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
Claim Rejections - 35 USC § 101
1. 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 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. Each of the independent claims recites steps that users provide natural language requests, prompt generated based on natural language, and in response generating structure data used to invoke or execute operations of the application which could be done by submit forms or run scripts. All of the recited steps are processes that, under its broadest reasonable interpretation, cover the limitations under the organized human activity with paper and pen.
The claim features under its broadest reasonable interpretation, are certain methods of organizing human activity performed by generic computer components. For example, but for the “accessing” [human activity:], “generating” [human activity: causing, creating], “receiving” [human behavior: collecting, obtaining], “executing” [human behavior: performing, implementing], and “providing” [human behavior: understanding that, on the condition], in the context of this claim encompasses methods of organized human activity. If the claim limitations, under its broadest reasonable interpretation, covers fundamental economic practice, commercial or legal interaction or managing personal behavior or relationships or interactions between people but for the recitation of generic computer components, then it falls within the "system/method of organized human activity" grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
This judicial exception is not integrated into a practical application. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea.
"[A]fter determining that a claim is directed to a judicial exception, 'we then ask, [w]hat else is there in the claims before us?"' MPEP 2106.05 (emphasis in MPEP) citing Mayo, 566 U.S. at 78. "What is needed is an inventive concept in the non-abstract application realm." SAP Inc. v. lnvestPic, LLV, Appeal No. 2017-2081 (Fed. Cir. 2018). For step two, the examiner must "determine whether the claims do significantly more than simply describe [the] abstract method" and thus transform the abstract idea into patent-eligible subject matter. Ultramercial, Inc. v. Hutu, LLC, 772 F.3d 709 (Fed. Cir. 2014).
A primary consideration when determining whether a claim recites "significantly more" than abstract idea is whether the additional element(s) are well-understood, routine, conventional activities previously known to the industry. See MPEP 2106.0S{d). "If the additional element (or combination of elements) is a specific limitation other than what is well- understood, routine and conventional in the field, for instance because it is an unconventional step that confines the claim to a particular useful application of the judicial exception, then this consideration favors eligibility. If, however, the additional element {or combination of elements) is no more than well-understood, routine, conventional activities previously known to the industry, which is recited at a high level of generality, then this consideration does not favor eligibility." Id.
The Federal Circuit has held that "[w]hether something is well-understood, routine, and conventional to a skilled artisan at the time of the patent is a factual determination." Bahr, Robert (April 19, 2018). Changes in Examination Procedure Pertaining to Subject Matter Eligibility, Recent Subject Matter Eligibility Decision (Berkheimer v. HP, Inc.) citing Berkheimer at 1369. "As set forth in MPEP 2106.05(d)(I), an examiner should conclude that an element (or combination of elements) represents well-understood, routine, conventional activity only when the examiner can readily conclude that the element(s) is widely prevalent or in common use in the relevant industry. This memo [] clarifies that such a conclusion must be based upon a factual determination that is supported as discussed in section III [of the memo]." Berkheimer Memo at 3 (emphasis in memo).
Generally, "[i]f a patent uses generic computer components to implement an invention, it fails to recite an inventive concept under Alice step two." West View Research v. Audi, CAFC Appeal Nos. 2016-1947-51 (Fed. Cir. 04/19/2017) citing Mortg. Grader, Inc. v. First Choice Loan Servs. Inc., 811 F.3d 1314, 1324-25 (Fed. Cir. 2016) (explaining that "generic computer components such as an 'interface,' 'network,' and 'database' ... do not satisfy the inventive concept requirement"; but see Bascom (finding that an inventive concept may be found in the non-conventional and non-generic arrangement of the generic computer components, i.e., the installation of a filtering tool at a specific location, remote from the end- users, with customizable filtering features specific to each end user).
In accordance with the above guidance, the examiner has searched the claim(s) to determine whether there are any "additional elements" in the claims that constitute "inventive concept," thereby rendering the claims eligible for patenting even if they are directed to an abstract idea. Alice, 134 S. Ct. 2347 (2014). Those "additional features" must be more than "well understood, routine, conventional activity." See Alice. To note, "under the Mayo/Alice framework, a claim directed to a newly discovered ... abstract idea [] cannot rely on the novelty of that discovery for the inventive concept necessary for patent eligibility." Genetic Techs. Ltd v. Merial LLC, 818 F.3d 1369, 1376 (Fed. Cir. 2016); Diamond v. Diehr, 450 U.S. 175, 188-89 (1981).
