Persistent cognitive machine with multimodal processing capabilities
A system and method for implementing persistent cognitive computation through geometric representation of thought in a dynamic latent manifold. The system encodes inputs into a curved space characterized by time-evolving metric tensors, compression pressure fields derived from Ricci curvature, and goal potential fields that shape attention flow. Cognition occurs through geodesic traversal of this manifold, with attention following paths that minimize cognitive action while balancing semantic density and goal relevance. A Cognitive Dynamics Engine maintains manifold geometry, computing optimal trajectories and managing thought bundle operations including consolidation, expansion, and higher-order abstraction. During idle periods, autonomous dreaming processes reorganize the manifold through perturbation, recombination, and topological surgery. This architecture enables persistent memory through geometric encoding, where frequently accessed concepts develop high-curvature regions and cognitive shortcuts emerge from usage patterns, transforming artificial intelligence from stateless computation to structured motion through shaped memory space.
1 . A computer system comprising a hardware memory, wherein the computer system is configured to execute software instructions stored on nontransitory machine-readable storage media that:
maintain a latent manifold as a geometric substrate incorporating multiple dimensional representations for heterogeneous data modalities, wherein local curvature reflects semantic density within and across modalities;
encode inputs from multiple modalities into a unified geometric space while preserving modality-specific properties through dimensional constraints;
generate compression pressure fields that account for information density patterns across different modalities;
enable navigation across modal boundaries through geometric pathways that preserve semantic relationships during dimensional transitions;
synthesize unified representations spanning multiple modalities through geometric recombination of semantically aligned structures; and
update the manifold geometry to reinforce multimodal integrations and cross-modal pathways based on traversal patterns.
2 . The computer system of claim 1 , wherein the compression pressure fields comprise modality-specific pressure patterns.
3 . The computer system of claim 1 , wherein the software instructions further:
execute autonomous reorganization of the latent manifold during idle periods, including perturbation of existing structures, synthesis of new connections between disparate regions, and removal of unused or redundant structures.
4 . The computer system of claim 1 , wherein the software instructions further:
maintain a plurality of bidirectional attention fields within the latent manifold that support both forward exploration toward goals and reverse traversal along previously computed paths, enabling backtracking and path revision.
5 . The computer system of claim 1 , wherein the software instructions further:
establish a plurality of goal potential fields that create attractive forces within the latent manifold, guiding path computation toward semantically relevant regions for achieving specific objectives.
6 . The computer system of claim 1 , wherein the software instructions further:
implement hierarchical organization with multiple nested latent manifolds operating at different levels of abstraction, wherein paths can traverse between abstraction levels through geometric bridges.
7 . A method for a persistent cognitive computation with multimodal capabilities, comprising the steps of:
maintain a latent manifold as a geometric substrate incorporating multiple dimensional representations for heterogeneous data modalities, wherein local curvature reflects semantic density within and across modalities;
encode inputs from multiple modalities into a unified geometric space while preserving modality-specific properties through dimensional constraints;
generate compression pressure fields that account for information density patterns across different modalities;
enable navigation across modal boundaries through geometric pathways that preserve semantic relationships during dimensional transitions;
synthesize unified representations spanning multiple modalities through geometric recombination of semantically aligned structures; and
update the manifold geometry to reinforce multimodal integrations and cross-modal pathways based on traversal patterns.
8 . The method of claim 7 , further comprising the step:
computing modality-aware compression pressure fields derived from local curvature.
9 . The method of 7 , further comprising the step:
executing autonomous reorganization of the latent manifold during idle periods, including perturbation of existing structures, synthesis of new connections between disparate regions, and removal of unused or redundant structures.
10 . The method of claim 7 , further comprising the step:
maintaining a plurality of bidirectional attention fields within the latent manifold that support both forward exploration toward goals and reverse traversal along previously computed paths, enabling backtracking and path revision.
11 . The method of claim 7 , further comprising the step:
establishing a plurality of goal potential fields that create attractive forces within the latent manifold, guiding path computation toward semantically relevant regions for achieving specific objectives.
12 . The method of claim 7 , further comprising the step:
implementing hierarchical organization with multiple nested latent manifolds operating at different levels of abstraction, wherein paths can traverse between abstraction levels through geometric.