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 .
Response to Arguments
Applicant’s arguments filed on 03/30/2026 have been fully considered. Applicant’s arguments and Examiner’s response are provided below.
Applicant argues: Zeng discloses adding an AIC layer in the protocol stacks of the UE and the RAN to implement the AI functions. The transmission of the AI data stream only occurs between the UE and the RAN. Zeng does not disclose a third connection is present between a UE and a core network element.
Examiner’s response: Zeng in [0301-0302] and Fig. 7B discloses a third connection corresponding to an AI layer that is separate from the control and data planes. The third connection is between two network elements (a UE and a RAN) and is used for AI data transmission. The previous claim only required the third connection to be between a first and a second network element, and did not specify the types of network elements to be a UE and a core network device. Therefore, the argument is rendered moot in view of new ground of rejection presented in this office action, which better addresses the claims as amended and relies on ZHANG et al. (US 20230319585 A1).
Applicant argues: Paragraph [0139] of ZHANG discloses that the AI data includes data that can be used to implement network optimization, such as gradient data, various measurement reports, and various communication records. This indicates that the network optimization is a decision-making process, in contrast to the present application which involves modification at the data level. Therefore, ZHANG does not disclose supporting network elements on the transmission path in parsing and modification of content of a data portion in the AI data stream.
Examiner’s response: Since network optimization is performed using gradient data, it necessarily involves processing that data to produce updated results, which constitutes data-level modification rather than mere decision-making. Therefore, ZHANG (US 20220322111 A1) implicitly supports data-level processing and modification. Further, the new reference ZHANG (US 20230319585 A1), being relied upon based on the amended claims, explicitly discloses the third connection supporting modification of AI data.
Applicant argues: The present application proposes a new type of connection, i.e., third connection, which is also referred to as an AI connection, through which AI data can be transmitted between any two or more network elements. None of the cited references discloses such an AI connection. The technical solutions and teachings of both references are directed to solving localized RAN optimization problems, and the teachings of both Zeng and ZHANG are confined to the RAN. Neither Zeng nor ZHANG recognizes the technical problem of “how to achieve free routing of an AI data stream among multiple network elements of a communication system”.
Examiner’s response: Both Zeng and ZHANG ‘111 disclose the AI connection used for transmitting AI data between network elements. See Zeng [0301-0302] and Fig. 7B, and ZHANG ‘111, Fig. 11 and [0136]. However, based on applicant’s amendment to include a core network element as one of the network elements, the argument is rendered moot in view of new ground of rejection presented in this office action, which better addresses the claims as amended and relies on ZHANG et al. (US 20230319585 A1).
Claim Rejections - 35 USC § 103
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.
Claims 1, 4-6, 8-10, 13-15, 17-18 and 20-23 are rejected under 35 U.S.C. 103 as being unpatentable over ZHANG et al. (US 20230319585 A1) in view of ZHANG et al. (US 20220322111 A1).
Regarding claim 1,
ZHANG discloses “A method applicable to a communication system” (See [0007] the disclosed examples may facilitate secure communication of AI-related information between entities in the wireless network), “wherein the communication system supports establishments of a user plane-based first connection, a control plane-based second connection” (See Fig. 4A, [0128] It should be noted that the CU 122 may be further split into CU control plane (CU-CP) and CU user plane (CU-UP)), “and a third connection for transmitting an artificial intelligence (Al) data stream for a network element in the communication system” (See Fig. 4A-4B [0129] the A-plane 410 includes higher layer protocols, such as an AI-related protocol (AIP) layer. The AIP may encrypt all communications, ensuring secure transmission of AI-related data. The A-plane 410 enables secure exchange of AI-related information, separate from the existing control plane and data plane communications. Note: The AI-related information is transmitted between the network entities using a third connection (A-plane) that is separate from the existing control and data plane communications), “wherein a plurality of network elements of the communication system are involved on a transmission path of the Al data stream, the third connection is established between the plurality of network elements” (See [0131] As shown in FIG. 4B, the system node 120 may process AI-related data using the AIP layer, as an intermediary between the UE 110 and the network node 131. The system node 120 may make use of the AI-related data from the UE 110. The system node 120 may also simply relay the AI-related data from the UE 110 to the network node 130), “and the plurality of network elements comprise a first network element