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
Claims 1-52 are pending and examined. This action is a non-final office action.
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 1-52 are rejected under 35 USC 101 as directed at an abstract idea without significantly more.
Here the claims are directed to a system which is a statutory category of invention. Step 1 Yes.
The claims under the broadest reasonable interpretation cover performance of the limitation as
A mental process that can be performed in the human mind.
Here independent claim 1 is analyzed.
The abstract elements include;
… one or more operatively coupled …; and b. … operated by the … and configured to engage a human operator in accordance with a predetermined process configuration toward an established requirement based at least in part upon one or more specific facts; wherein … is configured to allow the human operator to select and interactively engage one or more synthetic operators operated by the … to proceed through the predetermined process configuration, and to return a result to the human operator selected to at least partially satisfy the established requirement; and wherein each of the one or more synthetic operators is informed by a …. informed at least in part by historical actions of a particular actual human operator.
Broadly speaking the applicant is claiming mental processes of using the computer for human usage. The recitation of generic elements does not necessarily preclude the claims from being directed to an abstract idea (Step 2A prong 1) Yes the claims recite an abstract idea
The judicial exception is not integrated into a practical application. In particular the claims
The technical elements include a computer system, network, interface and convolutional neural network which are generic in this field of technology.
These are generic computing elements which are applied. The additional elements when considered separately and as an ordered combination do not integrate the abstract idea into a practical application because they do not impose meaningful limits on practicing the abstract idea and are at a high level of generality. Therefore claim 1 is directed to an abstract idea without a practical application. Step 2A prong 2 No the additional elements are not integrated into a practical application.
In regards to additional elements, when considered separately or in ordered combination they do not add significantly more known as inventive concept to the exception. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. Applicant dependent claims of which there are 51 may provide inventive concept if rolled up. The invention itself is directed to machine learning so if applicant were to provide an improvement in the machine learning, then this may satisfy the practical application or inventive concept elements.
Step 2B the claims as provided do not amount to significantly more.
The dependent claim 49 rolled up for example may be enough to create a practical application.
Claims 2-52 are rejected by virtue of dependency on rejected claim 1.
Claim Rejections - 35 USC § 103
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) 1-42 and 50-52 is/are rejected under 35 U.S.C. 103 as being unpatentable over US patent Publication to Acuna Marrero 20220383073 in view of US patent publication 2020/0090001 to Zargahi
As per claim 1, Acuna Marrero discloses;
a. a computing system comprising one or more operatively coupled computing resources;
and b. a user interface operated by the computing system and
Acuna(0022)
configured to engage a human operator in accordance with a predetermined
Acuna(0095) process configuration toward an established requirement based at least in part upon one or more specific facts; Acuna (0021 synthetic data generation)
and wherein each of the one or more synthetic operators is informed by a convolutional neural network informed at least in part by historical actions of a particular actual human operator.
A(0026) In regards to Human type operations, Zargahi teaches; wherein the user interface is configured to allow the human operator to select and interactively engage one or more synthetic operators operated by the computing system to proceed through the (0042, manual intervention)
predetermined process configuration, and to return a result to the human operator selected to at least partially satisfy the established requirement;
(0042, manual intervention, at least partially is a small amount possibly, “established? Requirement could be a lot of things) It would therefore have been obvious to one of ordinary skill in the art before the effective filing date of the invention to combine the AI teachings of Acuna with the manual intervention teachings of Zargahi for the motivation of properly training machine learning models … to achieve facial recognition. (0002)
As per claim 2, Acuna discloses; The system of claim 1, wherein the one or more specific facts are selected from the group consisting of: (only one)
textual information, numeric data, audio information, video information, emotional state information, analog chaos input selection, activity perturbance selection, curiosity selection, memory configuration, learning model, filtration configuration, and encryption configuration. Acuna(0092, machine learning)
As per claim 3 Acuna discloses; The system of claim 2, wherein the one or more specific facts comprise textual information pertaining to specific background information from historical storage.
Acuna(labeled source domain, 0019)
As per claim 4, Acuna does not explicitly disclose what Zargahi teaches; The system of claim 2, wherein the one or more specific facts comprise textual information pertaining to an actual operator.
Zargahi (0043, 0047, text box, one or more could be one)
The motivation would be similar to that provided for claim 1.
As per claim 5, Acuna does not explicitly disclose what Zargahi teaches;
The system of claim 2, wherein the one or more specific facts comprise textual information pertaining to a synthetic operator. Zargahi(0049)
The motivation would be similar to that provided for claim 1.
