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 § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claims 1-20 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Scallie et al. (U.S. Patent Publication No. 2018/0047372).
Regarding claim 1, Scallie discloses one or more processors comprising processing circuitry to (Scallie: 704; Fig. 7 “Processor”): determine one or more counts of one or more nodes corresponding to one or more target attributes (interpreted as nodes are organized/connected into one or more graphs of computation, node = operations/logic)[Scallie: 0037 “encompasses a data path from an output of a node representing a musical feature to the input of a node representing a parametrized visual property of an audio life form .”][Scallie: 0038 “More generally , a data path to an input of a node representing a parameterized visual property of an audio life form may encompass multiple nodes representing musical features .”](teaches a node represents features corresponding to nodes corresponding to attributes), the one or more nodes being arranged in one or more computational graphs [Scallie: 0054 “Nodes in a network may represent events , function calls , flow control operations , variables , etc . that can be used in graphs to define the functionality of the graph and the visual scripting node network that contains the node”](teaches nodes used in graphs) that define one or more behaviors of one or more primitives in a scene (interpreted as the computational graphs define behaviors (how something changes) for one or more primitives (objects) in a scene (virtual environment)) [Scallie: 0054 “visual scripting node networks that define the behavior”]; reserve allocated memory for the one or more computational graphs based at least on the one or more counts [Scallie: 0091 “software instructions contained in main memory”]; and perform one or more scripting operations to produce a graphical representation of at least a portion of the scene (interpreted as perform a script operation that results in a graphical representation (visual output) of at least part of the scene) [Scallie: 0037 “Such processing produces an input value that changes the visual property parameter and causes the audio life form to visibly exhibit the property parameter change .”] (teaches the executed node logic changes a visual property parameter and causes a visible change (graphical)) by executing the one or more computational graphs using the allocated memory (interpreted as use memory to execute the software) [Scallie: 0095 “The software instructions received by main memory 706 may optionally be stored on storage device ( s ) 710 either before or after execution by processor”] (teaches using the memory to execute software).
Regarding claim 2, Scallie discloses the one or more processors of claim 1, wherein the one or more target attributes correspond to one or more identifiers in the one or more nodes of at least one of the computational graphs [Scallie: 0064 “The visual property corresponds to the input data pin labeled “ NewScaleZ ” of node 206 .”][Scallie: 0070 “music features corresponding to the music feature nodes included in the node graph created using the node - based interface”][Scallie: 0037 “a node representing a musical feature”](teaches “NewScaleZ” which is the identifier, further teaches a node graph that includes music feature nodes (nodes identified by music feature they represent)), the one or more nodes defining one or more transformations of target data (interpreted as the node defines operations that transform target data (change/compute/update the data))[Scallie: 0037 “Such processing produces an input value that changes the visual property parameter and causes the audio life form to visibly exhibit the property parameter change”](teaches node network processing produces a value that changes the visual property which is a transformation).
Regarding claim 3, Scallie discloses the one or more processors of claim 1, wherein the one or more target attributes identify one or more target primitives in the one or more computational graphs (interpreted as target attributes (selected property) identify which target primitives (scene objects) being acted on are targeted by the computational graphs)[Scallie: 0038 “To an input of a node representing a parametrized visual property of an audio life form”][Scallie: 0061 “The output of the logic implementing the get node 204 is one of the twelve FFT chromagram values selected by an input index value corresponding to one of the twelve audio life forms”](teaches nodes that represent a parameterized visual property of an audio life form, meaning the attribute (parameterized visual property) is tied to (identifier) a specific scene object/primitive (the audio life form), further teaches selecting a value by an explicitly mechanism where an attribute/parameter input selects/identifies which specific audio life form (primitive) is the target. Thus, the target attributes identify the target primitives in the computational graph context).
Regarding claim 4, Scallie discloses the one or more processors of claim 1, wherein executing the one or more computational graphs is based at least on reading the one or more primitives without copying the one or more primitives into the allocated memory for the one or more computational graphs [Scallie: 0037 “The logic is executed by the A / V presentation platform at runtime to process the input . Such processing produces an input value that changes the visual property parameter and causes the audio life form to visibly exhibit the property parameter change”](teaches runtime execution of a node graph logic which can change the primitives meaning it is reading the primitives and not copying the primitives into the memory is an obvious limitation).
Regarding claim 5, Scallie discloses the one or more processors of claim 1, wherein executing the one or more computational graphs is based at least on overwriting primitive data of the one or more primitives with updated primitive data without copying the updated primitive data from the allocated memory for the one or more computational graphs [Scallie: 0037 “Such processing produces an input value that changes the visual property parameter”](teaches overwriting property parameters which is primitive data, again, not copying the updated data is an obvious limitation).
