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
The action is in response to claims dated 1/19/2023
Claims pending in the case: 1-22
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.
Claim(s) 1-22 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 pre-AIA the applicant regards as the invention.
Claim(s) 1 and 12 in the relevant part read: “wherein the one or more abstract pipelines comprise similar specifications of the abstract data types and a Directed Acyclic Graph (DAG)” The term “similar” is a relative term which renders the claim indefinite. The term “similar” is not defined by the claim, the specification does not provide a standard for ascertaining the requisite degree, and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention.
Claim(s) 1 and 12 in the relevant part read: “an execution plan by converting the one or more abstract pipelines from the configured one or more packages into one or more concrete pipelines”. Based on the claim language, it is unclear what is being referred to as “concrete pipelines”. It is also unclear what this conversion process involves. As such, a person of reasonable skill in the art would not be apprised of the metes and bounds of the invention.
For the purpose of examination, the limitation is interpreted as generating a workflow.
All claims dependent on this/these claim(s) are also rejected under 35 U.S.C. 112(b) due to the virtue of their respective direct and indirect dependencies.
Claim(s) 10 in the relevant part read: “wherein the orchestrator comprises three components”. Based on the claim language following this limitation, it is unclear what these distinct three components are. As such, a person of reasonable skill in the art would not be apprised of the metes and bounds of the invention.
For the purpose of examination, the three components are interpreted as a server, a session manager and a scheduler. Applicant is requested to clarify the limitation.
Claim Rejections - 35 USC § 103
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 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim(s) 1-9, 12-20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Minkin (US 20180165604) in view of Parameswaran (US 20200184376).
Regarding Claim1, Minkin teaches, A method for managing reproducible machine learning workflows (Minkin: [8]: generating workflows), the method comprising:
receiving, by a processor associated with a workflow management system, an input comprising abstract data sets (Minkin: [32, 159, 265]: data sets), wherein each abstract data set comprises an identifier and a specification as a one-layer set of key-value pairs (Minkin: [247, 251, 256-257]: may use key value requirement) ;
transforming, by the processor, the received abstract data sets into one or more abstract data types, wherein each abstract data type comprises a set of parameters specified as key-value pairs of variable names and associated abstract data types along with a map of input abstract data sets and output abstract data sets (Minkin: [224, 247, 258-264, 268]: transform raw data; source data to schema metric set construction – mapping of data sets from key values) ;
generating, by the processor, one or more abstract pipelines using the one or more abstract data types, wherein the one or more abstract pipelines are machine learning workflows (Minkin: [8, 270-272, 281]: AC (application composer)generate workflow and sub-workflow), and wherein the one or more abstract pipelines comprise similar specifications of the abstract data types and a Directed Acyclic Graph (Minkin: [156]: a directed acyclic graph view of a machine learning workflow; [8]: “workflows for metalearning, a subfield of machine learning where automatic learning algorithms are applied on meta-data”);
implementing, by the processor, the one or more abstract pipelines as one or more packages, wherein the one or more packages comprise pre-defined names and are imported systematically (Minkin: Fig. 9B, [27-28, 189, 193]: packaged workflow; [251-252]: label with domain relationship);
configuring, by the processor, the one or more packages as a map of key- value pairs comprising keys, wherein the keys in the configuration are a superset of keys in the set of parameters (Minkin: [247, 250, 324]: may use key value requirement; [158, 222]: configuration involve set of parameters);
storing, by the processor, the configured one or more packages in a database, wherein the one or more packages are stored upon checking in a repository and storing locally as files; generating, by the processor, an execution plan by converting the one or more abstract pipelines from the configured one or more packages into one or more concrete pipelines (Minkin: [211, 324]: saved workflow for use (concrete pipeline));
transmitting, by the processor, the execution plan to an orchestrator to merge individual one or more concrete pipelines into a dataset dependency graph, and to mark one or more tasks in the dataset dependency graph (Minkin: [204-205, 217, 219-220, 251]: [205]: dependency of tasks in a flow; [251]: “AC's question graphs (QGs—FIGS. 16A, 16B) are encoded in a semantic map as a set of entity relationships”);
executing, by the processor, the one or more tasks as a cluster, by calling an appropriate command (Minkin: [217-219]: tack cluster with hierarchy; [205, 281, 324]: execution module);
obtaining, by the processor, one or more predictions from different models or same model with different hyperparameters to provide a meta construct, upon executing the one or more tasks as the cluster (Minkin: [126, 222, 225]: [222]: “machine learning meta-learning architecture”- models with different hyperparameters); and
outputting, by the processor, a modified DAG comprising the one or more tasks mapped to the configuration, wherein the mapped one or more tasks are combined together using a combiner function (Minkin: [222]: “machine learning meta-learning architecture”- combined tasks; [227]: “At each step in the AC goal and task workflow hierarchy a specialized agent can be constructed that is responsible for combining workflow recommendations arising from the expert system and machine learning system”);
Although it is obvious that a modified DAG would be outputted, Minkin does not specifically teach, a modified DAG;
Parameswaran teaches, Modified DAG (Parameswaran: Fig. 2 [86, 90, 113]: DAG may be employed in the workflow; [93-103]: workflow lifecycle with DAG optimization creating a plan);
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Minkin and Parmeswaran because the combination would enable would enable optimizing DAG to generate a modified workflow. One of ordinary skill in the art would have been motivated to combine the teachings because the combination improves efficiency of modifying parameters and updating workflows (See Parameswaran [2]).
Regarding claim 2, Minkin and Parmeswaran teach the invention as claimed in claim 1 above and, wherein the abstract data sets, the one or more abstract pipelines comprises the specification, and wherein the one or more concrete pipelines comprise implementation. (Minkin: [121]: model based on a specific goal) (Parmeswaran: [59-60]: receive specification for workflow and execute the modified workflow).
