DETAILED ACTION
This non-final office action is in response to Applicant’s submission filed July 17, 2025. Currently Claims 1-20 are pending. Claims 1, 10 and 19 are the independent claims.
The instant application is a continuation of application no. 18485554 now U.S. Patent No. 12387154. Application No. 18485554 is a continuation of application no. 17308996 now U.S. Patent No. 11823102.
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 .
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Regarding Claims 2, 11 and 20, the claims recite the limitation " for each group" in claims 1, 10 and 19. There is insufficient antecedent basis for this limitation in the claim. Appropriate correction is required.
Regarding Claims 5 and 14, the claims recite the limitation " determining that all groups" in claims 1, 10 and 19. There is insufficient antecedent basis for this limitation in the claim. Appropriate correction is required.
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13.
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The actual filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/apply/applying-online/eterminal-disclaimer.
Claims 1-3, 10-12, 19 and 20 are rejected on the ground of nonstatutory double patenting over claims 1, 8, 9, 16 and 17 of U.S. Patent No. 11823102 (application no. 17308996) since the claims, if allowed, would improperly extend the “right to exclude” already granted in the patent.
The subject matter claimed in the instant application is fully disclosed in the patent and is covered by the patent since the patent and the application are claiming common subject matter, as follows:
The claims are rejected over U.S. Patent No. 11823102, wherein it would be obvious to one skilled in the art to omit, from the independent claims, one or more method step – see table below. Applicant appears to be attempting to broaden the scope of the parent application/patent and capture scope which was forgone during prosecution of the parent application.
The table below maps the conflicting claims between the instant application and U.S. Patent No. 11823102.
App. No. 19272278
UPSN 11823102
Claims 1, 10, 19
*replaced the phrase shopper in ‘102 with picker
Claims 1, 8, 16
Omitted:
applying...learning model to the geographic location of the warehouse...and periodically retrained....
wherein training the machine learning model comprises performing, by the one or more processors of the training system, a training process comprising: applying a set of training data describing historical numbers of shoppers available during the plurality of discrete time intervals to the machine learning model, and adjusting weights of the machine learning model based on the applying of the set of training data to the machine learning model, and wherein periodically retraining the machine learning model comprises performing, by the one or more processors of the training system, a training process comprising:
using the trained machine learning model to obtain an additional set of training data by applying the machine learning model to a plurality of discrete time intervals for a period of time, the additional set of training data describing numbers of shoppers available during the plurality of discrete time intervals in the period of time
grouping, by the one or more processors of the online concierge system, the number of estimated shoppers into a plurality of groups based on the identified characteristics;
for each of the plurality of groups, determining, by the one or more processors of the online concierge system, a score based on a combination of characteristics of estimated shoppers in the group, the score computed based on a combination of values of levels in the one or more tree structures corresponding to the combination of characteristics of each estimated shopper in the group;
identifying, by the one or more processors of the online concierge system, one or more groups in the plurality of groups having a combination of characteristics capable of fulfilling the order from the tags applied to the order;
selecting, by the one or more processors of the online concierge system, an estimated shopper from an identified group having a minimum score to fulfill the order;
dispatching, by the online concierge system, the selected shopper for fulfilling the order, wherein dispatching the selected shopper comprises transmitting, over the network, the order to a client device associated with the selected shopper for fulfilling the order, wherein the dispatching causes the client device to display the order to the selected shopper for fulfillment; and
decrementing a number of estimated shoppers in the identified group having the minimum score in response to the dispatching.
2, 11, 20
1, 8, 16
3, 12
2, 9, 17
Furthermore, there is no apparent reason why applicant was prevented from presenting claims corresponding to those of the instant application during prosecution of the application which matured into a patent. See In re Schneller, 397 F.2d 350, 158 USPQ 210 (CCPA 1968). See also MPEP § 804.
Claims 1, 2, 8, 10, 11, 18, 19 and 20?are rejected on the ground of nonstatutory double patenting over claims 1, 9 and 17 of U.S. Patent No. 12387154 (application no. 18485554) since the claims, if allowed, would improperly extend the “right to exclude” already granted in the patent.
The subject matter claimed in the instant application is fully disclosed in the patent and is covered by the patent since the patent and the application are claiming common subject matter, as follows:
The claims are rejected over U.S. Patent No. 12387154, wherein it would be obvious to one skilled in the art to omit, from the independent claims, one or more method step – see table below. Applicant appears to be attempting to broaden the scope of the parent application/patent and capture scope which was forgone during prosecution of the parent application.