As an example, the Federal Circuit has indicated that "inventive concept" can be found where the claims indicate the technological steps that are undertaken to overcome the stated problem(s) identified in Applicant's originally-filed Specification. See Trading Techs. Inc. v. CQG, Inc., No. 2016-1616 (Fed. Cir. 2017); but see IV v. Erie Indemnity, No. 2016-1128 (Fed. Cir. March 7, 2017) ("The claims are not focused on how usage of the XML tags alters the database in a way that leads to an improvement in technology of computer databases, as in Enfish.") (emphasis in original) and IV. v. Capital One, Nos. 2016-1077 (Fed. Cir. March 7, 2017) ("Indeed, the claim language here provides only a result-oriented solution, with insufficient detail for how a computer accomplishes it. Our law demands more. See Elec. Power Grp., 830 F.3d 1356 (Fed. Cir. 2016) (cautioning against claims 'so result focused, so functional, as to effectively cover any solution to an identified problem.')"). Furthermore, "[a]bstraction is avoided or overcome when a proposed new application or computer-implemented function is not simply the generalized use of a computer as a tool to conduct a known or obvious process, but instead is an improvement to the capability of the system as a whole." Trading Techs. Int'l, Inc. v. CQG, Inc., No. 2016-1616 (Fed. Cir. 2017) (emphasis added).
In the search for inventive concept, the Berkheimer Memo describes "an additional element (or combination of elements) is not well-understood, routine or conventional unless the examiner finds, and expressly supports a rejection in writing with, one or more of the following:
A citation to an express statement in the specification or to a statement made by an applicant during prosecution that demonstrates the well-understood, routine, conventional nature of the additional element(s).
A citation to one or more of the court decisions discussed in the MPEP as noting the well-understood, routine, conventional nature of the additional element(s).
A citation to a publication that demonstrates the well-understood, routine, conventional nature of the additional element(s).
A statement that the examiner is taking official notice of the well-understood, routine, conventional nature of the additional element(s).
See Berkheimer Memo at 3-4.
Accordingly, the examiner refers to the following generically-recited computer elements with their associated functions (and associated factual finding(s)), which are considered, individually and in combination, to be routine, conventional, and well-understood:
“a system for recommending data assets, the system comprising”,
“a non-transitory computer-readable medium that stores instructions that, when executed by one or more processors, cause the one or more processors to perform operations comprising”
“a method comprising”
As set forth in MPEP § 2106.0S(d)(I), an examiner should conclude that an element (or combination of elements) represents well-understood, routine, conventional activity only when the examiner can readily conclude that the element(s) is widely prevalent or in common use in the relevant industry. The Berkhiemer memo clarifies that such a conclusion must be based upon a factual determination that is supported as discussed in section III the memo. As seen in paragraphs ([28, 99, 104, 111]) of the instant Specification and Symantec.. 838 F.3d at 1.321, 110 USPQ2d at. 1362, the elements are viewed to be well-understood, routine and conventional.
In sum, the Examiner finds that the claims "are directed to the use of conventional or generic technology in a nascent but well-known environment, without any claim that the invention reflects an inventive solution to any problem presented by combining the two." In re TLI Communications LLC, No. 2015-1372 (May 17, 2016). Similar to the claims in SAP v. lnvestPic, "[t]he claims here are ineligible because their innovation is an innovation in ineligible subject matter." Appeal No. 2017-2081 (Fed. Cir. 2018). In other words, "the advance lies entirely in the realm of abstract ideas, with no plausibly alleged innovation in the non-abstract application realm." Id. Accordingly, when considered individually and in ordered combination, the examiner finds the claims to be directed to in-eligible subject matter.
Next, it is determined whether the claim integrates the judicial expectation into a practical application by identifying whether “any additional elements recited in the claim beyond the judicial exception(s)” and evaluate those elements to determine whether the integrate the judicial exception into a recognized practical application.