and a second network element, wherein the first network element comprises a user equipment, the second network element comprises a core network device” (See Fig. 4B, [0131] the AI execution module 220 at the system node 120 is involved in communications between the AI execution module 220 at the UE 110 and the AI management module 210 at the network node 131. As shown in FIG. 4B, the system node 120 may process AI-related data using the AIP layer, as an intermediary between the UE 110 and the network node 131. The system node 120 may also simply relay the AI-related data from the UE 110 to the network node 130. [0072] the network node 131 is within the core network 130); “and the method comprises: sending to or receiving from the second network element, by the first network element, the Al data stream over the third connection” (See [0131] The system node 120 may also simply relay the AI-related data from the UE 110 to the network node 130), “and the third connection supports modification of content of a data portion in the Al data stream by all or part of the plurality of network elements on the transmission path” (See [0129] AI-related data that may be communicated to the network node 131 (e.g., from the UE 110 and/or system node 120) may include raw (i.e., unprocessed or minimally processed) local data (e.g., raw network data) as well as processed local data (e.g., local model parameters, inferred data generated by local AI model(s), anonymized network data, etc.). See Fig. 4B, [0131] As shown in FIG. 4B, the system node 120 may process AI-related data using the AIP layer (e.g., decrypt, process and re-encrypt the data), as an intermediary between the UE 110 and the network node 131). Note: The system node performs modification of the AI data via the AIP layer (third connection) including decrypting, processing and re-encrypting the data. The AIP layer is also implemented at the UE and network node, indicating their ability to also process/ modify the AI data).
ZHANG does not explicitly disclose the third connection supports parsing of a data portion in the AI data stream.
However, ZHANG ‘111 discloses “and the third connection supports parsing of a data portion in the Al data stream by all or part of the plurality of network elements on the transmission path” (See [0136] The AI protocol layer is an independent protocol layer introduced in this embodiment of this application. See Fig. 11 and 19, The AI layer is implemented in a terminal device, an access network device and a core network element. [0244] the AI functions such as generating the AI parameter, receiving and parsing the AI data reported by the terminal device, and completing a network optimization operation based on the AI data are completed by the AI protocol layer of the first access network device). Note: The AI layer (third connection) supports parsing of the AI data.
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to have modified the teachings of ZHANG with the teachings of ZHANG ‘111, by incorporating parsing into the AIP-layer processing of ZHANG, and the motivation to do so would have been to improve efficiency and performance by enabling selective extraction and processing of relevant portions of AI data.
Regarding claim 4,
ZHANG in view of ZHANG ‘111 discloses “The method according to claim 1, wherein a third-generation partnership project (3GPP) protocol stack of the network element on the transmission path comprises a protocol layer corresponding to the third connection” (See ZHANG [0128] FIG. 4A is a block diagram illustrating an example implementation of an AI control plane (A-plane) 410 on top of the existing protocol stack as defined in 5G standards. [0129] The A-plane 410 enables secure exchange of AI-related information, separate from the existing control plane and data plane communications).
Regarding claim 5,
ZHANG in view of ZHANG ‘111 discloses “The method according to claim 4, wherein the protocol layer corresponding to the third connection is on a top layer of the 3GPP protocol stack” (See ZHANG [0128] FIG. 4A is a block diagram illustrating an example implementation of an AI control plane (A-plane) 410 on top of the existing protocol stack as defined in 5G standards. [0129] The A-plane 410 enables secure exchange of AI-related information, separate from the existing control plane and data plane communications).
Regarding claim 6,
ZHANG in view of ZHANG ‘111 discloses “The method according to claim 4, wherein there is at least one of: the network element on the transmission path comprises a user equipment, and the protocol layer corresponding to the third connection is above a Packet Data Convergence Protocol (PDCP) layer of a protocol stack of the user equipment” (See ZHANG, Fig. 4A-4B, the AIP layer is above a PDCP layer of a protocol stack of the UE).
Regarding claim 8,
ZHANG in view of ZHANG ‘111 discloses “The method according to claim 1, wherein the network elements on the transmission path comprise network elements between which a control plane connection is established and/or network elements between which a user plane connection is established” (See ZHANG Fig. 4A, [0128] It should be noted that the CU 122 may be further split into CU control plane (CU-CP) and CU user plane (CU-UP)). [0129] The A-plane 410 enables secure exchange of AI-related information, separate from the existing control plane and data plane communications).