The table below maps the conflicting claims between the instant application and U.S. Patent No. 12387154.
App. No. 19272278
UPSN 12387154
Claims 1, 10, 19
*replaced the phrase shopper in ‘102 with picker
Claims 1, 9, 17
Omitted:
"thereby improving the accuracy of the machine learning model"
group the number of estimated shoppers into a plurality of groups based on the levels of the estimated shoppers in the tree structures;
for each of the plurality of groups, determine, by the one or more processors, a score computed based on a combination of levels of the estimated shoppers;
identify one or more groups in the plurality of groups having a combination of levels capable of fulfilling the order; select one of the identified one or more groups having a minimum score; select an estimated shopper from the selected group to fulfill the order;
dispatch the selected shopper for fulfilling the order, wherein dispatching the selected shopper comprises transmitting, over the network, the order to a client device associated with the selected shopper for fulfilling the order, wherein the dispatching causes the client device to display the order to the selected shopper for fulfillment; and
decrement a number of estimated shoppers in the selected group having the minimum score in response to the dispatching.
2, 11, 20
1, 9, 17
8, 18
1, 9, 17
Furthermore, there is no apparent reason why applicant was prevented from presenting claims corresponding to those of the instant application during prosecution of the application which matured into a patent. See In re Schneller, 397 F.2d 350, 158 USPQ 210 (CCPA 1968). See also MPEP § 804.
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 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
Regarding independent Claims 1, 10 and 19, the claims are directed to the abstract idea of human resource planning. This is a process (i.e. a series of steps) which (Statutory Category – Yes –process).
The claims recite a judicial exception, a method for organizing human activity, human resource planning (Judicial Exception – Yes – organizing human activity). Specifically, the claims are directed to ????, wherein human resource planning is a fundamental economic practice that falls into the abstract idea fundamental economic principles and practice (resource planning). See 2106.04(a). Further all of the steps of “maintaining”, “receiving”, “applying”, “training”, “accessing”, “applying”, “determining”, “updating”, and “applying” recite functions of the human resource planning are also directed to an abstract idea that falls into the abstract idea fundamental economic principles and practice (resource planning) . The intended purpose of independent claims 1, 10 and 19 appears to be apply one or more tags to an order based on one or more items wherein the one or more tags correspond to levels (capability) of pickers capable of fulfilling the order.
Accordingly, the claims recite an abstract idea – fundamental economic practice, specifically in the abstract idea fundamental economic principles and practice (resource planning). The exceptions are the picker (who is a person) and additional limitations of generic computer elements: online concierge system (software per se), client device, network, computer readable storing medium having instructions encoded thereon, one or more processors. See 2106.04(a).
Accordingly, the claims recite an abstract idea under Step 2A, Prong One, we proceed to Step 2A, Prong Two. Considering whether the additional elements set forth in the claim integrate the abstract idea into a practical application (See 2106.04(a)), the previously identified non-abstract elements directed to generic computing components include: online concierge system (software per se), client device, network, computer readable storing medium having instructions encoded thereon, one or more processors. These generic computing components are merely used to maintain, access or process data as described extensively in Applicant’s specification (Specification: Paragraphs 71-73). Generic computers performing generic computer functions, alone, do not amount to significantly more than the abstract idea. Moreover, when viewed as a whole with such additional elements considered as an ordered combination, the claim modified by adding a generic computer would be nothing more than a purely conventional computerized implementation of applicant's human resource planning in the general field of business management – human task allocation/assignment and would not provide significantly more than the judicial exception itself. Note McRo, Inc. v. Bandai Namco Games America Inc. (837 F.3d 1299 (Fed. Cir. 2016)), guides: "[t]he abstract idea exception prevents patenting a result where 'it matters not by what process or machinery the result is accomplished."' 837 F.3d at 1312 (quoting O'Reilly v. Morse, 56 U.S. 62, 113 (1854)) (emphasis added). The claims are not directed to a particular machine nor do they recite a particular transformation (MPEP § 2106.05(b)).
Additionally, the claims do not recite any specific claim limitations that would provide a meaningful limitation beyond generally linking the use of the judicial exception to a particular technological environment. Nor do the claims present any other issues as set forth in the MPEP 2106.04(a) regarding a determination of whether the additional generic elements integrate the judicial exception into a practical application. Rather, the claims merely use instructions to implement an abstract idea on a computer, or merely use a computer as a tool to perform an abstract idea. Thus, under Step 2A, Prong Two (MPEP §§ 2106.05(a)-(c) and (e)- (h)), claims 1-20 do not integrate the judicial exception into a practical application.
