Guide to Evaluation Metrics.IntroductionAug 15, 2024Aug 15, 2024
Boosting Retrieval in RAG for LLMs: The Power of BM25 and RRFBM25 (Best Matching 25) and RRF (Reciprocal Rank Fusion) are two techniques that can be used to imBM25 (Best Matching 25) and RRF…Aug 11, 2024Aug 11, 2024
Standardization and Min-Max Scaling in Machine Learning and Deep Learning.IntroductionAug 11, 2024Aug 11, 2024
Risks Associated with Prompt Engineering in Large Language Models (LLMs)Prompt engineering in Large Language Models (LLMs) involves carefully crafting input prompts to guide the model’s output in a desired…Aug 9, 2024Aug 9, 2024
