Prosecution Insights
Last updated: April 19, 2026
Application No. 18/532,136

CLASSIFYING AN INSTANCE USING MACHINE LEARNING

Non-Final OA §101§103
Filed
Dec 07, 2023
Examiner
LI, RUIPING
Art Unit
2676
Tech Center
2600 — Communications
Assignee
Telefonaktiebolaget Lm Ericsson (Publ)
OA Round
1 (Non-Final)
77%
Grant Probability
Favorable
1-2
OA Rounds
2y 10m
To Grant
95%
With Interview

Examiner Intelligence

Grants 77% — above average
77%
Career Allow Rate
722 granted / 933 resolved
+15.4% vs TC avg
Strong +18% interview lift
Without
With
+18.0%
Interview Lift
resolved cases with interview
Typical timeline
2y 10m
Avg Prosecution
40 currently pending
Career history
973
Total Applications
across all art units

Statute-Specific Performance

§101
13.0%
-27.0% vs TC avg
§103
41.2%
+1.2% vs TC avg
§102
25.9%
-14.1% vs TC avg
§112
13.7%
-26.3% vs TC avg
Black line = Tech Center average estimate • Based on career data from 933 resolved cases

Office Action

§101 §103
DETAILED ACTION Notice of Pre-AIA or AIA Status. 1. The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA . Election/Restrictions 2. Applicant's election with traverse in the applicant’s response submitted on 01/26/2026, is acknowledged. The Examiner has made a thorough review of arguments presented in that document and has found it to be persuasive. Therefore, the restriction under 35 USC 121 and 372 has been withdrawn. Accordingly, claims 1-13 are pending and being examined. Claims 1 and 8 are independent form. Claim Rejections - 35 USC § 101 3. 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. 4. Claims 1-13 are rejected under 35 U.S.C. 101 because the claimed inventions are directed to non-statutory subject matter (an abstract idea without significantly more). 4-1. Regarding independent claim 1, the claim recites a selection server for selecting one or more other communications devices for classifying an instance using Machine Learning, ML, the selection server being operative to: [1] receive, from a communications device for classifying an instance using ML, a selection request message for selecting one or more other communications devices for classifying an instance using ML, the selection request message comprising information pertaining to at least one of: an identity of a user of the communications device, a contact list of the user, a type of data comprised in a feature vector representing the instance, an origin of the feature vector, a classification of the instance using a local first ML model of the communications device, a location of the communications device, a location associated with the instance, and one or more classified instances which are related to the instance represented by the feature vector; [2] select the one or more other communications devices based on at least one of: the identity of the user, the contact list of the user, the type of data comprised in the feature vector, the origin of the feature vector, the classification of the instance using the local first ML model, the location of the communications device, a respective location of the one or more other communications devices, the location associated with the instance, and the one or more classified instances which are related to the instance represented by the feature vector; and [3] transmit, to the communications device, a selection response message comprising information identifying the selected one or more other communications devices. Step 1: With regard to step (1), claim 1, is directed to a selection server for selecting one or more other communications devices for classifying an instance using Machine Learning. The claim 1 therefore is one of statutory categories of invention, i.e., a machine and/or manufacture. Step 2A-1: With regard to 2A-1, The elements recited in claim 1, as drafted, under their broadest reasonable interpretation, encompass a process(es) which is/are directed to organizing human activity, can be practically performed in human mind, or falls within mathematical concepts. For example, “select[ing] the one or more other communications devices based on [] the identity of the user” in step [2] in the context of this claim, is directed to manage personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions) therefore the limitation falls within the organizing human activity grouping. Similarly, “select[ing] the one or more other communications devices based on [] the origin of the feature vector” in step [2] in the context of this claim, is associated with mathematical calculations and encompasses mental determination that can be performed in human mind therefore the limitation falls within the organizing human activity grouping. Similarly, “transmit[ting], to the communications device, a selection response message comprising information identifying the selected one or more other communications devices” in step [3] is directed to manage personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions) therefore the limitation falls within the organizing human activity grouping of abstract ideas. Claim 1 therefore recites an abstract idea. If a claim limitation is directed to organizing human activity, can be practically performed in human mind, or falls within mathematical concepts, then the claim recites an abstract idea. See MPEP 2106.04(a)(2). Step 2A-2: The 2019 PEG defines the phrase "integration into a practical application" to require an