Regarding the use of the generic (known, conventional) recited online concierge system (software per se), client device, network, computer readable storing medium having instructions encoded thereon, one or more processors," the Supreme Court has held "the mere recitation of a generic computer cannot transform a patent-ineligible abstract idea into a patent-eligible invention." Alice, 573 U.S. 208, 223. Generic computers performing generic computer functions, alone, do not amount to significantly more than the abstract idea. The claims as a whole do not recite more than what was well-known, routine and conventional in the field (see MPEP § 2106.05(d)). In light of the foregoing and under the MPEP 2106.04(a), that each of the claims, considered as a whole, is directed to a patent-ineligible abstract idea that is not integrated into a practical application and does not include an inventive concept.
Regarding the recited application of a machine learning model to determine an estimated number of pickers and levels of estimated pictures in a tree structure and to predict a number of pickers at each level, is recited at a high level of generality and amounts to no more than mere instructions to apply the abstract idea using a generic machine learning model on a generic computer, also recited at a high level of generality. The machine learning model is used to generally apply the abstract idea without limiting how the machine learning model functions. The machine learning model is described at a high level such that it amounts to using a generic computer with a generic machine learning model to apply the abstract idea. These limitations only recite outcomes/results of the steps without any details about how the outcomes are accomplished.
Accordingly, the claims are not patent eligible under 35 U.S.C. 101.
Additionally, the claims recite a judicial exception, a mental processes, which can be performed in the human mind or via pen and paper (Judicial Exception – Yes – mental process).
The claimed steps of applying a machine learning model…to determine an estimated number of pickers, training the model over historical data, applying the model to predict a number of pickers at each level, determining an error metric, updating model parameters to reduce an error metric and applying one or more task to orders corresponding to levels of pickers capable of fulfilling the order all describe the abstract idea. These limitations as drafted are directed to a process that under its reasonable interpretation covers performance of the steps in the mind but for the recitation of the generic computer components. Other than the recitation of an online concierge system (software per se), client device, network, computer readable storing medium having instructions encoded thereon, one or more processors nothing in the claimed steps precludes the step from practically being performed in the mind. The claims do not recite additional elements that are sufficient to amount to significantly more than the abstract idea because the steps maintaining a data store (plurality of discrete time intervals…information describing a pluralyt of pickers…), receiving an order from a client device, accessing a plurality of training examples are directed to insignificant pre-solution activity (i.e. data gathering). The mere nominal recitation of a generic processor/computer does not take the claim limitation out of the mental processes grouping. Thus, the claim recites a mental process. (Judicial Exception recited – Yes – mental process).
The claims do not integrate the abstract idea into a practical application. The generic online concierge system (software per se), client device, network, computer readable storing medium having instructions encoded thereon, one or more processors are each recited at a high level of generality merely performs generic computer functions of retrieving, processing or displaying data. The generic processor/computer merely applies the abstract idea using generic computer components. The elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claims do not recite improvements to the functioning of a computer or any other technology field (MPEP 2106.05(a)), the claims do not apply or use the abstract idea to effect a particular treatment or prophylaxis for a disease or medical condition, the claims to do apply the abstract idea with a particular machine (MPEP 2106.05(b)), the claims do not effect a transformation or reduction of a particular article to a different state or thing (e.g. data remains data even after processing; MPEP 2106.05(c)), the claims no not apply or use the abstract idea in some other meaningful way beyond generally linking the user of the abstract idea to a particular technological environment (i.e. a generic computer) such that the claim as a whole is more than a drafting effort designed to monopolize the abstract idea (MPEP 2106.05(e)). The recited generic computing elements are no more than mere instructions to apply the exception using a generic computer component.
Regarding the recited application of a machine learning model to determine an estimated number of pickers and levels of estimated pictures in a tree structure and to predict a number of pickers at each level, is recited at a high level of generality and amounts to no more than mere instructions to apply the abstract idea using a generic machine learning model on a generic computer, also recited at a high level of generality. The machine learning model is used to generally apply the abstract idea without limiting how the machine learning model functions. The machine learning model is described at a high level such that it amounts to using a generic computer with a generic machine learning model to apply the abstract idea. These limitations only recite outcomes/results of the steps without any details about how the outcomes are accomplished. The recitation of a machine learning model in this claim does not negate the mental nature of these limitations because the machine learning is merely used at a tool to perform an otherwise mental process.