In this case, the additional elements do not integrate the judicial application into a practical application. The claim does not recite (i) an improvement to the functionality of a computer or other technology or technical field ; (ii) a "particular machine" to apply or use the judicial exception; (iii) a particular transformation of an article to a different thing or state; or (iv) any other meaningful limitation.
The additional elements beyond the judicial exception are a system, a memory, one or more processors, large language model, a non-transitory computer-readable medium. Using a computing device and module to identify and determine a value and disposition of an object is merely applying the judicial exception using a generic computing component. Additionally, the claim identifies and determines a value and disposition of an object - the claim does not improve the functioning of the computing device, or other technology or field.
The claims do not recite specific limitations (alone or when considered as an ordered combination) that were not well understood, routine, and conventional. As set forth in the Specification, the disclosed subject matter can be implemented as a method, apparatus, or article of manufacture using standard programming and/or engineering techniques to produce software, firmware, hardware, or any combination thereof to control a computer to implement the disclosed subject matter.
Dependent claims 2-7, 9-14 and 16-20 include further recited limitations, do not integrate the abstract idea into a practical application, and the additional elements taken individually and in combination, do not contribute to an inventive concept, In other words, the dependent claims are directed to an abstract idea without significantly more.
Claim Rejections - 35 USC § 103
2. 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.
3. Claims 1-3, 6-10, 13-17, 20 are rejected under 35 U.S.C. 103 as being unpatentable over Moreno et al. (US Patent 12,271,688).
As to claim 1, Moreno teaches a system for recommending data assets comprising:
a memory that stores instructions; and one or more processors coupled to the memory and configured to execute the instructions to perform operation (col. 1, lines 55-58; claim 1) comprising:
accessing a natural language requests (abstract; col. 1, lines 60-61 – a natural language request for executing an analytical task);
receiving, from the LLM and in response to the prompt, a structured list of parameter values (col. 58, lines 23-30 - extracting, from the natural language input, the function parameter values of each of the one or more parameters of the analytical function may include extracting, via the LLM (e.g., LLM 1504), one or more tokens from the natural language input that correspond to the first parameter and determining, via the LLM, that the one or more tokens are of a second data type, different from the first data type; col. 81, lines 49-51 - the LLM and the analytics compute service may be separate components that the digital assistant uses to generate the response to the user input);
executing the application operation based on the structured list of parameter values (col. 1, line 63 through col. 2, line 1 - translating the natural language input to an analytical function call for calling an analytical function of a plurality of distinct analytical functions of an analytics computing server, and extracting, from the natural language input, a function parameter value for each of one or more parameters for executing the analytical function); and
providing, based on the executing of the application operation, a response to the natural language request (col. 2, lines 11-14 - a response to the natural language input that includes the technical analytical output and the natural language explanation of the technical analytical output; col. 81, lines 49-51 - the LLM and the analytics compute service may be separate components that the digital assistant uses to generate the response to the user input).
Moreno does not explicitly discuss generating, based on the natural language request and metadata for an application operation, a prompt for a large language model (LLM).
However, Moreno teaches for analytical function call, a first vector value generated for the function code, a second vector value generated for prompt name, and a third vector value generated for prompt description (col. 55, lines 63-67); generate a resource optimization request 1718 to provide to the analytics compute service 1719. Resource optimization request generator generate the resource optimization request by combining the information received from LLM 1710 into a structured format (col. 70, lines 21-30); Once the parameter values have been converted, LLM 1710 (e.g., or resource optimization request generator 1717) generates a resource optimization request (col. 71, lines 25-27).
It would have been obvious to generate a prompt for a large language model in order to generate resource optimization request by combining the information received from LLM 1710 into a structured format.
As to claims 2, 9 and 16, Moreno does not explicitly discuss the system of claim 1, the non-transitory computer readable medium of claim 8 and the method of claim 15, wherein the generating of the LLM prompt is further based on a user selected scenario. However, Moreno teaches LLM receives a user input 1702 (“What if my demand increases by 5%”) and perform prompt selection to select resource forecasting prompt 1904. After performing prompt selection, LLM 1710 extract parameters from the user input 1702 and may output the values of the extracted parameters. For instance, if the resource forecasting prompt 1904 indicates to locate a value parameter and a direction parameter, LLM 1710 attempts to extract a value for the value parameter (e.g., 5%) and the direction parameter (e.g., “increases”) (col. 71, lines 2-11). It would have been obvious that the LLM prompt selection based on user input that selected a scenario by the user demand increases by 5% in order for the LLM to attempt to extract a value for the value parameter 5%.