additional element or a combination of additional elements in the claim to apply, rely on, or use the judicial exception. In the instant case, the additional elements of “receiv[ing] from a communications device for classifying an instance using ML, a selection request message [...]” in steps [1] under their broadest reasonable interpretation, are mere data gathering recited at a high level of generality, and thus are insignificant extra-solution activity. Similarly, the “selection server” and the “communications devices” are recited at high level of generality and amount to no more than mere instruction to apply the exception using generic communication devices, such as a smart phone. Similarly, the claim recites “using machine learning (ML)” for classifying an instance, but providing nothing more than mere instruction to implement an abstract idea on a generic computer. Therefore, the claim as a whole does not integrate the judicial exception into a practical application. Step 2B: As explained above, the electronic device comprising a selection server and communications devices, is at best the equivalent of merely adding the words “apply it” to the judicial exception. The “receiv[ing]” in step [1] was considered insignificant extra-solution activity. These conclusions should be reevaluated in Step 2B. The limitations are mere data gathering and/or output recited at high level of generality and amount to receiving (i.e., acquiring), accessing, or transmitting data over a network, which is well-understood, routine, conventional activity. See MPEP 2106.05(d), subsection II. The limitations remain insignificant extra-solution activity even upon reconsideration. Even when considered in combination, the additional elements present mere instructions to apply an exception and insignificant extra-solution activity, which cannot provide an inventive concept. The claim therefore is ineligible. 4-2. Regarding dependent claims 2-7, they are viewed individually, these additional elements are under its broadest reasonable interpretation, either covers performance of the limitation in the mind, performing a mathematical algorithm or extra solution activity for data gathering and do not provide meaningful limitations to transform the abstract idea into a patent eligible application of the abstract idea such that the claims amount to significantly more than the abstract idea itself. And, when the claims are viewed as a whole, they do not improve a technology by allowing the technology to perform a function that it previously was not capable of performing; and they do not provide any limitations beyond generally linking the use of the abstract idea to a broad technological environment (i.e., computer-based analysis of generic data). Hence, the claimed invention does not constitute significantly more than the abstract idea, so the claims are rejected under 35 USC § 101 as being directed to non-statutory subject matter. 4-3. Regarding independent claims 8 and 13, the claims recite a method (claim 8) and a non-transitory storage medium (claim 13) and each of which is analogous to apparatus claim 1. Therefore, grounds of rejection analogous to those applied to claim 1 are applicable to claims 8 and 13. Regarding step 2A-2, the claim(s) does/do not integrate the abstract idea into a practical application because the claim(s) does/do not recite any additional elements that impose any meaningful limits on practicing the abstract idea. The claim(s) therefore recites/recite an abstract idea. Because the claim(s) fails/fail under (2A), the claim(s) needs/need to be further evaluated under (2B). The claim(s) herein does/do not include any additional elements that are sufficient to amount to significantly more than the judicial exception. The claim(s) is/are not patent eligible. 4-4. Regarding dependent claims 9-12 they are dependent from claim 8 and viewed individually, these additional elements are under its broadest reasonable interpretation, either covers performance of the limitation in the mind, performing a mathematical algorithm or extra solution activity for data gathering and do not provide meaningful limitations to transform the abstract idea into a patent eligible application of the abstract idea such that the claims amount to significantly more than the abstract idea itself. And, when the claims are viewed as a whole, they do not improve a technology by allowing the technology to perform a function that it previously was not capable of performing; and they do not provide any limitations beyond generally linking the use of the abstract idea to a broad technological environment (i.e., computer-based analysis of generic data). Hence, the claimed invention does not constitute significantly more than the abstract idea, so the claims are rejected under 35 USC § 101 as being directed to non-statutory subject matter. Claim Rejections - 35 USC § 103 5. 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. 6. 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 of this title, 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. 