Latest Posts

By Sam G. on Feb 11, 2025

Essential strategies to efficiently scale RAG (Retrieval-Augmented Generation) for millions of documents, including vector database selection, indexing methods, reranking approaches, and optimized data ingestion pipelines.

By Hannah F. on Feb 8, 2025

Complete guide to system requirements for running DeepSeek models on Mac, including both full and quantized models. We provide detailed recommendations on compatible Apple Silicon devices like MacBook Pro, Mac Studio, and iMac.

By Wei Ming T. on Feb 7, 2025

Top LLMs for coding in 2025, ranked based on accuracy, integration, cost, and speed. Learn which AI tools work best and why Claude 3.5 Sonnet and OpenAI's models stand out.

By Ryan A. on Feb 2, 2025

GPU system requirements for Qwen models with detailed guidance on VRAM needs, recommended GPUs for both full and quantized versions, and best practices for efficient AI deployment.

By Wei Ming T. on Jan 26, 2025

Comparison of the training costs of two cutting-edge language models, DeepSeek V3 (671B parameters) and Llama 3.1 (405B parameters)

By Sam G. on Jan 26, 2025

Hugging Face simplifies machine learning and natural language processing with pre-trained models, tools, and an active community. Learn how it fits into your AI learning journey.

By Wei Ming T. on Jan 22, 2025

GPU system requirements to run DeepSeek-R1 and its distilled models effectively, along with recommendations for choosing the right hardware for your needs.

By Wei Ming T. on Jan 22, 2025

Learn how to implement the FizzBuzz problem using a deep learning approach with PyTorch. This step-by-step guide highlights the coding process, training, and testing to achieve impressive results.

By Sam G. on Jan 22, 2025

Top vector databases optimized for Retrieval-Augmented Generation (RAG). Learn why RAG relies on vector databases and explore short code examples to integrate each.

By Wei Ming T. on Jan 22, 2025

Learn how to build a straightforward blog post recommendation system using Scikit-Learn. We'll leverage TF-IDF and cosine similarity to suggest related content based on text similarity.