SingularityNET Launches Unified AI Framework Based on Hyperon and PRIMUS

In accordance with Biji Network, SingularityNET has released a unified artificial intelligence framework based on Hyperon and PRIMUS. The framework integrates symbolic reasoning and neural learning through a shared Atomspace memory to support broader intelligent goals. PRIMUS cognitive circuits guide goal and pattern discovery, while integrated tools handle tasks within a unified memory structure. SingularityNET's Chief Scientist Ben Goertzel recently published a detailed whitepaper introducing Hyperon and PRIMUS as an integrated architecture aimed at advancing current AI systems toward artificial general intelligence (AGI) and eventually beneficial superintelligence. Unlike many AI frameworks built from disconnected modules, Hyperon uses a unified approach to process perception, memory, and learning. All system content, including goals, information, processes, and neural patterns, is stored in a structure called 'Atomspace.' This setup allows symbolic and neural systems to interact directly on shared memory without external data calls. MORK, an expandable version of Atomspace, supports fast, lock-free access and uses efficient formats like PathMap and Merkle-DAG to manage data. MORK also integrates neural elements through QuantiMORK, embedding multi-resolution graphs directly into memory, eliminating delays typically encountered when switching between symbolic and neural processing.