Show HN: Core-1 – A distributed C++ AGI framework for trillion-parameter scale (github.com)

TitanCore has announced the release of Core-1, a groundbreaking distributed C++ AGI framework designed to operate at a staggering trillion-parameter scale. This framework integrates a sophisticated 120-layer Mixture-of-Experts Transformer with a robust cognitive architecture encompassing persistent memory, structured reasoning, and continuous online learning. It employs cutting-edge technologies such as FlashAttention v2 and Monte Carlo Tree Search (MCTS), allowing it to execute complex cognitive processes through a complete loop of perceiving, remembering, reasoning, planning, acting, and learning, all within multi-node GPU clusters. The significance of Core-1 for the AI/ML community lies in its comprehensive approach to AGI, capable of real-time weight updates and adaptive meta-learning, which enables rapid task adaptation with minimal examples. With features like Elastic Weight Consolidation to preserve knowledge during learning and a built-in safety framework, TitanCore addresses crucial scalability and safety concerns in AGI systems. The framework is designed to leverage advanced hardware setups with NVIDIA GPUs, making it a powerful tool for researchers eager to explore high-performance AGI capabilities. Core-1 is set for public release in February 2026, marking a significant milestone in the ongoing evolution of artificial general intelligence.