A senior engineer spent the past year implementing five LLM architectures from scratch in PyTorch, including GPT-2, Llama 3, and DeepSeek. The project resulted in open-source code and a detailed book documenting the process, explaining advanced concepts like KV cache, MoE, and FP8 quantization.
EchoMemo is a voice-controlled local AI agent that runs entirely offline, utilizing models like Whisper and Ollama to convert speech to text and understand user intent. This project demonstrates a solution for privacy, cost, dependency, and latency, offering a clean web UI without the need for APIs or internet after initial setup.
This article details how to deploy the Llama 3.2 11B model with GGUF quantization on a low-cost DigitalOcean Droplet for production inference. It demonstrates significant cost savings compared to paid AI APIs, while maintaining good performance on CPUs.
This article compares leading open-source LLMs of 2026, including Llama 3, Mistral, Qwen, and Gemma, emphasizing their competitive performance, licensing, and hardware requirements. It aims to assist users in selecting the right model for their specific use case.
This content explains how to deploy Llama 3.2 Vision with vLLM and quantization on a DigitalOcean Droplet to drastically reduce costs compared to GPT-4 Vision. It highlights production-grade multimodal inference at a fraction of the price.
This article details the construction of a voice-controlled local AI agent, utilizing Groq, Whisper, and Llama 3.3-70b for intent detection and action execution. It covers the architecture, chosen models, and challenges in creating a pipeline with Speech-to-Text and Intent Detection components.
This content details a "Divide & Conquer" framework that enables smaller language models to outperform larger ones like GPT-4o on long context tasks. It addresses the performance degradation of LLMs with growing context windows by breaking documents into parallel chunks.
This content provides an in-depth analysis of LLaMA 3, Meta's advanced large language model. It features insights from Thomas Scialom, a key figure from Meta, offering a detailed exploration of its architecture, capabilities, and potential applications.