Regarding claim 3, Minkin and Parmeswaran teach the invention as claimed in claim 1 above and, wherein the configuration specifies a mapping of each one or more abstract data types to implementation of the one or more abstract pipelines (Minkin: [122, 125, 133, 136]: mapping based on data type) (Parmeswaran: [120, 125-131]: map according to data features (types)).
Regarding claim 4, Minkin and Parmeswaran teach the invention as claimed in claim 1 above and, wherein, each implementation of the one or more abstract pipelines as one or more packages inherits a base class to provide inherent access to the set of parameters and the abstract data sets and handle storage of the abstract data sets (Parmeswaran: [151]: a base “class that implements methods fit and score”).
Regarding claim 5, Minkin and Parmeswaran teach the invention as claimed in claim 1 above and, wherein each transformation of the received abstract data sets into the one or more abstract data types comprises metadata, wherein the metadata comprises at least one of, a Uniform Resource Identifier (URI), an abstract transform name, an affinity, versions, and schemas for the abstract data sets (Minkin: [94]: “processes performed after ingestion of data and metadata that acts to prepare sources for mapping”; [103, 115]: schemas used in build).
Regarding claim 6, Minkin and Parmeswaran teach the invention as claimed in claim 1 above and, wherein the one or more abstract pipelines are an extension of the transformation (Parmeswaran: [60]: modify workflow -extension of the transformation).
Regarding claim 7, Minkin and Parmeswaran teach the invention as claimed in claim 1 above and, wherein the DAG comprises nodes, wherein the nodes are the transformation specified by a name mapped to the one or more abstract data types (Parmeswaran: [73-74]: Nodes in DAG representing machine learning workflow).
Regarding claim 8, Minkin and Parmeswaran teach the invention as claimed in claim 1 above and, wherein the meta construct comprises at least one of a workflow specification, a mapper function, and the combiner function, wherein the mapper function is to generate a list of configurations for the workflow specification, and the combiner function comprises receiving a list of runs for a list of configurations and generating an output (Minkin [8, 28-33, 44, 115, 233-234]: using mapping and combining to generate optimization models; [197]: progressive modeling of iteration – list of runs; [239]: utility function for optimization).
Regarding claim 9, Minkin and Parmeswaran teach the invention as claimed in claim 1 above and, wherein the one or more concrete pipelines comprises a dataset dependency map which comprises a dependency of concrete data types to concrete datasets of parent concrete data types, and a task definition map with information of concrete data types (Minkin [233-234]: dependency map; task modeled by associating meta-features – task definition).
Regarding Claim(s) 12-20, this/these claim(s) is/are similar in scope as claim(s) 1-9 respectively. Therefore, this/these claim(s) is/are rejected under the same rationale.
Claim(s) 10, 21 is/are rejected under 35 U.S.C. 103 as being unpatentable over Minkin (US 20180165604) and Parameswaran (US 20200184376) in view of Wang (US 20230237367).
Regarding claim 10, Minkin and Parmeswaran teach the invention as claimed in claim 1 above and, wherein the orchestrator comprises three components, which comprises
a server to actively listen to commands from other components and a client (Minkin: [180, 218]: server client communication), to maintain a queue for submitted the one or more abstract pipelines, completed tasks, to maintain a list of machines in the clusters (Minkin: [84]: key phases with specific tasks in a workflow (machines)), a session manager to maintain the dependency graph and task information, … connect with spawners that run the tasks (Minkin.: [33, 134, 138, 150-152, 270]: orchestrator to plan and execute tasks; [84]: “one or more non-linear sequences of tasks that can be mapped to key distinct phases in a given workflow”- dependency graph; [205, 217, 219]: run tasks);
Minkin and Parmeswaran do not specifically teach, a scheduler;
Wang teaches,
a scheduler to connect with spawners that run the tasks (Wang: Figs. 2A-B, [37, 49, 50, 52, 90]: maintain a portfolio with candidate configurations for a list of tasks; run tasks by scheduling tasks with specific configurations);
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Minkin, Parmeswaran and Wang because the combination would enable would enable using a scheduler in the implementation of a pipeline. One of ordinary skill in the art would have been motivated to combine the teachings because the combination streamlines the process of determining a suitable model and executing tasks (see Wang [2]).
Regarding Claim(s) 21, this/these claim(s) is/are similar in scope as claim(s) 10. Therefore, this/these claim(s) is/are rejected under the same rationale.
Claim(s) 11, 22 is/are rejected under 35 U.S.C. 103 as being unpatentable over Minkin (US 20180165604) and Parameswaran (US 20200184376) in view of LaRock (US 20180293098).
Regarding claim 11, Minkin and Parmeswaran teach the invention as claimed in claim 1 above and,
LaRock further teaches, wherein upon executing the one or more tasks as the cluster, the orchestrator transmits task information to a spawner, wherein the spawner receives task information from the orchestrator and calls an executor depending on the task information, wherein the executor executes and saves the output and signals completion to the spawner, and wherein the spawner signals back to the orchestrator (LaRock: [31, 36-37, 42]: executing tasks in registry; task information used to update, schedule and execute dependent tasks; system may execute a task and the information is used for task management);
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Minkin, Parmeswaran and LaRock because the combination would enable would enable using task information to manage and execute multiple tasks. One of ordinary skill in the art would have been motivated to combine the teachings because the combination provides a more efficient and accurate way of executing computing tasks (see Wang [2]).
Regarding Claim(s) 22, this/these claim(s) is/are similar in scope as claim(s) 11. Therefore, this/these claim(s) is/are rejected under the same rationale.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure in the attached 892.
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/Mandrita Brahmachari/Primary Examiner, Art Unit 2144