Ai

Balancing Big Ideas and Practical Detail in AI Development

Evaluating the role of low-code platforms and AI-enhanced code-first development

Exploring AI paradigms, from modular to end-to-end models, and how hardware drives innovation.

A comparison of pretrained, fine-tuning, RAG, and prompt engineering in LLM

Designing better prompts for guiding Large Language Models (LLMs) to generate accurate and relevant responses

Enhancing information retrieval with embedding models and document chunking

Vector database and its application in RAG systems

A short summary of key concepts in retrieval augmented generation

LLMs in AI application development - change in efficiency and versatility