DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1-20 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 1, line 4, the claim recites the limitations "the memory" and “the event”. There is insufficient antecedent basis for this limitation in the claim. Additionally, it is not clear what the term “event” refers to. Further down the claim, limitations drawn to “decreased in importance” render the claim indefinite since these terms appear to be relative terms of degree. The importance is being decreased from what level of importance and how is the importance being determined or what is it a measure of? How is the memory being determined to be important and in what sense?
Claim 2, the claimed “a storage subsystem” and “a generative artificial intelligence system” adds ambiguity since it is not clear if these are new elements or if the claim is referring to those elements in claim 1. Additionally, the claimed “greater importance” introduces the same deficiencies as those mentioned in claim 1 as being a relative term of degree that is not clear.
Claim 4, the claim recites the act of “compressing the compressed memory” which is logically impossible. A method as claimed cannot compress and already compressed memory. As such, this renders the claim indefinite. Additionally, the limitation drawn to “quantizing a vector” since its not clear what this step accomplishes or how it leads to compression.
Claims 5 and 8, limitations drawn to “decreased in importance” render the claim indefinite since these terms appear to be relative terms of degree. The importance is being decreased from what level of importance and how is the importance being determined or what is it a measure of? How is the memory being determined to be important and in what sense? Additionally, the claimed relevancy tag renders the claim indefinite since it is unclear what the claimed relevancy is in relation to.
Claims 3, 6, 7, 9 are rejected as having the same deficiencies as their parent claims.
Claims 10-20 are similarly rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor regards as the invention.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to abstract ideas without significantly more. The claim(s) recite methods of organizing human activity (evaluating the importance or relevance of an event, tagging for retention, as well as organizing, archiving, and data management), mental processes (evaluating decreased importance and identifying context), mathematical concepts (quantizing a vector, numeric compression). This judicial exception is not integrated into a practical application because the claim elements simply recite generic components (such as storage subsystem, physical processors, physical memory, generative artificial intelligence system) performing basic, routine computational functions of storing, evaluating, compressing, and retrieving data. The claims fail to improve the functioning of a system and recite only the desired result of generic data compression to save storage space. The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements consist solely of well understood, routine, and conventional computer activities in data archiving and cache management.
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claims 1-20 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Doggett et al. [US 2024/0394965].
Claim 1, Doggett et al. teaches a computer-implemented method [par. 0007, 0018, 0079-0080] comprising: storing, within a storage subsystem [114, 116, par. 0020, 0023-0034, 0046, 0052] of a generative artificial intelligence system, structured memory representation comprising vectorized and semantic event data [vectorized data] , wherein the memory of the event comprises a summary of the event and context associated with the event [par. 0041-0048, 0078]; determining that the memory has decreased in importance for use in responding to prompts provided to the generative artificial intelligence system [determining that a memory decreases in importance/retention for use in prompt generation over time via a forgetting/decay model where retention level R and retrieval score decrease as elapsed time increases without access, par. 0049-0051, 0054-0055, 0082]; in response to the determination that the memory has decreased in importance, compressing the memory such that the compressed memory uses less storage space in the storage subsystem than an uncompressed memory of the event [converting older, uncompressed interaction messages/history into condensed/compressed summary, such as initial summary 324 and updated summary 326, as events age out, to manage prompt context windows and storage efficiency, par. 0037, 0057-0061, 0078] ; replacing the uncompressed memory with the compressed memory in the storage subsystem [discloses updating memory records where raw, detailed conversational logs are condensed periodically or continually into an updated summary (summary 326) that replaces the older individual message history in active memory representations, par. 0059-0061, 0078] ; and using the compressed memory to respond to a prompt provided to the generative artificial intelligence system [discloses injecting the condensed summary 326 along with recent messages into a prompt 328 input to large language model 200 to generate response 236, par. 0057, 0061, 0065, 0084-0085, claim 13].
Claim 2, Doggett et al. discloses the method of claim 1, further comprising: storing, within a storage subsystem of a generative artificial intelligence system, a memory of an additional event, wherein: the memory of the additional event comprises context indicating that the memory is a core memory; and the memory of the event comprises a non-core memory; and the memory of the additional event has greater importance than the memory of the event and takes up more storage space in the storage subsystem than the memory of the event [designating certain memories as core memories having high stability S that effectively disables forgetting/decay, while other memories created from ongoing user interactions are assigned lower stability S and allowed to decay sooner, non-core memories, par. 0051. Because non-core memories are subjected to summarization and pruning, par. 0059-0060, while core memories are preserved without decay, the core memories take up more storage space over time than the condensed non core memory]
Claim 3, Doggett et al. discloses the method of claim 1, wherein: the event comprises a security event; and storing the memory of the event comprises evaluating the event by a plurality of artificial intelligence security operations center agents to identify the context and create the summary [tracking and mapping access permissions, access controls, and authorized users as monitored events, par. 0078. Multiple instances of management engines and retrieval engines execute across distributed nodes, par. 0019. Doggett discloses using multiple specialized LLM personas and multi agent chain of thought prompting to evaluate input messages/events for truthfulness and policy adherence before generating outputs, par. 0067. Unauthorized access is an anomalous/security events, and the distributed multi persona verification agents functionally evaluate the event to identify context and synthesize the memory/summary.]
Claim 4, Doggett et al. discloses the method of claim 1, wherein compressing the compressed memory comprises quantizing a vector that stores the summary of the event [par. 0039, 0047].
Claim 5, Doggett et al. discloses the method of claim 1, wherein determining that the memory has decreased in importance comprises evaluating at least one of: a time since the memory was last accessed, a time since the memory was created, or a relevancy tag associated with the memory [par. 0048-0051, 0053-0055, 0082].
Claim 6, Doggett et al. discloses the method of claim 1, wherein the memory is a shared memory accessible by a plurality of artificial intelligence agents, each agent having independent contextual memory [par. 0019, 0040-0041, 0052, 0064-0067].
Claim 7, Doggett et al. discloses the method of claim 1, wherein using the compressed memory to respond to a prompt comprises injecting the compressed memory into a context window of a generative artificial intelligence model [constructing prompt 328 by injecting the memory summary 326 into the prompt input provided to LLM 200, par. 0057, 0061, 0065, 0084].
Claim 8, Doggett et al. discloses the method of claim 1, wherein compressing the memory comprises applying a dynamic compression factor based on at least one of: available storage space, relevancy of the memory, or a predefined compression floor [see par. 0049-0050, 0054-0055, 0055].
Claim 9, Doggett et al. discloses the method of claim 1, wherein replacing the uncompressed memory with the compressed memory comprises maintaining a reference to an original context of the memory to enable navigation and searching of the memory [when memories and summaries are formed, metadata is maintained linking each memory/summary to unique identifiers, character ID, user ID, original conversation IDs, and knowledge source references par. 0044-0046, 0048, 0078].
Claims 10-20 are rejected using the same rationale as Claims 1-9.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
LEE et al. [US 2026/0065048]; Self-Speculative Decoding Using Forecasted Embeddings in Autoregressive Generative Artificial Intelligence Models [see Abstract].
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/MIDYS ROJAS/ Primary Examiner, Art Unit 2133