Regarding claim 9,
ZHANG in view of ZHANG ‘111 discloses “The method according to claim 1, wherein the Al data stream comprises at least one of: input data of an Al model; model parameters of the Al model; a final result output by the Al model; an intermediate result output by the Al model; or configuration parameters of the Al model” (See ZHANG [0129] It should be noted that, in the present disclosure, AI-related data that may be communicated to the network node 131 (e.g., from the UE 110 and/or system node 120) may include raw (i.e., unprocessed or minimally processed) local data (e.g., raw network data) as well as processed local data (e.g., local model parameters, inferred data generated by local AI model(s), anonymized network data, etc..).
Regarding claim 10,
ZHANG discloses “A communication apparatus, wherein the communication apparatus is disposed in a communication system, and the communication apparatus comprises a memory and a processor, wherein the memory is configured to store a program” (See Fig. 2. [0062] FIG. 2 illustrates an example apparatus that may implement the methods and teachings according to this disclosure. In particular, FIG. 2 illustrates an example computing system 250, which may be used to implement a UE 110), “the communication system supports establishments of a user plane-based first connection, a control plane-based second connection” (See Fig. 4A, [0128] It should be noted that the CU 122 may be further split into CU control plane (CU-CP) and CU user plane (CU-UP)), “and a third connection for transmitting an artificial intelligence (Al) data stream for a network element in the communication system” (See Fig. 4A-4B [0129] the A-plane 410 includes higher layer protocols, such as an AI-related protocol (AIP) layer. The AIP may encrypt all communications, ensuring secure transmission of AI-related data. The A-plane 410 enables secure exchange of AI-related information, separate from the existing control plane and data plane communications. Note: The AI-related information is transmitted between the network entities using a third connection (A-plane) that is separate from the existing control and data plane communications), “wherein a plurality of network elements of the communication system are involved on a transmission path of the Al data stream, the third connection is established between the plurality of network elements” (See [0131] As shown in FIG. 4B, the system node 120 may process AI-related data using the AIP layer, as an intermediary between the UE 110 and the network node 131. The system node 120 may make use of the AI-related data from the UE 110. The system node 120 may also simply relay the AI-related data from the UE 110 to the network node 130), “the plurality of network elements comprises a first network element and a second network element, and the communication apparatus is the first network element, wherein the first network element comprises a user equipment, the second network element comprises a core network device” (See Fig. 4B, [0131] the AI execution module 220 at the system node 120 is involved in communications between the AI execution module 220 at the UE 110 and the AI management module 210 at the network node 131. As shown in FIG. 4B, the system node 120 may process AI-related data using the AIP layer, as an intermediary between the UE 110 and the network node 131. The system node 120 may also simply relay the AI-related data from the UE 110 to the network node 130. [0072] the network node 131 is within the core network 130); “and the processor is configured to call the program from the memory to perform: sending to or receiving from the second network element, by the first network element, the Al data stream over the third connection” (See [0131] The system node 120 may also simply relay the AI-related data from the UE 110 to the network node 130), “and the third connection supports modification of content of a data portion in the Al data stream by all or part of the plurality of network elements on the transmission path” (See [0129] AI-related data that may be communicated to the network node 131 (e.g., from the UE 110 and/or system node 120) may include raw (i.e., unprocessed or minimally processed) local data (e.g., raw network data) as well as processed local data (e.g., local model parameters, inferred data generated by local AI model(s), anonymized network data, etc.). See Fig. 4B, [0131] As shown in FIG. 4B, the system node 120 may process AI-related data using the AIP layer (e.g., decrypt, process and re-encrypt the data), as an intermediary between the UE 110 and the network node 131). Note: The system node performs modification of the AI data via the AIP layer (third connection) including decrypting, processing and re-encrypting the data. The AIP layer is also implemented at the UE and network node, indicating their ability to also process/ modify the AI data).
ZHANG does not explicitly disclose the third connection supports parsing of a data portion in the AI data stream.
However, ZHANG ‘111 discloses “and the third connection supports parsing of a data portion in the Al data stream by all or part of the plurality of network elements on the transmission path” (See [0136] The AI protocol layer is an independent protocol layer introduced in this embodiment of this application. See Fig. 11 and 19, The AI layer is implemented in a terminal device, an access network device and a core network element. [0244] the AI functions such as generating the AI parameter, receiving and parsing the AI data reported by the terminal device, and completing a network optimization operation based on the AI data are completed by the AI protocol layer of the first access network device). Note: The AI layer (third connection) supports parsing of the AI data.
