Optimization
NVIDIA AI Researchers Introduce FFN Fusion: A Novel Optimization Technique that Demonstrates How Sequential Computation in Large Language Models LLMs can be Effectively Parallelized
Large language models (LLMs) have become vital across domains, enabling high-performance applications such as natural language generation, scientific research, and conversational agents. Underneath these advancements lies the transformer architecture, where alternating layers of attention mechanisms and feed-forward networks (FFNs) sequentially process tokenized input. However, with an increase in size and complexity, the computational burden required…
10 Google Shopping Product Feed Optimization Tips & Tricks
Google Shopping isn’t just about bidding and budget management – it’s about feeding Google the best possible data. Unlike traditional search ads, where keywords dictate targeting, Shopping campaigns rely on your product feed. The quality, accuracy, and completeness of your product data determine how often and where your ads appear. A well-optimized feed improves impressions,…
Fine-Tuning an Open-Source LLM with Axolotl Using Direct Preference Optimization (DPO) — SitePoint
LLMs have unlocked countless new opportunities for AI applications. If you’ve ever wanted to fine-tune your own model, this guide will show you how to do it easily and without writing any code. Using tools like Axolotl and DPO, we’ll walk through the process step by step. What Is an LLM? A Large Language Model…
Voice Search Optimization At Scale: A Guide For Enterprise Marketers
Smartphones put the world at our fingertips. People have questions that need answering, as well as the services or products they need. All of these things are just a search away, and now, we’ve seen a cosmic shift from traditional search to voice search and voice assistants. Statistically, voice search and assistants are not something…