The instant application fails to be patent eligible under 35 U.S.C. 101 for very similar reasons the court found Recentive Analytics, Inc. v. Fox Corp., No. 2023-2437 (Fed. Cir. Apr. 18, 2025) patents ineligible, namely the claims do no more than apply established methods of machine learning to a new data environment (order fulfillment, resource planning, human task assignment).
Similar to the discussion on Page 12 of the Recentive decision, the Applicant has failed to provide support or substantative arguments that the disclosed invention or the claimed invention improves the recited first/machine learning processes or the unsupervised machine learning process now claimed (“But Recentive also admits that the patents do not claim a specific method for “improving the mathematical algorithm or making machine learning better.” Oral Arg. at 4:40–4:44.). As such the recite machine learning processes are merely tools/conduits for the abstract idea – recited at a high level and applied using a generic computer/computing device which is likewise not improved by the recited or disclosed invention (i.e. claims lack a specific technological improvement). More specifically not only does Applicant’s specification fail to disclose a improvement which the newly claimed machine learning processes (first/second machine learning, unsupervised machine learning), Applicant’s disclosure and subsequent arguments fila to delineate steps through which the machine learning processes, now claimed, achieve an improvement.
See, e.g., IBM v. Zillow Grp., Inc., 50 F.4th 1371, 1381 (Fed. Cir. 2022) (holding abstract a claim that “d[id] not sufficiently describe how to achieve [its stated] results in a non-abstract way,” because “[s]uch functional claim language, without more, is insufficient for patentability under our law.” (quoting Two-Way Media Ltd v. Comcast Cable Commc’ns, LLC, 874 F.3d 1329, 1337 (Fed. Cir. 2017))); see also Intell. Ventures I LLC v. Capital One Fin. Corp., 850 F.3d 1332, 1342 (Fed. Cir. 2017) (similar); Elec. Power Grp., LLC v. Alstom S.A., 830 F.3d 1350, 1356 (Fed. Cir. 2016) (similar). “[T]he patent system represents a carefully crafted bargain that encourages both the creation and the public disclosure of new and useful advances in technology, in return for an exclusive monopoly for a limited period of time.” Pfaff v. Wells Elecs., 525 U.S. 55, 63 (1998); Sanho Corp. v. Kaijet Tech. Int’l Ltd., 108 F.4th 1376, 1382 (Fed. Cir. 2024). Allowing a claim that functionally describes a mere concept without disclosing how to implement that concept risks defeating the very purpose of the patent system. In this respect, the patents’ claims are materially different from those in McRO, Inc. v. Bandai Namco Games America Inc., 837 F.3d 1299 (Fed. Cir. 2016), and Koninklijke, the cases on which Recentive relies.
Instead of disclosing “a specific implementation of a solution to a problem in the software arts,” Enfish, LLC v. Microsoft Corp., 822 F.3d 1327, 1339 (Fed. Cir. 2016), or “a specific means or method that solves a problem in an existing technological process,” Koninklijke, 942 F.3d at 1150, the only thing the claims disclose about the use of machine learning is that machine learning is used in a new environment. This new environment is to determine an estimated number of pickers and levels of estimated pictures in a tree structure and to predict a number of pickers at each level. Similar to the court’s conclusion that simply applying machine learning to a new field of use does not result in patent eligibility, Applicant’s disclosure makes clear that the recite machine learning model is not improved in any way and do not result in an improvement in an underlying technology or another technical field) (“We see no merit to Recentive’s argument that its patents are eligible because they apply machine learning to this new field of use. We have long recognized that “[a]n abstract idea does not become nonabstract by limiting the invention to a particular field of use or technological environment.” Intell. Ventures I LLC v. Capital One Bank (USA), 792 F.3d 1363, 1366 (Fed. Cir. 2015); see also Alice, 573 U.S. at 222; Parker v. Flook, 437 U.S. 584, 593 (1978); Stanford, 989 F.3d at 1373 (rejecting argument that a claim was not abstract where patentee contended “the specific application of the steps [was] novel and enable[d] scientists to ascertain more haplotype information than was previously possible”).
