The Whizbang Weekly

  • Understanding Agentic RAG for Business Efficiency

    AI adoption is accelerating across enterprises, with many organizations already implementing Retrieval Augmented Generation (RAG) systems to power knowledge-driven applications. But while traditional RAG has proven valuable, its static approach is increasingly insufficient for complex business needs. Enter Agentic RAG – an approach that transforms passive information retrieval into intelligent orchestration. As organizations push toward…

    Campbell Robertson

  • The Rise of Agentic AI: Navigating the Future of Autonomous Systems

    Agentic AI, what’s the deal? These systems are designed to operate with a degree of autonomy, enabling them to achieve specific goals independently. This shift towards Agentic AI is changing the way businesses and technologies operate. It provides many benefits and presents unique challenges. In this post, we will explore the concept of Agentic AI.…

    Campbell Robertson

  • Why Small Language Models Are the Future of AI

    The great thing about AI is that nothing stays constant. Case in point models and model choice. Sustainability and cost are causing AI to undergo a significant transformation. with small language models (SLMs) are emerging as a critical component in the quest for efficient, cost-effective, and environmentally sustainable AI solutions. Unlike their large language model…

    Campbell Robertson

  • AI Agents – Why the Buzz?

    AI Agents vs. Large Language Models (LLMs) – Understanding the Differences and Implications The rapid evolution of artificial intelligence (AI) has led to the emergence of two distinct concepts: AI agents and Large Language Models (LLMs). While both are integral to modern AI applications, they serve different purposes and have distinct characteristics. This article aims…

    Campbell Robertson

  • The Rise of Better AI Models on the Horizon

    The landscape of artificial intelligence is undergoing a significant transformation with the emergence of a new class of generative AI models that leverage mathematical reasoning to correct themselves and prevent hallucinations. This shift marks a critical departure from the current generation of models, which, despite their impressive capabilities, are plagued by the problem of hallucinations—instances…

    Campbell Robertson

  • Update: Model Choice and Deprecation Planning

    Selecting the right Large Language Model (LLM) for your organization is a critical decision that can significantly impact your AI strategy and outcomes. As the field of AI rapidly evolves, it’s essential not only to choose wisely but also to plan for model deprecation. Here’s a comprehensive approach to tackle both challenges. Choosing the Right…

    Campbell Robertson

  • Dave vs. Goliath in GenAI

    Apologies for the lapse in posts, much continues to develop in this space with more ‘mini’ models being rolled out and the growing concern towards large LLMs consuming vasts amounts of data and energy; I think we should evaluate what and when various models should be used. Large Language Models (LLMs) and mini LLMs represent…

    Campbell Robertson

  • How to use lower cost LLM’s in larger content based tasks.

    As we explore the evolution of large language models (LLM), both cost-effectiveness and computational efficiency are critical factors to consider. Lesser expensive, smaller LLMs with a smaller token limit while seemingly restrictive, offer substantial benefits over their larger, pricier counterparts. The notable advantage of smaller LLMs is their affordability and swift response times. They serve…

    Campbell Robertson

  • In Generative AI: Model size matters, but it’s how you use them that counts.

    As I talk with clients looking to use Generative AI models they seem to make this erroneous decision that the larger the model is (number of tokens it can process) the better it will be at everything. This is far from the truth. Larger models take more computation power e.g. more money. We are making progress in seeing…

    Campbell Robertson