Understanding the Distinction: RAG vs Agent-Based AI Systems
Understanding the Distinction: RAG vs Agent-Based AI Systems
In the evolving landscape of AI, two methodologies stand out for enhancing AI capabilities: Retrieval-Augmented Generation (RAG) and Agent-Based Systems. While they share some common goals, their approaches and applications are distinct, yet complement each other in modern AI solutions.
Rise of RAG: Making AI Smarter
Large Language Models (LLMs) have shown remarkable capabilities, but they come with an inherent limitation: they can only work with the information they were trained on. Retrieval-Augmented Generation (RAG) has emerged as an elegant solution to this challenge, fundamentally changing how AI systems access and utilize information.
Creating Logos with AI
Artificial Intelligence image generators are an interesting way to generate new ideas for logos. Marimsa Solutions was in search of a new logo. So we tried out different Ai models to find new inspiration. The methods shown here are Stable Diffusion, StyleGan2 and Playform. The tools used are Runway and Playform.
Changing the Way We See
Augmented Reality applications can be used effectively for marketing and art. Most everyone has a smartphone which makes it easy to implement with many different applications available. But the next generation systems will put the technology closer to your eyes.
AI is Changing Your World
The velocity of the technology around Ai - Artificial Intelligence is accelerating the changes and innovations that are happening. It is impacting how we write, how we draw and even how we think. It is making inroads into any profession that requires writing language, writing code and into creating visual images and videos. Let’s explore some of the places Ai is creating opportunities. (Ai was not used to write this blog but look for that in future posts.)