As Applicant’s specification makes clear, the invention as disclosed merely automates previous manual methods wherein the court found that merely using existing machine learning technology to perform tasks previously undertaken by humans does not render a claim patent eligible under 35 U.S.C. 101 (“Finally, the claimed methods are not rendered patent eligible by the fact that (using existing machine learning technology) they perform a task previously undertaken by humans with greater speed and efficiency than could previously be achieved. We have consistently held, in the context of computer-assisted methods, that such claims are not made patent eligible under § 101 simply because they speed up human activity. See, e.g., Content Extraction, 776 F.3d at 1347; DealerTrack, 674 F.3d at 1333. Whether the issue is raised at step one or step two, the increased speed and efficiency resulting from use of computers (with no improved computer techniques) do not themselves create eligibility. See, e.g., Trinity Info Media, LLC v. Covalent, Inc., 72 F.4th 1355, 1363 (Fed. Cir. 2023) (rejecting argument that “humans could not mentally engage in the ‘same claimed process’ because they could not perform ‘nanosecond comparisons’ and aggregate ‘result values with huge numbers of polls and members’”) (internal citation omitted); Customedia Techs., LLC v. Dish Network Corp., 951 F.3d 1359, 1365 (Fed. Cir. 2020) (holding claims abstract where “[t]he only improvements identified in the specification are generic speed and efficiency improvements inherent in applying the use of a computer to any task”); compare McRo, 837 F.3d at 1314– 16 (finding eligibility of claims to use specific computer techniques different from those humans use on their own to produce natural-seeming lip motion for speech).”)
Accordingly, the claims are more similar to those the court found ineligible under 35 U.S.C. 101 and are therefore also ineligible under 35 U.S.C. 101.
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. (Integrated into a Practical Application – No).
As discussed above the additional elements in the claims amount to no more than a mere instruction to apply the abstract idea using generic computing components, wherein mere instructions to apply an judicial exception using generic computer components cannot integrate a judicial exception into a practical application or provide an inventive concept. For the retrieving and displaying steps that were considered extra-solution activity, this has been re-evaluated and determined to be well-understood, routine, conventional activity in the field. Applicant’s specification does not provide any indication that the computer/processor is anything other than a generic, off-the-shelf computer component, and the Symantec, TLI, and OIP Techs. court decisions (MPEP 2106.05(d)(II)) indicate that mere collection or receipt of data is a well‐understood, routine, and conventional function when it is claimed in a merely generic manner (as it is here). For these reasons, there is no inventive concept. The claim is ineligible (Provide Inventive Concept – No).
The claims are ineligible under 35 U.S.C. 101 as being directed to an abstract idea without significantly more.
Regarding dependent claims 2-11 and 13-19, the claims are directed to the abstract idea of human resource planning and merely further limit the abstract idea claimed in independent claims 1, 10 and 19.
Claims 2, 11 and 20 further limit the abstract idea by limiting the tag to a respective picker characteristics and determining a score for each group of estimated pickers (a more detailed abstract idea remains an abstract idea). Claims 3 and 12 further limit the abstract idea computing a product of the values associated with levels in the trees structure (a more detailed abstract idea remains an abstract idea, a mathematical operation). Claims 4 and 13 further limit the abstract idea by updating a picker capability characteristics including ONE or more of modifying a value, adding a new level or removing an existing level (a more detailed abstract idea remains an abstract idea). Claims 5 and 14 further limit the abstract idea by determining that all groups of estimated pickers are capable of fluffing the order and transmitting a prompt recommending selection of an alternative discrete time interval (a more detailed abstract idea remains an abstract idea). Claims 6 and 15 further limit the abstract idea by maintaining separately a tree structure for each tag (a more detailed abstract idea remains an abstract idea). Claims 7 and 16 further limit the abstract idea by selecting tags based on attributes of both items in the order and an identified warehouse (a more detailed abstract idea remains an abstract idea). Claims 8 and 17 further limit the abstract idea by selecting a picker from a group of estimated pickers (a more detailed abstract idea remains an abstract idea). Claims 9 and 18 further limit the abstract idea wherein each value in the tree structure is indicative of breadth of fulfillment capability (a more detailed abstract idea remains an abstract idea).
None of the limitations considered as an ordered combination provide eligibility because taken as a whole the claims simply instruct the practitioner to apply the abstract idea to a generic computer.
Further regarding claims 1-20, Applicant’s specification discloses that the claimed elements directed to a online concierge system (software per se), client device, network, computer readable storing medium having instructions encoded thereon, one or more processors at best merely comprise generic computer hardware which is commercially available (Specification: Paragraphs 71-73). More specifically Applicant’s claimed features directed to a system do not represent custom or specific computer hardware circuits, instead the terms merely refers to commercially available software and/or hardware. Thus, as to the system recited, "the system claims are no different from the method claims in substance. The method claims recite the abstract idea implemented on a generic computer; the system claims recite a handful of generic computer components configured to implement the same idea." See Alice Corp. Pry. Ltd., 134 S.Ct. at 2360.
