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 .
Applicant’s Reply
Applicant's response of 06/11/26 has been entered. The examiner will address applicant's remarks at the end of this office action. Currently claims 1, 3-8, 10-15, 17-23, are pending.
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, 3-8, 10-15, 17-23, are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
The claims recite a method, system and a non-transitory computer readable medium; therefore, the claims pass step 1 of the eligibility analysis.
For step 2A, the claim(s) recite(s) an abstract idea of generating an incident status report for an incident (the incident can be any type of incident).
Using claim 1 as a representative example that is applicable to claims 8, 15, the abstract idea is defined by the elements of:
obtaining a set of reportable criteria related to the incident;
for one or more reportable criteria of the set, transmitting a respective classification request,
the respective classification request comprising the incident data and a reportable criterion of the one or more reportable criteria of the set, and instructing to return a binary decision indicating whether the incident data includes the reportable criterion;
identifying a subset of the reportable criteria, the subset including each reportable criterion for which the binary decision indicates that the incident data includes the reportable criterion;
transmitting a summarization request, wherein the summarization request includes the subset of the reportable criteria and the incident data, and
summarize the incident data based on the subset of the reportable criteria; and
transmitting an incident status report
The obtaining of data regarding criteria related to an incident and the request for a classification and a summary of the incident data as claimed with the transmitting of an incident report is the act of monitoring and keeping others updated about the status of an incident, where the incident can be anything. This is something that is considered to be a certain method of organizing human activities type of abstract idea. Human beings can perform the claimed steps. When an incident occurs, such as a law enforcement incident (a crime) or an accident, it is known that people track the status of the incident and can received updates about the status, such as whether or not the incident is taken care of or is still in progress, etc.. People can request and receive written summaries that would satisfy the claimed summarization request. The claimed abstract idea is a concept that is managing relationships between people by keeping interested parties informed about the status of an incident. The claimed concept is similar to the President receiving status updates about a military operation that is in progress, as was done in WWII, or a CEO obtaining an update about a data breach that has occurred. The concept of obtaining incident data and performing the steps claimed to provide for an incident status report that includes information about the incident and reportable data is something that people are capable of performing manually. For this reason the claims are considered to be reciting a certain method of organizing human activity.
For claim 1 the additional elements are the recitation to a language model classifier that classifies the incident and the use of a language model to summarize the incident data. The language model classifier and the language model have been interpreted as being a model such as an artificial intelligence model that is being used to create the incident status report that is itself part of the abstract idea.
For claim 8, the additional elements are the one or more memories, one or more processors and the recitation to a language model classifier that classifies the incident and the use of a language model to summarize the incident data.
For claim 15, the additional elements are the non-transitory computer readable medium that is storing instructions to perform the steps that define the abstract idea, and the use of the a language model classifier that classifies the incident and the use of a language model to summarize the incident data.
This judicial exception is not integrated into a practical application (2nd prong of eligibility test for step 2A) because the additional elements of the claim when considered individually and in combination with the claim as a whole, amount to the use of a computing device (with a processor(s) and memory) that is being merely used as a tool to execute the abstract idea, in combination with a general link to the use of language models, see MPEP 2106.05(f), (h). The claim is simply instructing one to practice the abstract idea by using a generically recited computing devices that have a processor and memory. This is claiming computer implementation for the abstract idea and does not provide for integration into a practical application, see MPEP 2106305(f). Using a language model to output an incident report is interpreted as being a general link to the particular field of machine learning for execution of a step that defines the abstract idea, see MPEP 2106.05(h). The use of the language model(s) is/are broadly reciting the use of artificial intelligence models to effectuate the performance of the abstract idea. The extent of the use of the processors and memory and the language model(s) is that they are being used as a tool to execute the abstract idea that can otherwise be practiced by humans with no technology at all. The claimed additional elements do not amount to more than a mere instruction to implement the abstract idea on a computer that uses a language model in the form of an artificial intelligence models to perform the steps that defines the abstract idea (classification, binary response, summarization of incident data). This is the equivalent of reciting “apply it” with a computer for the abstract idea and is taken as a link to a particular technological environment, that is the use of computers and artificial intelligence (machine learning). This is indicative of the fact that the claim has not integrated the abstract idea into a practical application and therefore the claim is found to be directed to the abstract idea identified by the examiner.
