AEVA Devlog #1

This is Project AEVA, an AI I’ve been trying to create completely from scratch on consumer hardware I own to compete with the current SOTA architectures. I originally started creating this AI because i thought that LLM’s although usefull and highly advance come with many issues esspecially on low-end hardware, halucinations, memory limit and the frozen weights after training. instead i want my AI to actually live with a human level life-span and continuously learn during that tmie slowly increasing its parameter size.

After months of designing and rewriting, AEVA (The name of the model I’m making) has officially reached its first training run. Instead of using Transformers, I’m building a completely new cognitive AI architecture designed to compete with frontier models while running on consumer hardware. The current architecture scales in O(n), is designed for massive context and persistent memory, and aims to support self-improvement and offline “sleep” learning in the future. Right now, the first model is being trained for 4 hours into training on my RTX 5090, and if everything goes well, it should become conversational soon. This is just the beginning for AEVA.

• Completed designing and programing the architecture
• Started creating a better dataset for the model
• Started Modl Training