AI hallucinations occur because large language models (LLMs) like GPT generate text by predicting the most likely sequence of words based on their training data—not by applying logical reasoning or…

In the evolving world of AI, semantic chunking has emerged as a powerful technique to improve machine comprehension of human language. It helps bridge the gap between mere word prediction…

The concept of determinism plays a pivotal role in shaping how we develop, deploy, and trust AI systems. At Jaxon, we’ve been leveraging determinism as a central tenet of creating…

In the fast-paced world of financial services, staying ahead of the curve is essential. AI-driven technologies are transforming the landscape, enhancing efficiency, compliance, and customer satisfaction. Here are 17 innovative ways…

The Limitations of the RAG Technique in Addressing Hallucinations in Large Language ModelsIn recent years, the development of Large Language Models (LLMs) has revolutionized the field of natural language processing…

Effective use of generative AI is being blocked by the so-called “hallucination problem”, when Large Language Models (LLMs) make inaccurate predictions (flat-out fabrications). For regulated and high-risk applications, this is…

First principles thinking is a method of problem-solving  that involves breaking a situation down into its fundamental elements and building up from there. It's based on the idea of examining…

The AI Perspective on the AI Risk Management Framework In the digital tapestry of the 21st century, where artificial intelligence (AI) threads increasingly intertwine with the fabric of daily life,…

"System 1" and "System 2" are terms popularized by  Daniel Kahneman in his book "Thinking, Fast and Slow", which describe two different modes of thought that govern our [human] decision-making…

Neural networks, as a sub-symbolic data processing model, play a crucial role in the field of deep learning and generative AI. These networks, through their layered structures and interconnected nodes,…