For step 2B, the claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception when considered individually and in combination with the claim as a whole because they amount to the use of a computing device (with a processor(s) and memory) that is being merely used as a tool to execute the abstract idea, in combination with a general link to the use of language models, see MPEP 2106.05(f), (h). The claim is simply instructing one to practice the abstract idea by using a generically recited computing devices that have a processor and memory. This is claiming computer implementation for the abstract idea and does not provide for integration into a practical application, see MPEP 2106305(f). Using a language model to output an incident report is interpreted as being a general link to the particular field of machine learning for execution of a step that defines the abstract idea, see MPEP 2106.05(h). The use of the language model(s) is/are broadly reciting the use of artificial intelligence models to effectuate the performance of the abstract idea. The extent of the use of the processors and memory and the language model(s) is that they are being used as a tool to execute the abstract idea that can otherwise be practiced by humans with no technology at all. The claimed additional elements do not amount to more than a mere instruction to implement the abstract idea on a computer that uses a language model in the form of an artificial intelligence models to perform the steps that defines the abstract idea (classification, binary response, summarization of incident data). This is the equivalent of reciting “apply it” with a computer for the abstract idea and is taken as a link to a particular technological environment, that is the use of computers and artificial intelligence (machine learning). The rationale set forth for the 2nd prong of the eligibility test above is also applicable to step 2B because the issue is the same, namely the computer implementation of the abstract idea using language models. This does not amount to reciting significantly more than the abstract idea at step 2B.
Therefore, claims 1, 8, 15, do not recite any additional elements that provide for integration at the 2nd prong or that provide significantly more at step 2B. Therefore the claims are not considered to be eligible.
For claims 3, 10, 17, identifying whether the incident data includes the reportable criteria is part of the abstract idea as was set forth for claims 1, 8, 15. The training data including first training data as claimed and second training data as claimed are elements that are also considered to be part of the abstract idea. Training data is just data or information per se and is not eligible subject matter. The recitation to training of the language model classifier is claiming that the classifier is artificial intelligence, as was addressed for claims 1, 8, 15. The training the language model is an additional element that is interpreted as being a link to the use of artificial intelligence, as was stated for the independent claims. Artificial intelligence (machine learning) by definition employs a trained model that has been trained on training data. The claimed training limitation is reciting training of a model and is an instruction for one to use a trained model to perform a step of the abstract idea and/or can be construed as a link to a particular technological environment, namely the field of artificial intelligence or machine learning. Training an artificial intelligence classifier requires training of the model and is not more than a link to artificial intelligence (machine learning). The recitation to training the classifier based on first and second data training sets is a link to machine learning and does not provide for integration into a practical application or significantly more, for the same reasons already addressed for claims 1, 8, 15, see MPEP 2106.05(f), (h). The claims do not recite any additional elements that provide for integration at the 2nd prong or that provide significantly more at step 2B. Therefore the claims are not considered to be eligible.
For claims 4, 11, 18, the claimed data that is the reportable criteria is part of the abstract idea. The data of the incident such as if the incident has a fix identified, or if the incident is resolved, are elements that fall under the umbrella of the abstract idea. No further additional elements have been claimed for consideration beyond those recited in the independent claims. The claims do not recite any additional elements that provide for integration at the 2nd prong or that provide significantly more at step 2B. Therefore the claims are not considered to be eligible.
