The Token Toll of Reasoning: How Context Window Limits Impact LLMs
Large Language Models (LLMs) have transformed how we process and interact with information. However, their capabilities are bounded by certain constraints, one of the most significant being the context window size—the amount of information the model can consider at once. While this limitation is often associated with the length of input text, the complexity of […]
Making AI Work for Code Documentation
In the realm of large-scale software projects, well-maintained documentation is essential for smooth collaboration, efficient onboarding, and effective maintenance. However, the sheer scale and complexity of ever-evolving codebases present unique challenges. While Large Language Models (LLMs) promise to streamline documentation, their limitations in understanding context and generating tailored content often hinder their effectiveness. This […]
Grounding AI with Structure: Addressing Context Window Limitations for Reliable Outputs
Large Language Models (LLMs) have become indispensable tools for research, enabling organizations to analyze extensive datasets and generate actionable insights. However, to ensure these outputs are reliable, models must be effectively “grounded” in authoritative data—information that is accurate, trusted, and tailored to specific use cases. Grounding AI becomes particularly challenging when working with large, complex […]
Beyond Big: The End of the Hype Cycle
As AI continues to advance, the immense promise of Generative AI (GAI) has driven massive investment and excitement. However, signs are emerging that the GAI hype cycle may be nearing its peak, with economic demands beginning to take precedence over sheer technological ambition. Challenges like scaling limitations and data quality issues are fueling this […]
Overcoming RAG Limitations with Awarity’s Elastic Context Window
Introduction Retrieval-Augmented Generation (RAG) has emerged as a popular technique to enhance the capabilities of large language models (LLMs) by combining their generative power with the ability to access and retrieve information from external knowledge sources. While RAG has shown promise in various applications, scaling it to handle the massive datasets encountered in enterprise environments […]
Navigating the Challenges of Context Window Limitations
In the deployment of Large Language Models (LLMs), context windows define the amount of data a model can process at any given time. While this might sound like a minor technical detail, it directly impacts the quality of insights generated—especially when working with enterprise-level datasets that can easily reach tens of gigabytes. For many […]