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to have modified the teachings of ZHANG with the teachings of ZHANG ‘111, by incorporating parsing into the AIP-layer processing of ZHANG, and the motivation to do so would have been to improve efficiency and performance by enabling selective extraction and processing of relevant portions of AI data.
Regarding claim 13,
ZHANG in view of ZHANG ‘111 discloses “The communication apparatus according to claim 10, wherein a third-generation partnership project (3GPP) protocol stack of the network element on the transmission path comprises a protocol layer corresponding to the third connection” (See ZHANG [0128] FIG. 4A is a block diagram illustrating an example implementation of an AI control plane (A-plane) 410 on top of the existing protocol stack as defined in 5G standards. [0129] The A-plane 410 enables secure exchange of AI-related information, separate from the existing control plane and data plane communications).
Regarding claim 14,
ZHANG in view of ZHANG ‘111 discloses “The communication apparatus according to claim 13, wherein the protocol layer corresponding to the third connection is on a top layer of the 3GPP protocol stack” (See ZHANG [0128] FIG. 4A is a block diagram illustrating an example implementation of an AI control plane (A-plane) 410 on top of the existing protocol stack as defined in 5G standards. [0129] The A-plane 410 enables secure exchange of AI-related information, separate from the existing control plane and data plane communications).
Regarding claim 15,
ZHANG in view of ZHANG ‘111 discloses “The communication apparatus according to claim 13, wherein there is at least one of: the communication apparatus is a user equipment, and the protocol layer corresponding to the third connection is above a Packet Data Convergence Protocol (PDCP) layer of a protocol stack of the user equipment” (See ZHANG, Fig. 4A-4B, the AIP layer is above a PDCP layer of a protocol stack of the UE).
Regarding claim 17,
ZHANG in view of ZHANG ‘111 discloses “The communication apparatus according to claim 10, wherein the network elements on the transmission path comprise network elements between which a control plane connection is established and/or network elements between which a user plane connection is established” (See ZHANG Fig. 4A, [0128] It should be noted that the CU 122 may be further split into CU control plane (CU-CP) and CU user plane (CU-UP)). [0129] The A-plane 410 enables secure exchange of AI-related information, separate from the existing control plane and data plane communications).
Regarding claim 18,
ZHANG in view of ZHANG ‘111 discloses “The communication apparatus according to claim 10, wherein the Al data stream comprises at least one of: input data of an Al model; model parameters of the Al model; a final result output by the Al model; an intermediate result output by the Al model; or configuration parameters of the Al model” (See ZHANG [0129] It should be noted that, in the present disclosure, AI-related data that may be communicated to the network node 131 (e.g., from the UE 110 and/or system node 120) may include raw (i.e., unprocessed or minimally processed) local data (e.g., raw network data) as well as processed local data (e.g., local model parameters, inferred data generated by local AI model(s), anonymized network data, etc..).
Regarding claim 20,
ZHANG in view of ZHANG ‘111 discloses “The method according to claim 1, wherein the third connection supports parsing and modification of content of a data portion in the Al data stream by all the network elements on the transmission path; or the third connection supports parsing and modification of content of a data portion in the Al data stream by a part of the network elements on the transmission path” (See ZHANG [0129] AI-related data that may be communicated to the network node 131 (e.g., from the UE 110 and/or system node 120) may include raw (i.e., unprocessed or minimally processed) local data (e.g., raw network data) as well as processed local data (e.g., local model parameters, inferred data generated by local AI model(s), anonymized network data, etc.). See Fig. 4B, [0131] As shown in FIG. 4B, the system node 120 may process AI-related data using the AIP layer (e.g., decrypt, process and re-encrypt the data), as an intermediary between the UE 110 and the network node 131). Note: The system node performs modification of the AI data via the AIP layer (third connection) including decrypting, processing and re-encrypting the data. The AIP layer is also implemented at the UE and network node, indicating their ability to also process/ modify the AI data). See ZHANG ‘111 [0136] The AI protocol layer is an independent protocol layer introduced in this embodiment of this application. See Fig. 11 and 19, The AI layer is implemented in a terminal device, an access network device and a core network element. [0244] the AI functions such as generating the AI parameter, receiving and parsing the AI data reported by the terminal device, and completing a network optimization operation based on the AI data are completed by the AI protocol layer of the first access network device). Note: The AI layer (third connection) supports parsing of the AI data.