For claims 5-7, 12-14, 19, 20, claiming that the summarization request includes a style criterion is part of the abstract idea, as well as reciting that the style indicates one or more users are technical users, reciting that the style indicates a maximum number of words to be included, reciting anonymizing the incident status report, and excluding social media tags. This is claiming the format or appearance or content for the status report that is being output. This is part of the abstract idea. No further additional elements have been claimed for consideration beyond those recited in the independent claims. The claims do not recite any additional elements that provide for integration at the 2nd prong or that provide significantly more at step 2B. Therefore the claims are not considered to be eligible.
For claims 21-23, the limitation reciting that the incident data that does not correspond to reportable criteria of the subset is excluded from the incident status report is claiming more about the abstract idea and the content of the report. The content of the report and the generation of the report are elements that are part of the abstract idea. A human can write a report and exclude data from the report, which is not actually claiming what the report includes but is claiming what the report does not include. This serves to define more about the abstract idea. No further additional element is claimed for consideration other than those already addressed for claims 1, 8, 15. The claims do not recite any additional elements that provide for integration at the 2nd prong or that provide significantly more at step 2B. Therefore the claims are not considered to be eligible.
Therefore, for the above reasons Claims 1, 3-8, 10-15, 17-23, are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Claim Rejections - 35 USC § 102
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.
Claim(s) 1, 8, 15, is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Wei et al. (20220366146).
For claims 1, 8, 15, Wei discloses a computerized system (memory, processor) and method for reporting incidents, tracking incidents, and using language models to create status reports for incidents in an automated manner, see paragraph 009 in general.
The claimed obtaining of incident data associated with an incident is satisfied by Wei disclosing that an incident can be reported about an emergency, see paragraph 029, 032. The receipt of information indicating that an incident such as an emergency has occurred satisfies the claimed data associated with an incident. The claimed obtaining of the set of reportable criteria related to the incident is satisfied by the information that is contained in the incident logs that is looked for by the system to deduce the status of the incident, see paragraph 018. Wei discloses that received incident data is analyzed to determine status values for status objects (reportable criteria). Data that is included in an incident report that correlates to the status objects in Wei satisfies the obtaining of the reportable criteria related to the incident. Also see paragraph 032.
The claimed use of the language model classifier for the classification request and the classifier instructed to return a binary decision indicating whether the incident data includes the reportable criteria, this is satisfied by the use of a language classifier model in Wei that receives the properties (the reportable criteria) and analyzes the properties (reportable criteria) to determine if a real time update should be provided, where the update provides the reportable criteria to the user as an update (satisfies the identifying of the reportable criteria). Paragraph 018 teaches that incident properties are extracted and updated, and depending on the status values, the system determines whether or not to provide an update (yes) or not provide an update due to nothing new to update about (no). See paragraph 020. Paragraph 031 teaches that the providing of a status update is automatic when the system determines that one should be provided. The system of Wei is determining if an update is to be provided or not, which satisfies the claimed binary decision of whether or not the incident data contains the reportable criteria. This satisfies what is claimed.
The claimed transmitting of a summarization request to a language model, that includes the subset of reportable criteria and the incident information, is satisfied by Wei teaching that a natural language generator is used to generate text for an incident report upon request from a user, see paragraphs 020, 038. A user can request an incident report (update report) about an incident by entering a query that specifies the incident and what the user wants as information. This satisfies what is claimed.
The claimed transmitting of an incident status report is disclosed in paragraph 015, 020, 038. After the summarization request is submitted to the language model in Wei, the output of the language model is a status report for the incident, which is provided to the user in Wei. This satisfies the claimed transmitting of an incident status report that is the output from the language model and in response to the summarization request for the user.
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) 3, 4, 10, 11, 17, 18, 21-23, is/are rejected under 35 U.S.C. 103 as being unpatentable over Wei et al. (20220366146).