Accordingly, the claims merely recite manipulating data utilizing generic computer hardware (e.g. memory, processor, etc.). Generic computers performing generic computer functions, alone, do not amount to significantly more than the abstract idea. Further the lack of detail of the claimed embodiment in Applicant’s disclosure is an indication that the claims are directed to an abstract idea and not a specific improvement to a machine.
Accordingly given the broadest reasonable interpretation and in light of the specification the claims are interpreted to include the process steps being performed by a human mind or via pen and paper. The claim limitations which recite a computer implemented method is at best recite generic, well-known hardware. However, the recited generic hardware simply performs generic computer function of displaying or processing data. Generic computers performing generic, well known computer functions, alone, do not amount to significantly more than the abstract idea. Further the recited memories are part of every conventional general-purpose computer.
Applicant has not demonstrated that a special purpose machine/computer is required to carry out the claimed invention. A special purpose machine is now evaluated as part of the significantly more analysis established by the Alice decision and current 35 U.S.C. 101 guidelines. It involves/requires more than a machine only broadly applying the abstract idea and/or performing conventional functions.
Applicant’s specification discloses that the claimed elements directed to a online concierge system (software per se), client device, network, computer readable storing medium having instructions encoded thereon, one or more processors merely comprise generic computer hardware which is commercially available (Specification: Paragraphs 71-73). More specifically Applicant’s claimed features directed to a system and components do not represent custom or specific computer hardware circuits, instead the term system merely refers to commercially available software and/or hardware. Thus, as to the system recited, "the system claims are no different from the method claims in substance. The method claims recite the abstract idea implemented on a generic computer; the system claims recite a handful of generic computer components configured to implement the same idea." See Alice Corp. Pry. Ltd., 134 S.Ct. at 2360.
Accordingly, the claims are not patent eligible under 35 U.S.C. 101.
Allowable Subject Matter
The closest prior art, see detailed discussion below, fail to teach or suggest either singularly or in combination an order fulfillment system comprising: storing a plurality of discrete time intervals for fulfilling orders received by the online concierge system, and information describing a plurality of pickers, the information comprising one or more characteristics of the plurality of pickers encoded in a tree structure having a plurality of levels, wherein each level has a value corresponding to a capability of pickers to fulfill an order; receiving an order from a client device over a network, the order including one or more items and a discrete time interval; applying a machine learning model to the discrete time interval to determine an estimated number of pickers and corresponding levels of the estimated pickers in the tree structure, wherein the machine learning model is trained over historical data describing available pickers in the tree structure during a plurality of discrete time intervals, the training comprising: accessing a plurality of training examples, each labeled with a discrete time interval and a plurality of pickers available during the interval, each picker corresponding to a level in the tree structure; determining an error metric by comparing predicted numbers with labeled values; and updating model parameters to reduce the error metric; applying one or more tags to the received order based on the one or more items, the one or more tags corresponding to levels of pickers capable of fulfilling the order as recited in independent Claims 1, 10, and 19.
The claims remain rejected under 35 U.S.C. 101 and 35 U.S.C. 112b and are therefore not in condition for allowance.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Singh et al., U.S. Patent No. 11829908 discloses an order fulfillment system, assigning groups of orders to pickers
Krishnamoorthy et al. U.S. Patent Publication No. 20220398526 discloses an order fulfillment system for in store order pickups comprising grouping human workers/pickers, order timelines, dividing orders into sub-orders assigned to groups of pickers and utilizing machine learning,
Ripert et al., U.S. Patent No. 10818186 discloses a system and method for assigning orders (picking tasks) to in-store shoppers/delivery agents.
Allor et al., U.S. Patent No. 7240288 discloses an expandable tree, graphical user interface, for assigning computing resources for tasks.
Rajkhowa, U.S. Patent No. 10699328 discloses a system and method for assigning orders to available pickers.
Krishanan, U.S. Patent Publication No. 20170091880 discloses a system and method comprising grouping orders to vendors for delivery.
Nari, U.S. Patent No. 9665899, discloses a system and method for managing batches of in-store picking pickers/shoppers.
Field-Darragh, U.S. Patent Publication No. 20140279294 discloses a system and method for assigning orders to pickers.
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SCOTT L. JARRETT
Primary Examiner
Art Unit 3625
/SCOTT L JARRETT/Primary Examiner, Art Unit 3625
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