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to have modified the teachings of ZHANG with the teachings of ZHANG ‘111, by incorporating parsing into the AIP-layer processing of ZHANG, and the motivation to do so would have been to improve efficiency and performance by enabling selective extraction and processing of relevant portions of AI data.
Regarding claim 21,
ZHANG discloses “A chip, comprising: a processor configured to call a program from a memory to cause a device provided with the chip to perform a method applicable to a communication system” (See Fig. 2), “wherein the communication system supports establishments of a user plane-based first connection, a control plane-based second connection” (See Fig. 4A, [0128] It should be noted that the CU 122 may be further split into CU control plane (CU-CP) and CU user plane (CU-UP)), “and a third connection for transmitting an artificial intelligence (Al) data stream for a network element in the communication system” (See Fig. 4A-4B [0129] the A-plane 410 includes higher layer protocols, such as an AI-related protocol (AIP) layer. The AIP may encrypt all communications, ensuring secure transmission of AI-related data. The A-plane 410 enables secure exchange of AI-related information, separate from the existing control plane and data plane communications. Note: The AI-related information is transmitted between the network entities using a third connection (A-plane) that is separate from the existing control and data plane communications), “wherein a plurality of network elements of the communication system are involved on a transmission path of the Al data stream, the third connection is established between the plurality of network elements” (See [0131] As shown in FIG. 4B, the system node 120 may process AI-related data using the AIP layer, as an intermediary between the UE 110 and the network node 131. The system node 120 may make use of the AI-related data from the UE 110. The system node 120 may also simply relay the AI-related data from the UE 110 to the network node 130), “and the plurality of network elements comprise a first network element and a second network element; wherein the first network element comprises a user equipment, the second network element comprises a core network device” (See Fig. 4B, [0131] the AI execution module 220 at the system node 120 is involved in communications between the AI execution module 220 at the UE 110 and the AI management module 210 at the network node 131. As shown in FIG. 4B, the system node 120 may process AI-related data using the AIP layer, as an intermediary between the UE 110 and the network node 131. The system node 120 may also simply relay the AI-related data from the UE 110 to the network node 130. [0072] the network node 131 is within the core network 130); “and the method comprises: sending to or receiving from the second network element, by the first network element, the Al data stream over the third connection” (See [0131] The system node 120 may also simply relay the AI-related data from the UE 110 to the network node 130); “and the third connection supports modification of content of a data portion in the Al data stream by all or part of the plurality of network elements on the transmission path” (See [0129] AI-related data that may be communicated to the network node 131 (e.g., from the UE 110 and/or system node 120) may include raw (i.e., unprocessed or minimally processed) local data (e.g., raw network data) as well as processed local data (e.g., local model parameters, inferred data generated by local AI model(s), anonymized network data, etc.). See Fig. 4B, [0131] As shown in FIG. 4B, the system node 120 may process AI-related data using the AIP layer (e.g., decrypt, process and re-encrypt the data), as an intermediary between the UE 110 and the network node 131). Note: The system node performs modification of the AI data via the AIP layer (third connection) including decrypting, processing and re-encrypting the data. The AIP layer is also implemented at the UE and network node, indicating their ability to also process/ modify the AI data).
ZHANG does not explicitly disclose the third connection supports parsing of a data portion in the AI data stream.
However, ZHANG ‘111 discloses “and the third connection supports parsing of a data portion in the Al data stream by all or part of the plurality of network elements on the transmission path” (See [0136] The AI protocol layer is an independent protocol layer introduced in this embodiment of this application. See Fig. 11 and 19, The AI layer is implemented in a terminal device, an access network device and a core network element. [0244] the AI functions such as generating the AI parameter, receiving and parsing the AI data reported by the terminal device, and completing a network optimization operation based on the AI data are completed by the AI protocol layer of the first access network device). Note: The AI layer (third connection) supports parsing of the AI data.
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to have modified the teachings of ZHANG with the teachings of ZHANG ‘111, by incorporating parsing into the AIP-layer processing of ZHANG, and the motivation to do so would have been to improve efficiency and performance by enabling selective extraction and processing of relevant portions of AI data.