For claims 3, 10, 17, Wei discloses that the classifier needs to be trained, see paragraph 017, 024, 028. Paragraph 028 teaches that the training data needs to be annotated for training, which is implying to one of ordinary skill in the art the use of supervised machine learning although it is not expressly disclosed. The classifier of Wei is a pre-trained deep learning model that requires training. Not discloses is first training data that includes reportable criteria and second training data that does not include reportable criteria. This is interpreted to be the use of supervised machine learning that uses data training sets that have positive examples and negative examples for the training. The examiner takes official notice of the fact that supervised machine learning uses training data that has been annotated as positive examples and annotated as negative examples for the model to learn from. This is a well-known manner by which machine learning models can be trained and is something that is very well known to those of ordinary skill in the artificial intelligence (machine learning) art. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to provide Wei with the ability to train the classifier using training data that has examples with reportable criteria and with examples that does not have reportable criteria, so that the classifier can be trained using supervised machine learning. This is a well-known way to train a machine learning model and would yield predictable results of allowing the classifier model of Wei to be trained using supervised machine learning that has a positive data training set and a negative data training set.
For claims 4, 11, 18, the claimed reportable criteria is claiming data relating to various aspects about the incident and that indicates status of the incident such as a cause of the incident (a fire) or a change in severity (an update to the incident). These are satisfied by Wei. The reportable criteria is satisfied by the content of the incident logs in Wei that represents the incident and any updates or changes in information for the incident. Any information that is received about an incident satisfies the claimed reportable criteria. Not disclosed is that the criteria includes if the incident is under investigation, a level of customer impact, whether a fix is identified, a change in severity and whether or not it is resolved. The language of these claims is directed at non-functional descriptive material that does not define more than criteria in general. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have the incident logs able to include data such as if the incident is under investigation, a level of customer impact, whether a fix is identified, a change in severity and whether or not it is resolved so that the incident and its status can be known. The claimed aspects to an incident are fully within the purview of one of ordinary skill in the art as far as when an incident occurs, people want to know if it is under investigation or what impact the incident has or whether it has been fixed or not, it is has gotten worse, etc.. What is claimed as far as criteria that can define an incident are things that would have been obvious to one of ordinary skill in the art.
For claims 21-23, Wei teaches that status objects for an incident are monitored for their status (properties of the incident) and that updates for the status objects are provided to a user in the incident report, see paragraph 038. The latest status of the incident status objects is determined and used in generating the incident report. This is teaching that the status objects are provided to a user. Not expressly disclosed is that the incident report excludes incident data that does not correspond to the reportable criteria of the subset. While not disclosed, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to not include irrelevant data in an incident report that does not correspond to reportable criteria of the subset so that the user is not provided with irrelevant information that has nothing to do with the status of the incident. One of ordinary skill in the art would understand that the incident report will contain varying content depending on the use and situation at hand, and that based on Wei teaching that the incident status is monitored and updated using status objects (reportable criteria), one of ordinary skill in the art would find it obvious to only report the reportable criteria that is relevant to a user as opposed to including incident data that does not correspond to reportable criteria and is of little to no interest in a user who is requesting the incident report. This would yield the predictable result of ensuring that the incident report contains useful information and does not contain information that does not correspond to reportable criteria that is of little to no interest to a user and that has no bearing on the status of the incident.
Claim(s) 5-7, 12, 19, 20, is/are rejected under 35 U.S.C. 103 as being unpatentable over Wei et al. (20220366146) in view of O’Donncha et al. (21210312122).
For claims 5, 12, 19, not disclosed is that the summarization request includes a style criteria. This element is reciting the aspect of the invention that uses the language model to customize or tailor the output of the language model to a diverse audience.
O’Donncha et al. (21210312122) discloses a system and method for generating documents with a particular style. See paragraph 014. In paragraph 002 it is disclosed that effective communication depends on appropriate style, tone, descriptiveness, concision, vocabulary given the intended reader or audience. Paragraph 081 discloses that a language model can be used to generate output that is based on a target style.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to provide Wei with the ability to customize the output of the language model using style criteria as set forth by O’Donncha. This would yield the predictable results of allowing for the report to be tailored to certain audiences using a particular style, that would depend on the audience at hand.