7. Claims 1-13 rejected under 35 U.S.C. 103 as being unpatentable over Ushida et al (US Pub 2004/0010409, hereinafter “Ushida”) in view of Huang et al (“AUDIO-VISUAL DEEP LEARNING FOR NOISE ROBUST SPEECH RECOGNITION”, 2013, hereinafter “Huang”). Regarding claim 1, Ushida discloses a selection server for selecting one or more other communications devices for classifying an instance (the voice/speech recognition system; see abstract and fig.1) receive, from a communications device for classifying an instance see para.168: “An audio receiving part 112 [of the server 111] receives audio data from the client 101.” It should be noticed that the audio data from the client 101 is the selection request message from the device 101 for recognizing the audio data pertaining to the device 101), select the one or more other communications devices based on therefore, the device 101 is the communication device selected to transmit a response message to), transmit, to the communications device, a selection response message comprising information identifying the selected one or more other communications devices (see para.172: “the audio recognition engine 114 [of server 111] recognizes the audio data according to the vocabulary and outputs the audio data recognized result to [...] a result transmit part 116 [i.e., the client 101]”.). As explained above, the mere difference is that Ushida does not discloses using machine learning (ML) for speech recognition. However, using machine learning for speech recognition is a well-known and widely used technique. As evidence, in the same field of endeavor, Huang teaches audio-visual deep learning for robust speech recognition, see the title, wherein the deep belief network (DBN) is trained by both the audio data and the visual data, see fig.1 and Sec.3. It would have been obvious to one of ordinary skill in the art before the effective filling date of the claimed invention was made to combine the teachings of Huang and the teachings of Ushida and use the deep belief network (DBN) to classify input data. Suggestion or motivation for doing so would have been to “improve audio-visual speech recognition” and “extract better audio-visual features”, see Sec. 1, Par.5. Therefore, the claim is unpatentable over Ushida in view of Huang. Regarding claim 2, 9, the combination of Ushida and Huang discloses, being operative to select the one or more other communications devices for classifying an instance using ML by using a second ML model, and being further operative to: receive, from at least one of: the communications device and the one or more other communications devices, a calculated confidence level (Ushida, para.13: “a predetermined case the first transmitting means transmits the audio data to another device is a case a degree of reliability in the recognition result by the first audio recognition means is not more than a predetermined threshold value”); and update the second ML model based on the received calculated confidence level (Huang, see the DBN’s training phase in Sec. 3.1, wherein the “weight layer is trained”). Regarding claim 3, 10, the combination of Ushida and Huang discloses, wherein the instance is an image or a video frame capturing an object (Huang, see “audio-visual input” in fig.1). Regarding claim 4, 11, the combination of Ushida and Huang discloses, wherein the instance is an audio recording capturing a sound (Ushida, see “audio data” in fig.1). Regarding claim 5, 12, the combination of Ushida and Huang discloses the selection server according to claim 1, comprising: a communications module, wherein the communications module is operative to effect communications through a communications network; a processing unit; and a computer-readable storage medium (Ushida, see “the client”, “the server”, and the communication between them shown in fig.1, see para.52, para.105). Regarding claim 6, the combination of Ushida and Huang discloses the selection server according to claim 1, further comprising: a device selection module; and a messaging module (ibid.). Regarding claim 7, the combination of Ushida and Huang discloses the selection server according to claim 1, wherein the selection server is maintained by a social-network provider (Ushida, see “the client”, “the server”, and the communication between them shown in fig.1, see para.52, para.105). Regarding claims 8, 13, each of them is an inherent variation of claim 1, thus it is interpreted and rejected for the reasons set forth in the rejection of claim 1. Conclusion 9. Any inquiry concerning this communication or earlier communications from the examiner should be directed to RUIPING LI whose telephone number is (571)270-3376. The examiner can normally be reached 8:30am--5:30pm. Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, HENOK SHIFERAW can be reached on (571)272-4637. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit https://patentcenter.uspto.gov; https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center, and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /RUIPING LI/Primary Examiner, Ph.D., Art Unit 2676
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Prosecution Timeline

Dec 07, 2023
Application Filed
Feb 13, 2026
Non-Final Rejection — §101, §103 (current)

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Study what changed to get past this examiner. Based on 5 most recent grants.

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Prosecution Projections

1-2
Expected OA Rounds
77%
Grant Probability
95%
With Interview (+18.0%)
2y 10m
Median Time to Grant
Low
PTA Risk
Based on 933 resolved cases by this examiner. Grant probability derived from career allow rate.

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