Parameters powering the next generation of artificial general intelligence
A 258 billion parameter transformer backbone with optimized attention mechanisms for efficient processing.
Specialized subsystems implementing distinct cognitive functions that interact through structured pathways.
Multi-tier memory architecture enabling learning and knowledge retention across extended contexts.
Advanced reasoning capabilities with chain-of-thought processing and self-correction mechanisms.
Unified understanding of text, code, images, and structured data within a single model.
Integrated safety mechanisms ensuring reliable and aligned behavior.
MEGAMIND uses a hybrid architecture combining transformer foundations with specialized cognitive modules. Unlike standard LLMs that use uniform attention layers, MEGAMIND implements differentiated systems for memory, reasoning, planning, and metacognition that interact through structured pathways.
MEGAMIND features 258 billion parameters, extended context processing, multi-modal capabilities (text, code, images), specialized cognitive modules, long-term memory systems, and advanced reasoning capabilities with metacognitive monitoring.
MEGAMIND uses a combination of sparse attention patterns, memory retrieval systems, and hierarchical summarization to process information beyond fixed context limits. Important information is stored in episodic memory and retrieved as needed.
MEGAMIND is currently in active development. We're conducting internal testing and safety evaluations. Developer access will be available in phases - sign up for updates to be notified when access opens.
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