For claims 6, 20, the combination above for claims 5, 15, is considered to satisfy the claimed element where the style indicates if one or more users are technical users. This is claiming a particular type of audience member that the style is for. In paragraph 012 of O’Donncha it is disclosed that the style can be tailored for users such as readers of a scientific journal as opposed to elementary school students. This satisfies what is claimed because readers of scientific journal are technical users (the term technical does not define anything to the user itself).
For claims 7, 20, Wei as modified in view of O’Donncha does not teach that the style includes maximum number of words that the report is to be limited to. O’Donncha teaches that concision is a consideration to make when rendering a document for communication with a user. Concision is defined as the act of being concise. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to provide Wei (as modified with O’Donncha) with style that limits a document communication to a certain number of words so that the report is concise and not too long. Nobody wants to read a 20 page report when the information can be provided in 1 or 2 pages by being concise. Limiting the incident report to a maximum numbers of words would have been obvious in view of a desire to be concise with the content of the report.
Claim(s) 13, 14, is/are rejected under 35 U.S.C. 103 as being unpatentable over Wei et al. (20220366146) in view of O’Donncha et al. (21210312122) and further in view of Blumenfeld et al. (20150244681).
For claims 13, 14, not disclosed is that the style indicates that the incident report data should be anonymized or that social media tags are removed.
For claims 13, 14, Blumenfeld teaches a system and method for anonymous incident reporting where an incident report that contains incident data is anonymized, see the abstract and paragraph 005, 006, 009 as examples. This ensures that incident information is kept anonymous. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to provide Wei with the ability to anonymize the incident report as claimed. Anonymizing of data and reports as is taught by Blumenfeld is known in the art and would have been obvious to provide to Wei.
For claim 14, while not disclosed in the cited art, it would have been obvious to one of ordinary skill in the art to remove social media tags when anonymizing the incident report data because social media tags can be used to identify a person, such as a person that is reporting an incident who wants to remain anonymous, or for an update to the incident that is received by the system of Wei and that is to be anonymized. If one is anonymizing the incident report data, then it follows that one of ordinary skill in the art would want to remove social media tags as part of the anonymization of the incident report. This yields the predictable result of ensuring that social media tags are removed to maintain anonymity.
Response to arguments
The traversal of the 35 USC 101 rejection is not persuasive. On page 7 of the reply the applicant argues that the claims does not recite an abstract idea at step 2A. The applicant argues that the transmitting of a request to a language model classifier and use of a language model are operations of specific machine components. The applicant argues that a human cannot transmit a classification request to a language model classifier as claimed. This is not persuasive because the transmission of the request to classify and instruction to return a binary decision, and the summarization request are elements that define the abstract idea. A human can request a classification and a binary response by asking another person to perform a classification, etc. A person can request another person provide a summary of incident data as claimed. Absent the recitation to the use of “models”, the claimed functions that are being argued are fully capable of being performed by a person and are property treated as elements of the abstract idea. The fact that the claims use language models is a recitation to using machine learning as a tool to execute the abstract idea, see MPEP 2106.05(f), (h). The claim is simply instructing one to practice the abstract idea by using a generically recited computing devices that have a processor and memory and that uses language models. Using a language model(s) as claimed is a general link to the particular field of machine learning for execution of a step that defines the abstract idea, see MPEP 2106.05(h). The extent of the use of the processors and memory and the language model is that they are being used as a tool to execute the abstract idea. This does not amount to more than a mere instruction to implement the abstract idea on a computer that uses a language model in the form of an artificial intelligence model. This is the equivalent of reciting “apply it” with a computer for the abstract idea and is taken as a link to a particular technological environment, that is the use of computers and artificial intelligence (machine learning).
