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
The Action is responsive to the Amendments and Remarks filed on 10/29/2025 included in the Request for Continued Examination filed on 12/30/2025. Claims 1-21 are pending claims. Claims 1, 8, and 15 are written in independent form.
Comments - 35 USC § 101
It is noted that when analyzing Claim 1 under 35 USC 101, the claim is understood as necessarily being directed to one of the eligible categories of subject matter when reciting an apparatus comprising an interface circuitry and programmable circuitry to perform the claimed steps because the specification specifically states “The interface circuitry 820 may be implemented by hardware in accordance with any type of interface standard, such as an Ethernet interface, a universal serial bus (USB) interface, a Bluetooth® interface, a near field communication (NFC) interface, a Peripheral Component Interconnect (PCI) interface, and/or a Peripheral Component Interconnect Express (PCIe) interface” (Spec. Para. [0091]) and “As used herein, “programmable circuitry” is defined to include any circuitry that can be programmed or configured to perform different operations and that includes one or more semiconductor-based logic devices” (Spec. Para. [0116]).
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim(s) 1-21 are rejected under 35 U.S.C. 103 as being unpatentable over Statton et al. (U.S. Pre-Grant Publication No. 2024/0370339, hereinafter referred to as Statton) and further in view of Huang et al. (U.S. Pre-Grant Publication No. 2017/0371978, hereinafter referred to as Huang) and Topatan et al. (U.S. Pre-Grant Publication No. 2010/0185650, hereinafter referred to as Topatan).
Regarding Claim 1:
Statton teaches an apparatus comprising:
Interface circuitry in communication with a storage system and a vector index database, wherein the interface circuitry is configured to access a difference report indicative of at least one change between a first snapshot of an input data set in a storage system at a first time and a second snapshot of the input data set in the storage system at a second time;
Statton teaches “Interface module 240 of storage system 105 may execute an interface by which other systems or devices may create, modify, delete, and/or delete backup data for backups 142.” (Para. [0062]) where “Chunks are written into chunkfiles at different offsets. By comparing new chunk IDs to the chunk table, backup manager 154 can determine if the data already exists on the system” (Para. [0057]) and “while the techniques of this disclosure are described primarily with respect to retrieving backup data stored to a secondary storage system, the techniques may be applied with respect to any data stored as a form of backup data to any storage system. For example, backup data can include archive data, replicated data, mirrored data, or snapshots.” (Para. [0033]).
Therefore, Statton teaches accessing a report indicative of at least one change between snapshots of input data at a first and second time.
Machine-readable instructions (Para. [0011]); and
Programmable circuitry to be programmed by the machine-readable instructions to (Para. [0011]):
Load a document of the input data set from the storage system via the interface circuitry;
Statton teaches “One or more communication units 215 of computing system 202 may communicate with devices external to computing system 202 by transmitting and/or receiving data, and may operate, in some respects, as both an input device and an output device.” (Para. [0051]) where “An embedding is a numerical-typically a vector-representation of a piece of information, for example, text, documents, images, audio, etc.” (Para. [0072]) and “Index of embeddings 164 may adhere to a RBAC model allowing for access control over read, write, update, and deletion of the index at a role-level” (Para. [0072]) and “Database layer 320 is configured to insert new entries of vectors/embeddings into embeddings 164” (Para. [0104]). Therefore, Statton teaches loading via communication units pieces of informaiotn (text, documents
Generate a first vector embedding in the vector index database, the first vector embedding corresponding to a first chunk of the document of the input data set;
Statton teaches “generate index of embeddings 164 (sometimes referred to as an embeddings database)” and “Index of embeddings 164 may adhere to a RBAC model allowing for access control over read, write, update, and deletion of the index at a role-level” (Para. [0072]) where “Database layer 320 is configured to insert new entries of vectors/embeddings into embeddings 164” (Para. [0104]).Statton further teaches different portions of the index of embeddings by teaching “Index of embeddings 164 may be per-tenant, per-account, or per-user,” (para. [0103]).
update the vector index database by re-indexing the first vector embedding in the vector index database;
Statton teaches “generate index of embeddings 164 (sometimes referred to as an embeddings database)” and “Index of embeddings 164 may adhere to a RBAC model allowing for access control over read, write, update, and deletion of the index at a role-level” (Para. [0072]) where “Database layer 320 is configured to insert new entries of vectors/embeddings into embeddings 164” (Para. [0104]).Statton further teaches different portions of the index of embeddings by teaching “Index of embeddings 164 may be per-tenant, per-account, or per-user,” (para. [0103]). Therefore, Statton teaches re-indexing a first portion of the index of embeddings.
