Granted Patent B1

US 12,387,050 · App. 19/051,193 · Granted Aug 12, 2025

Inventors: Brian Galvin (Silverdale, WA); Alan McCord (Forney, TX)

Assignee: ATOMBEAM TECHNOLOGIES INC.

G06F40/30G06F16/3325G06F16/3329

Abstract

Claims (52)

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:

receive a prompt from a user;

process the prompt into a plurality of corresponding thoughts using a first large language model;

route both the prompt and the plurality of thoughts through a second large language model that has fewer parameters than the first large language model;

associate each corresponding thought in the plurality of corresponding thoughts to a portion of the prompt;

cache each associated corresponding thought, wherein a plurality of associated corresponding thoughts may be retrieved from a thought cache when the portion of the prompt they correspond to is present in a future prompt; and

generate a response to the prompt by processing the plurality of thoughts and the prompt through the second large language model.

2. The computer system of claim 1 , wherein the computer system is further configured to execute software instructions stored on nontransitory machine-readable storage media that:

analyze the prompt using a prompt analyzer to determine key concepts and requirements;

query the thought cache to determine if similar thoughts exist for the determined key concepts; and

synthesize new thoughts when similar thoughts exist but do not fully address the prompt requirements.

3. The computer system of claim 1 , wherein the thought cache comprises at least a local cache stored on an edge device and a global cache stored in a cloud environment, wherein the global cache is accessible by a plurality of edge devices.

4. The computer system of claim 3 , wherein the global cache is organized into specialized domains, and thoughts are categorized and stored according to their relevant domain.

5. The computer system of claim 1 , wherein caching each associated corresponding thought comprises:

evaluating relevance of the thought to the portion of the prompt;

assigning metadata tags based on the evaluation;

storing the thought with vector embeddings for similarity searching; and

indexing the thought for retrieval.

6. The computer system of claim 1 , wherein caching each associated corresponding thought comprises:

storing each associated corresponding thought in a short-term memory as explicit reasoning text;

progressively compressing a plurality of older associated corresponding thoughts into consolidated representations; and

storing a plurality of compressed older associated corresponding thoughts in a long-term memory.

7. The computer system of claim 1 , wherein the computer system is further configured to execute software instructions stored on nontransitory machine-readable storage media that:

maintain a shared thought cache accessible by multiple AI agents;

enable thought transfer between specialized reasoning modules; and

coordinate collaborative reasoning across multiple model instances.

8. A method for encrypted data compression with a hardware management layer, comprising the steps of:

receiving a prompt from a user;

processing the prompt into a plurality of corresponding thoughts using a first large language model;

routing both the prompt and the plurality of thoughts through a second large language model that has fewer parameters than the first large language model;

associating each corresponding thought in the plurality of corresponding thoughts to a portion of the prompt;

caching each associated corresponding thought, wherein a plurality of associated corresponding thoughts may be retrieved from a thought cache when the portion of the prompt they correspond to is present in a future prompt; and

generating a response to the prompt by processing the plurality of thoughts and the prompt through the second large language model.

9. The method of claim 8 , further comprising the steps of:

analyzing the prompt using a prompt analyzer to determine key concepts and requirements;

querying the thought cache to determine if similar thoughts exist for the determined key concepts; and

synthesizing new thoughts when similar thoughts exist but do not fully address the prompt requirements.

10. The method of claim 8 , wherein the thought cache comprises at least a local cache stored on an edge device and a global cache stored in a cloud environment, wherein the global cache is accessible by a plurality of edge devices.

11. The method of claim 10 , wherein the global cache is organized into specialized domains, and thoughts are categorized and stored according to their relevant domain.

12. The method of claim 8 , wherein caching each associated corresponding thought comprises:

evaluating relevance of the thought to the portion of the prompt;

assigning metadata tags based on the evaluation;

storing the thought with vector embeddings for similarity searching; and

indexing the thought for retrieval.

13. The method of claim 8 , wherein caching each associated corresponding thought comprises:

storing each associated corresponding thought in a short-term memory as explicit reasoning text;

progressively compressing a plurality of older associated corresponding thoughts into consolidated representations; and

storing a plurality of compressed older associated corresponding thoughts in a long-term memory.

14. The method of claim 8 , further comprising the steps of:

maintaining a shared thought cache accessible by multiple AI agents;

enabling thought transfer between specialized reasoning modules; and

coordinating collaborative reasoning across multiple model instances.

Assignments (1)

References Cited (29)

Cited By (2)

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