Llama 3

A deep dive into deploying production-ready LLM inference servers using Llama 3 and vLLM, covering hardware math, networking, and production optimization.

A deep dive into LLM memory math, explaining why model weights are only half the story and how to calculate KV cache requirements for Llama 3 and Gemma 2.

Meta has officially rolled out its AI agent for WhatsApp Business globally, introducing a significant shift in its monetization strategy by charging businesses based on token usage rather than flat conversation fees.

Meta's strategic acquisition of Assured Robot Intelligence marks a significant pivot toward Embodied AI and Vision-Language-Action (VLA) models, bridging the gap between digital LLMs and physical humanoid robotics.

Learn how KVQuant uses 4-bit KV cache quantization to reduce LLM memory requirements by 4x, enabling massive models like LLaMA-70B to run on consumer hardware with minimal accuracy loss.

A comprehensive guide on building production-grade AI agents for under $5/month using OpenRouter, LangChain, and cost-efficient open-source models like Llama 3 and DeepSeek.

Learn how to build a fully private Personal Health Record (PHR) analyzer using Llama-3, WebGPU, and WebLLM. This guide covers local inference, React integration, and edge AI optimization.

Meta expands its data center infrastructure with a massive commitment to Nvidia's Blackwell, Rubin, Grace, and Vera architectures to power the next generation of Llama models.

Discover how moving from GPT-4 few-shot prompting to fine-tuned LLaMA 3 LoRA adapters resulted in a 30% conversion lift and a massive reduction in token costs for a content optimization platform.