The applicant argues that the claims are integrated into a practical application because the claims are reciting the asking of a language model to return a binary answer to questions about a corpus of data (indecent data) and then creating a summary of the request based on the answers. This is arguing the abstract idea itself and not a practical application of the abstract idea that would amount to more than a general link to the use of computers and language models to perform steps that represent the abstract idea. The applicant does little more than to generally allege that the claims are integrated into a practical application by arguing the abstract idea in terms of the transmission of the claimed requests. This is not persuasive.
With respect to the comment about an adversarial attack, the applicant argues that a hacker might inject irrelevant data to incident response. This is irrelevant to the claimed invention that has nothing to do with preventing hacking of any kind. The applicant is arguing that the claims are improving how data is generated, which is not persuasive. The manner in which the data is being generated is what defines the abstract idea and the fact that the claims recite the use of a processor and language models is a link to computer technology that is being used as a tool to execute the abstract idea. The claims do not result in an improvement to technology such that the claims would be eligible. The claims do not recite additional elements that with the claim as a whole are providing for integration into a practical application.
For step 2B, the applicant has not presented any argument. The applicant has requested evidentiary support for the claimed combination of elements being well understood, routine, and conventional in the art is if this was a requirement at step 2B, which is not true. The applicant is stating something is required from Berkheimer that is not actually required in the eligibility guidance or the Berkheimer memo. Absent a request for evidence that the claim in total was so well known that is essentially ubiquitous in the art (which is the meaning of something being well understood, routine, and conventional), there is no argument being presented.
The examiner additionally notes that no such requirement exists in the eligibility guidance that instructs examiners to provide evidence for step 2B in all situations. The examiner has not taken the position that anything is well understood, routine, or conventional at step 2B because nothing has been found to be an insignificant extra solution activity at the 2nd prong. Examiners do not have to prove that a claimed invention was well understood, routine, and conventional in a given field to find that the claims are not eligible at step 2B. To do so would be injecting a prior art analysis into the eligibility inquiry. Something that is well understood, routine, and conventional is more than just known in the art, it means that something is more or less ubiquitous in a given field. There is no requirement that an examiner prove with evidence that a claimed invention is so well known in a given field that it rises to the level of being well understood, routine, and conventional. This requires not just the existence of one or two of even maybe three prior art references that would teach the invention as claimed but would require a showing that the claimed invention in total was so well known in the art that it is hard to not find it in the prior. The rejection of record does not find anything to be an insignificant extra solution activity at the 2nd prong so there is nothing to reassess at step 2B with respect to the issue of being well understood, routine, and conventional (the Berkheimer memo). The argument is not persuasive and not relevant to the rejection of record. The examiner does not have to produce evidence that establishes the well understood nature of the abstract idea and the additional elements as a whole. What is being argued is not provided for in the guidance as it pertains to step 2B when the issue at hand is an instruction for one to apply the abstract idea in a particular technological field, such as the use of computers and machine learning (language models) for the pending claims. The authority for this position is found in MPEP 2106.05(f) and (h). Therefore the request for evidence is not persuasive to show error in the 101 rejection.
The arguments are not persuasive and the 101 rejection is being maintained.
With respect to the prior art rejection, the arguments are considered to be moot based on the new grounds of rejection that was necessitated by the amendment to the claims. Wei is considered to anticipate what is claimed in claims 1, 8 and 15 as is set forth in the rejection of record. This moots the argument from the applicant that is generally arguing that the claimed elements are not taught by Wei. The dependent claims have not been argued separately and rely on the argument for claims 1, 8, 15, which is not persuasive and is moot based on the rejection of record.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to DENNIS WILLIAM RUHL whose telephone number is (571)272-6808. The examiner can normally be reached M-F 7am-3:30pm.
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, Jessica Lemieux can be reached at 5712703445. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/DENNIS W RUHL/Primary Examiner, Art Unit 3626
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