As per claim 6, Acuna does not explicitly disclose what Zargahi teaches
The system of claim 1, wherein the specific facts comprise a predetermined profile of specific facts developed as an initiation module for a specific synthetic operator profile.
Zargahi (0074)
The motivation would be similar to that provided for claim 1.
As per claim 7 Acuna does not explicitly disclose what Zargahi teaches
The system of claim 1, wherein the one or more operatively coupled computing resources comprises a local computing resource.
Z(0132, LAN)
The motivation would be similar to that provided for claim 1.
As per claim 8, Acuna does not explicitly disclose what Zargahi teaches
The system of claim 7, wherein the local computing resource is selected from the group consisting of: a mobile computing resource, a desktop computing resource, a laptop computing resource, and an embedded computing resource.
Z(0135, laptop)
The motivation would be similar to that provided for claim 1.
As per claim 9 Acuna discloses;
The system of claim 8, wherein the local computing resource comprises an embedded computing resource selected from the group consisting of: an embedded microcontroller, an embedded microprocessor, and an embedded gate array.
A(0101, embedded system control)
As per claim 10 Acuna discloses; The system of claim 1, wherein the one or more operative coupled computing resources comprises resources selected from the group consisting of: a remote data center; a remote server; a remote computing cluster; and an assembly of computing systems in a remote location. A(0073, server) Z(0131 server)
As per claim 11, Acuna does not explicitly disclose what Zargahi teaches
The system of claim 1, further comprising a localization element operatively coupled to the computing system and configured to determine a location of the human operator relative to a global coordinate system. Z(0038)
The motivation would be similar to that provided for claim 1.
As per claim 12 Acuna discloses; The system of claim 11, wherein the localization element is selected from the group consisting of: a GPS sensor; an IP address detector; a connectivity triangulation detector; an electromagnetic localization sensor; an optical location sensor.
A(0101 GPS)
As per claim 13 Acuna discloses; The system of claim 11, wherein the one or more operatively coupled computing resources are activated based upon the determined location of the human operator. A(0093, data center operator)
As per claim 14, Acuna discloses; The system of claim 1, wherein the user interface comprises a graphical user interface.
A(0072, interface)
As per claim 15 Acuna discloses;
The system of claim 1, wherein the user interface comprises an audio user interface.
A(0085, sound)
As per claim 16 Acuna discloses; The system of claim 14, wherein the graphical user interface is configured to engage the human operator using an element selected from the group consisting of: a computer graphics engagement display; a video graphics engagement display; and an audio engagement accompanied by displayed graphics.
A(0081, graphic cluster, choice of one)
As per claim 17 Acuna discloses;
The system of claim 14, wherein the graphical user interface comprises a video graphics engagement display configured to present a real-time or near real-time graphical representation of a video interface engagement character with which the human operator may converse.
A(0081,0085)
As per claim 18 Acuna does not explicitly disclose what Zargahi teaches; The system of claim 17, wherein the video interface engagement character is selected from the group consisting of: a humanoid character, an animal character, and a cartoon character.
Z(0043) The motivation for the combination would be similar to that provided for claim 1.
As per claim 19 Acuna does not explicitly disclose what Zargahi teaches;
The system of claim 18, wherein the user interface is configured to allow the human operator to select the visual presentation of the video interface engagement character.
Z(fig. 4) The motivation for the combination would be similar to that provided for claim 1.
As per claim 20 Acuna does not explicitly disclose what Zargahi teaches;
The system of claim 19, wherein the user interface is configured to allow the human operator to select a visual presentation characteristic of the video interface engagement character selected from the group consisting of: character gender, character hair color, character hair style, character skin tone, character eye coloration, and character shape.
Z(0119-120, manual development)
The motivation for the combination would be similar to that provided for claim 1.
As per claim 21 Acuna discloses;
The system of claim 19, wherein the visual presentation of the video interface engagement character may be modelled after a selected actual human.
A(0083, interface)
As per claim 22 Acuna discloses; The system of claim 18, wherein the user interface is configured to allow the human operator to select one or more audio presentation aspects of the video interface engagement character.
A(0083)
As per claim 23 Acuna discloses; The system of claim 22, wherein the user interface is configured to allow the human operator to select one or more audio presentation aspects of the video interface engagement character selected from the group consisting of: character voice intonation; character voice loudness; character speaking language; character speaking dialect; and character voice dynamic range.