Regarding claim 6, Scallie discloses the one or more processors of claim 1, wherein the processing circuitry is further to arrange the one or more computational graphs in one or more first data groupings in the allocated memory (interpreted as the processor additionally organizes the computational graphs into data groups that reside in the memory) [Scallie: 0054 “Nodes in a network may represent events , function calls , flow control operations , variables , etc . that can be used in graphs to define the functionality of the graph and the visual scripting node network that contains the node”] [Scallie: 0036 “visual scripting node networks”][Scallie: 0081 “addressing main memory 706 and for transferring data between and among the various components of device 700 .”](teaches that the claimed computational graphs as visual scripting node networks (graphs of nodes/wires used to define behavior) and that is grouping them into a data group which would be stored on the memory) based at least on an arrangement of target primitive data of the one or more target primitives in one or more second data groupings [Scallie: 0076 “The music data frame generally is a data structure containing the extracted music features on a per track and / or per - channel ( left , right , mid ) basis . Thus , the music data frame may contain a separate set of extracted music features for the rhythm track , the bass track , the melody track , the lead track , and the master track .”](teaches a separate set of extract music features which is a second data group) at least partially stored using memory that is not the allocated memory [Scallie: 0086 “one of the mass storage devices 710 ( e . g . , the main hard disk for the device”] (teaches utilizing the hard disk (for storage) which is different from the flash memory used).
Regarding claim 7, Scallie discloses the one or more processors of claim 1, wherein the processing circuitry is further to execute a type resolution based at least on propagating one or more data types through the one or more computational graphs (interpreted as carrying information along node connections) [Scallie: 0055 “ A “ wire ” can represent the flow of execution from one node to another or represent the flow of data from one node to another”](teaches sending data through the node graph system), and to reserve the allocated memory for the one or more computational graphs based at least on the type resolution [Scallie: 0034 “The bit depth of samples in the coded music stream may be , for example , 8 bit , 16 - bit , 20 - bit , 24 - bit , 32 - bit floating point , etc”][Scallie: 0102 “The OS 810 manages low - level aspects of computer operation , including managing execution of processes , memory allocation”](teaches allocating different memory sizes).
Regarding claim 8, Scallie discloses the one or more processors of claim 1, wherein the one or more target attributes are defined by a query (interpreted as target attributes are specified by a query), the query comprising a periodic query (a query that repeats at intervals)[Scallie: 0061 “The output of the logic implementing the get node 204 is one of the twelve FFT chromagram values selected by an input index value corresponding to one of the twelve audio life forms shown in screenshot 100 of FIG . 1 .”] (teaches selecting one value from an array based on an index which is a graph level query selection) [Scallie: 0068 “the plugin 402 receives an event tick from the A / V presentation platform 404 at a rate that is equal to , or substantially equal to , the video frame rate of the A / V presentation platform 404”](teaches repeated frame rate event tick which corresponds to the periodic query), and the processing circuitry is further to update the allocated memory based at least on updated results responsive to the updated query [Scallie: 0070 “Upon receiving an event tick from the A / V presentation platform 404 , the plugin 402 provides a music data frame to the A / V presentation platform 404 via the API”][Scallie: “changes the visual property parameter”](teaches that on each even tick, the system provides a new updated music data frame (updated results), meaning the memory was updated).
Regarding claim 9, Scallie discloses the one or more processors of claim 1, wherein the processing circuitry is comprised in at least one of: a system for performing simulation operations; a system for performing digital twin operations; a system for performing light transport simulation; a system for performing collaborative content creation for 3D assets; a system for performing deep learning operations; a system for performing remote operations; a system for performing real-time streaming; a system for generating or presenting one or more of augmented reality content, virtual reality content, or mixed reality content; a system implemented using an edge device; a system implemented using a robot; a system for generating synthetic data; a system for performing one or more generative AI operations [Scallie: 0052 “In some implementations , an audio life form can be automatically generated by an AI ( Artificial Intelligence )”](only one of these limitations need to be met and Scallie explicitly teaches using generative AI to implement the operations); a system that implements one or more large language models (LLMs); a system that implements one or more vision language models (VLMs); a system incorporating one or more virtual machines (VMs); a system implemented at least partially in a data center; or a system implemented at least partially using cloud computing resources.
Claims 10 and 19 are system and method claims corresponding to claim 1 without any additional limitations. Thus, claims 10 and 19 are rejected for the same reasons as claim 1 above.
Claim 11 is a system claim corresponding to claim 2 without any additional limitations. Thus, claim 11 is rejected for the same reasons as claim 2 above.
Claim 12 is a system claim corresponding to claim 3 without any additional limitations. Thus, claim 12 is rejected for the same reasons as claim 3 above.
Claim 13 is a system claim corresponding to claim 4 without any additional limitations. Thus, claim 13 is rejected for the same reasons as claim 4 above.
Claim 14 is a system claim corresponding to claim 5 without any additional limitations. Thus, claim 14 is rejected for the same reasons as claim 5 above.
Claim 15 is a system claim corresponding to claim 6 without any additional limitations. Thus, claim 15 is rejected for the same reasons as claim 6 above.
Claim 16 is a system claim corresponding to claim 7 without any additional limitations. Thus, claim 16 is rejected for the same reasons as claim 7 above.
Claim 17 is a system claim corresponding to claim 8 without any additional limitations. Thus, claim 17 is rejected for the same reasons as claim 8 above.
Claims 18 and 20 are system and method claims corresponding to claim 9 without any additional limitations. Thus, claims 18 and 20 are rejected for the same reasons as claim 9 above.
Conclusion
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/AHMED TAHA/Examiner, Art Unit 2613
/XIAO M WU/Supervisory Patent Examiner, Art Unit 2613