Regarding claim 22,
ZHANG in view of ZHANG ‘111 discloses “The method according to claim 1, wherein the plurality of network elements on the transmission path comprise an intermediate network element, wherein the intermediate network element forwards the Al data stream to a next network element over the third connection” (See Fig. 4A, [0130] The communications between the UE 110 and the network node 131 over the A-plane 410 may be forwarded by the system node 120 in a completely transparent manner. See Fig. 4B, [0131] the system node 120 may process AI-related data using the AIP layer as an intermediary between the UE 110 and the network node 131, or simply relay the AI-related data from the UE 110 to the network node 130).
Regarding claim 23,
ZHANG in view of ZHANG ‘111 discloses “The method according to claim 1, wherein the plurality of network elements on the transmission path are configured with operation behavior comprising at least one of: parsing and modification of content of the data portion in the Al data stream, or forwarding the Al data stream” (See [0131] As shown in FIG. 4B, the system node 120 may process AI-related data using the AIP layer (e.g., decrypt, process and re-encrypt the data), as an intermediary between the UE 110 and the network node 131. The system node 120 may make use of the AI-related data from the UE 110 (e.g., to perform training of a local AI model at the system node 120. The system node 120 may also simply relay the AI-related data from the UE 110 to the network node 130).
Claims 2-3 and 11-12 are rejected under 35 U.S.C. 103 as being unpatentable over ZHANG et al. (US 20230319585 A1) in view of ZHANG et al. (US 20220322111 A1) and further in view of Tanach et al. (US 20230130964 A1).
Regarding claims 2 and 11,
ZHANG in view of ZHANG ‘111 discloses claim 2 of “The method according to claim 1”, and claim 11 of “The communication apparatus according to claim 10”, but does not explicitly disclose a header portion of the AI data stream comprising parameters.
However, Tanach discloses “wherein a data packet of the Al data stream comprises a
header portion and a data portion” (See Fig. 2), “wherein the header portion comprises
one or more of: a first parameter indicative of a source network element of the Al data
stream; a second parameter indicative of a destination network element of the Al data
stream” (See [0047] The header portion 210 includes a number of fields designating, in part,
the AI task type, the length of the payload data, a source address (or identifier), and
a destination address (or identifier). [0060] FIG. 6 illustrates an example flow diagram
illustrating the dataflow between an AI client 120 and an AI server 130 using the AIoF
protocol to transport AI computing tasks according to an embodiment).
ZHANG in view of ZHANG ‘111 discloses using a third connected for transmitting AI data between network elements, but does not disclose header addressing, and Tanach discloses including a source and destination addresses in the header of an AI packet for routing between an AI client and an AI server. A POSITA would understand an AI client or AI server to be a type of network element that participates in network communication.
Therefore, it would have been obvious to a person of ordinary skill in the art before the
effective filing date of the claimed invention to have modified the teachings of ZHANG and ZHANG ‘111 with the teachings of Tanach, to incorporate the addressing mechanism into the AI packet structure, and the motivation to do so would have been to facilitate correct routing of AI data between network elements.
Regarding claims 3 and 12,
ZHANG in view of ZHANG ‘111 discloses claim 3 of “The method according to claim 2”, and claim 12 of “The communication apparatus according to claim 11”, “wherein there is at least one of: the first parameter is an address of the source network element; or the second parameter is an address of the destination network element” (See Tanach [0047] The header portion 210 includes a number of fields designating, in part, the AI task type, the
length of the payload data, a source address (or identifier), and a destination address (or
identifier). [0060] FIG. 6 illustrates an example flow diagram illustrating the dataflow
between an AI client 120 and an AI server 130 using the AIoF protocol to transport AI
computing tasks according to an embodiment).
ZHANG in view of ZHANG ‘111 discloses using a third connected for transmitting AI data between network elements, but does not disclose header addressing, and Tanach discloses including a source and destination addresses in the header of an AI packet for routing between an AI client and an AI server. A POSITA would understand an AI client or AI server to be a type of network element that participates in network communication.
Therefore, it would have been obvious to a person of ordinary skill in the art before the
effective filing date of the claimed invention to have modified the teachings of ZHANG and ZHANG ‘111 with the teachings of Tanach, to incorporate the addressing mechanism into the AI packet structure, and the motivation to do so would have been to facilitate correct routing of AI data between network elements.
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.
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/SALMA AYAD/Examiner, Art Unit 2462 /YEMANE MESFIN/Supervisory Patent Examiner, Art Unit 2462
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