As to claims 3, 10 and 17, Moreno does not explicitly discuss the system of claim 1, the non-transitory computer readable medium of claim 8 and the method of claim 15, wherein the storing data for the application operation into a database table; and based on the structured list of parameter values, invoking the application operation. However, Moreno teaches extracting, from the natural language input, a function parameter value for each of one or more parameters for executing the analytical function; calling the analytical function at the analytics computing server using the analytical function call and the function parameter value extracted for each of the one or more parameters of the analytical function (col. 4 lines 39-45); a computer-implemented system may comprise: one or more processors; a memory; a computer-readable medium operably coupled to the one or more processors, the computer-readable medium having computer-readable instructions stored thereon that, when executed by the one or more processors, cause a computing device to perform operations comprising: calling the analytical function at the analytics computing server using the analytical function call and the function parameter value extracted for each of the one or more parameters of the analytical function (col. 7, lines 12-32). Hence, it would have been obvious that parameter values for executing the analytical function stored in computing server or a computer-readable medium operably coupled to the one or more processors for future processing needs.
As to claims 6, 13 and 20, Moreno teaches the system of claim 1, the non-transitory computer readable medium of claim 8 and the method of claim 15, wherein the response from the LLM comprises a set of parameter values in extended markup language (XML) format (col. 70, lines 27-35 - resource optimization request generator generates the resource optimization request 1718 by combining the information received from LLM 1710 into a structured format (e.g., in an Extensible Markup Language (XML) format or a JavaScript Object Notation (JSON) format). In some examples, resource optimization request generator 1717 provides the resource optimization request 1718 to the analytics compute service 1719 via an API call).
As to claims 7 and 14, Moreno teaches the system of claim 1 and the non-transitory computer readable medium of claim 8, wherein the operations further comprise receiving, via a user interface, the natural language request (col. 62, lines 25-29 - receive a natural language input including a natural language request for executing an analytical task. The natural language input may be received via a GUI, a command line interface, or an application programming interface (API); col. 68, lines 37-40 - receive, via a GUI associated with the analytics digital assistant, user input that includes a request to execute a resource demand forecasting task).
4. Claims 4-5, 11-12 and 18-19 are rejected under 35 U.S.C. 103 as being unpatentable over Moreno et al. (US Patent 12,271,688) in view of Elimelech (2023/0132877).
As to claims 4, 11, and 18, Moreno does not explicitly discuss the system of claim 1, the non-transitory computer readable medium of claim 8 and the method of claim 15, wherein the storing of the data for the application operation comprises storing a parameter name and a parameter type.
Elimelech teaches the schema can include a schema record for each operation, and a schema record for each parameter of the operation. Each schema record for a parameter can include the name of the parameter, a description of the parameter, and a type of the parameter ([0047]).
It would have been obvious before the effective filing date of the claimed invention to incorporate the teachings of Elimelech into the teachings of Moreno for the purpose of identifying a containerized cluster operation that includes a textual parameter name and parameter type for mapping data structure.
As to claims 5, 12 and 29, Elimelech teaches the system of claim 1, the non-transitory computer readable medium of claim 8 and the method of claim 15, wherein the storing of the data for the application operation comprises storing a parameter description ([0047]); and Moreno teaches process 1430 calls the analytical function based on the function parameter value extracted for the one or more parameters and the default function parameter value assigned to the required parameter (col. 58, lines 53-56), hence it would have been obvious that a parameter default value extracted from a storage when the LLM did not extract the function parameter value of the required parameter then extracting the default one for processing.
Conclusion
5. Any inquiry concerning this communication or earlier communications from the examiner should be directed to QUYNH H NGUYEN whose telephone number is (571)272-7489. The examiner can normally be reached Monday-Thursday 7:30AM-5:30PM.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Ahmad Matar can be reached on 571-272-7488. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/QUYNH H NGUYEN/Primary Examiner, Art Unit 2693
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