8962
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 .
DETAILED ACTION
This action is in response to Applicant's Election (January 09,2026), in response to the Election/Restriction requirement (filed on 11/20/2025).
Claims 1-9 and 14-20 are pending.
This action is response to the application filed on January 09, 2026.
This application claims a benefit of priority under 35 U.S.C. § 119(e) from U.S. Provisional Application No. 63/326,351, filed April 1, 2022, entitled "ZERO CODE STREAM PROCESSING ENGINE FOR MACHINE INTERFACE," which is fully incorporated by reference herein for all purposes
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitation(s) is/are: “…. ML prediction service module…. “ and “ …. business process management (BPM) broker …. “, limitation fails to recite sufficiently definite structure and that the presumption against means-plus function claiming is rebutted." Id. at 1351, 115 USPQ2d at 1113. In support, the Federal Circuit determined that "the word 'module' does not provide any indication of structure because it sets forth for providing the same specified function as if the term ‘means’ had been used." Id. at 1350–51, 115 USPQ2d at 1112. in claims 1 and 14 (and in dependent claims 5-6, 9 and 17).
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof. (in applicant’s specification, [0005] A system is provided for zero code stream processing orchestration, the system including a processor, a non-transitory computer-readable medium, and instructions stored on the non-transitory computer-readable medium and translatable by the processor for providing a plurality of runtime services, including: a connector runtime configured for deploying a source connector for connecting to disparate source endpoints and streaming event streams from the disparate source endpoints, a stream processor configured for orchestrating microservices, including a machine learning (ML) service, operating on messages in the event streams, an artificial intelligence (AI) runtime configured for providing a distributed parallel processing microservice service bus and runtime that hosts a ML prediction service module, wherein the ML prediction service module is trained to make a prediction based at least in part on the messages from the stream processor, and a business process management (BPM) broker that operates as a managed dispatcher for automatically initiating BPM workflows based on the prediction).
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
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 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)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claims 1-9 and 14-20 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Layman et al (US 20170228253 A1).
With respect to claims 1 and 14, Layman et al teaches
connector runtime configured for deploying a source connector for connecting to disparate source endpoints and streaming event streams from the disparate source endpoints ([0099] FIG. 1, IoT platform 100. IoT platform 100 includes data sources 102, input connectors 104, stream container(s) 106, orchestration system 112, output connectors 122 and application(s) 123. Orchestration 112, [0100] FIG. 2, stream processing framework 200 used in the platform shown in FIG. 1, Framework 200 includes data sources 102, input pipeline 204, stream container 106, rich contextual data store 110 and output pipeline 218.);
a stream processor configured for orchestrating microservices ([0099] FIG. 1, orchestration system 112, output connectors 122 and application(s) 123. Orchestration 112,), including a machine learning (ML) service([0029] machine learning), operating on messages in the event streams ([0029] from real-time data streams. [0116] Stream container 106 allows for parallelization of spouts and bolts using different tuple grouping strategies to pass event streams);
an artificial intelligence (Al) runtime ([0075] artificial intelligence) configured for providing a distributed parallel processing microservice service bus and runtime that hosts a ML prediction service module, wherein the ML prediction service module is trained to make a prediction based at least in part on the messages from the stream processor ([0116] Stream container 106 allows for parallelization of spouts using different tuple grouping strategies to pass event streams. [0093] machine learning deliver intelligent decisions in a predictive manner. [0178] for handling cases predictably in business environments); and
a business process management (BPM) broker that operates as a managed dispatcher for automatically initiating BPM workflows based on the prediction ([0107] Batch processing framework operating in container(s) 108 generates business intelligence using OnLine Analytical Processing. [0093] machine learning deliver intelligent decisions in a predictive manner. [0178] for handling cases predictably in business environments).
With respect to claims 2-4 and 15-16, Layman et al teaches disparate sources comprise a data pipeline, an Internet-of- Things platform ([0004] model for Internet of Things (IoT), providing a straightforward, intuitive, scalable and easily codable workflow for IoT. [0007] “Internet of Things” (IoT). IoT is about a pervasive presence in the environment of a variety of things/objects).
With respect to claims 5 and 17, Layman et al teaches Al knowledge base for training and predicting state data of the ML prediction service modules ([0142] FIG. 3 state machine 300 implementing an automated multi-step progression of interaction with an entity).
With respect to claims 6 and 18, Layman et al teaches service runtime for handling lifecycle and execution of a service module [0142] FIG. 3 state machine 300 implementing an automated multi-step progression of interaction with an entity).
With respect to claims 7 and 19, Layman et al teaches deploying a sink connector for a sink endpoint ([0122] output pipeline 218 is transmitted concurrently to a SQL data store and NoSQL data store like rich contextual data store 110. Output pipeline 218 can also be hosted by Kafka, which acts a sink for the output of the jobs).
With respect to claims 8 and 20, Layman et al teaches event streams are initiated by machines ([0014] workflow state machine that handles machine-generated events).
With respect to claim 9, Layman et al teaches disparate source endpoints, the connector runtime, the stream processor, the Al runtime, the BPM broker, and the BPM workflows are distributed across different computing environments ([0099] FIG. 1 includes exemplary IoT platform 100. IoT platform 100 includes data sources 102, input connectors 104, stream container(s) 106, orchestration system 112, output connectors 122 and application(s) 123. The rich contextual data store 110 includes various storage nodes C1-C3. Orchestration 112).
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ISAAC M WOO whose telephone number is (571)272-4043. The examiner can normally be reached 9:00 to 5:00.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Tony Mahmoudi can be reached on 571-272-4078. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/ISAAC M WOO/Primary Examiner, Art Unit 2163