A(0083)
As per claim 24, Acuna discloses;
The system of claim 23, wherein the one or more audio presentation aspects of the video interface engagement character may be modelled after a selected actual human.
A(0083)
As per claim 25 Acuna discloses; The system of claim 1, wherein the predetermined process configuration comprises a finite group of steps through which the engagement shall proceed in furtherance of the established requirement.
A(0104, steps)
As per claim 26, Acuna discloses; The system of claim 1, wherein the predetermined process configuration comprises a process element selected from the group consisting of: one or more generalized operating parameters; one or more resource/input awareness and utilization settings; a domain expertise module; a process sequencing paradigm; a process cycling/iteration paradigm; and an AI utilization and configuration setting.
A(0017)
As per claim 27 Acuna discloses;
The system of claim 25, wherein the finite group of steps comprises steps selected from the group consisting of: problem definition; potential solutions outline; preliminary design; and detailed design.
A(0037)
As per claim 28 Acuna does not explicitly disclose what Zargahi teaches; The system of claim 25, wherein the predetermined process configuration comprises a selection of elements by the human operator.
Z(0038-0042)
The motivation would be similar to that provided for claim 1.
As per claim 29 Acuna does not explicitly disclose what Zargahi teaches;
The system of claim 28, wherein selection of elements by the human operator comprises selecting synthetic operator resourcing for one or more aspects of the predetermined process configuration. Z(0038)
The motivation would be similar to that provided for claim 1.
Claims 30-37 are similar to claim 29 in their rejection by Acuna in view of Zargahi
As per claim 38 Acuna discloses; The system of claim 37, wherein the convolutional neural network is informed using inputs from a training dataset using a supervised learning model.
Acuna(0055, supervised learning)
As per claim 39 Acuna discloses;
The system of claim 37, wherein the convolutional neural network is informed using inputs from a training dataset along with analysis of the established requirement using a reinforcement learning model. (CNN, 0028)
As per claim 40 Acuna discloses synthetic actions but Zargahi teaches human elements;
The system of claim 1, wherein each of the one or more synthetic operators is informed by a convolutional neural network informed at least in part by a curated selection of synthetic action records pertaining to synthetic actions of an actual human operator. (0020-21)
In regards to human’s see Zargahi.
The motivation for the combination is similar to that provided for claim 1.
As per claim 41 Acuna discloses; The system of claim 1, wherein each of the one or more synthetic operators is informed by a convolutional neural network informed at least in part by a curated selection of synthetic action records pertaining to synthetic actions of a synthetic operator. (0020-21)
As per claim 42 Acuna discloses; The system of claim 25, wherein the computing system is configured to separate each of the finite group of steps with an execution step during which the one or more synthetic operators are configured to progress toward the established requirement in accordance with one or more execution behaviors associated with the pertinent convolutional neural network.
A(0032 CNN)
As per claim 50, Acuna does not explicitly disclose what Zargahi teaches
The system of claim 1, wherein the user interface is configured to allow the human operator to pause the computing system while it otherwise proceeds through the predetermined process configuration so that one or more intermediate results may be examined by the human operator pertaining to the established requirement. Z(0039)
The motivation for the combination would be similar to that proposed in claim 1.
As per claim 51, Acuna does not explicitly disclose what Zargahi teaches; The system of claim 50, wherein the user interface is configured to allow the human operator to change one or more aspects of the one or more specific facts during the pause of the computing system to facilitate forward execution based upon the change. Z(0039 manual correction)
The motivation for the combination would be similar to that proposed in claim 1.
As per claim 52, Acuna discloses;
The system of claim 1, wherein the user interface is configured to provide the human operator with a calculated resourcing cost based at least in part upon utilization of the operatively coupled computing resources in the predetermined process configuration.
Acuna (0021, 24)
Claims 43-49 are rejected under 35 USC 103 over US Patent Publication to Acuna Marrero 20220383073 in view of US Patent Publication 2020/0090001 to Zargahi further in view of US patent Publication
To Conort 20220076164
As per claims 43-49 Acuna and Zargahi do not explicitly disclose the project element that Conort teaches; 0290 generically teaches project leadership.
The motivation for the combination is to provide …to provide feature engineering for machine learning models (0004)
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Towards Pervasive Distributed Agentic Generative AI -- A State of The Art, ArXiv 2025
AI generations: from AI 1.0 to AI 4.0, PMC 2025
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/BRUCE I EBERSMAN/Primary Examiner, Art Unit 3693