Cause sending of an updated index object application programming interface (API) name of the updated vector index database in a refresh notification to a large language model (LLM) query engine and
Statton teaches “By leveraging the robust file system 153, data platform 150 incorporating response generation platform 158 incorporates (or enables) ‘AI Ready’ for RAG-assisted large language models (LLMs) through an on-demand index of embeddings 164 that are provided just-in-time to the application requesting the data. The data may be secured through RBAC control models.” (Para. [0077]). Therefore, Statton teaches on-demand index of embeddings provided to applications requesting data for Rag-assisted LLMs.
Statton alsoteaches “metadata information describing the backup data, such as file names, sizes, timestamps, and backup versions” (Para. [0004]) thereby teaching tracking the data over time, and “Backup manager 154 may generate and manage chunk metadata 220 for generating, viewing, retrieving, or restoring objects stored as chunks (and references thereto) within chunkfiles, for any of backups 142. Stored objects may be represented and manipulated using logical files for identifying chunks for the objects.” (Para. [0057]) where “Interface module 240 of storage system 105 may execute an interface by which other systems or devices may create, modify, delete, and/or delete backup data for backups 142. Interface module 240 may execute and present an API.” (Para. [0062]), thereby teaching an index having an object name related to an API for creation, modification, and/or deletion, and “By leveraging the robust file system 153, data platform 150 incorporating response generation platform 158 incorporates (or enables) ‘AI Ready’ for RAG-assisted large language models (LLMs) through an on-demand index of embeddings 164 that are provided just-in-time to the application requesting the data. The data may be secured through RBAC control models.” (Para. [0077]).
Cause the LLM query engine to access the updated vector index database via the interface circuitry based on a query and the updated index object API name.
Statton teaches “the index of embeddings 164 is provided, along with the original query, to the Language Model (such as GPT4) (e.g., model 322) to enable query processor 321 to provide a context-aware response 332.” (Para. [0078]) where the most recent index object API name is used by teaching “By leveraging the robust file system 153, data platform 150 incorporating response generation platform 158 incorporates (or enables) ‘AI Ready’ for RAG-assisted large language models (LLMs) through an on-demand index of embeddings 164 that are provided just-in-time to the application requesting the data. The data may be secured through RBAC control models.” (Para. [0077]).
Statton explicitly teaches all of the elements of the claimed invention as recited above except:
Generate a second vector embedding in the vector index database, the second vector embedding corresponding to a second chunk of the document of the input data set, the first chunk corresponding to one or more first words in the document, the second chunk corresponding to one or more second words in the document, the one or more second words separate from the one or more first words;
In response to the at least one change indicated in the difference report, update the vector index database by re-indexing the first vector embedding in the vector index database without re-indexing the second vector embedding in the vector index database;
However, in the related field of endeavor of managing a document index, Huang teaches:
Generate a second vector embedding in the vector index database, the second vector embedding corresponding to a second chunk of the document of the input data set, the first chunk corresponding to one or more first words in the document, the second chunk corresponding to one or more second words in the document, the one or more second words separate from the one or more first words;
Huang teaches a document being separated into different segments or chunks that represent different words in the document (Para. [0025]-[0026] & Fig. 5A) and Statton teaches “An embedding is a numerical-typically a vector-representation of a piece of information, for example, text, documents, images, audio, etc.” (Para. [0072]) and “Index of embeddings 164 may adhere to a RBAC model allowing for access control over read, write, update, and deletion of the index at a role-level” (Para. [0072]) and “Database layer 320 is configured to insert new entries of vectors/embeddings into embeddings 164” (Para. [0104]).Therefore, Huang in combination with Statton teaches generating multiple vector embeddings, each vector embedding representing different word/text chunks from the same document.
update the vector index database by re-indexing the first vector embedding in the vector index database without re-indexing the second vector embedding in the vector index database;
Huang teaches “When some metadata fields of a document are indexed to the fulltext index, any update to the document would trigger reconstruction of the index for the whole document (including all the metadata fields of the document), which is a waste as the whole document (including all the metadata fields of the document) has to be processed again and again, a majority of which is unnecessary. To at least in part solve the above and other potential problems, example embodiments of the present disclosure provide a solution for managing a document index. The solution divides all the fields of documents into two categories: independently updatable fields and non-independently-updatable fields. An index for an item in an independently updatable field is stored in a specific mariner such that the index for the item in the independently updatable field can be updated without modifying an identifier of a document.” (Paras. [0025]-[0026]).Huang further teaches this in an example edit of Document 1 text resulting in only a partial edit to an index by teaching “FIG. 5B illustrates a schematic diagram of updating a document in the example shown in FIG. 5A according to an embodiment of the present disclosure. Block 521 shows partial modification made to document 1, namely, updating document 1 (for example, “marvelous” is replaced with “falling down” in document 1); block 525 shows the index after the document 1 is updated. It can be seen that when receiving a request for updating a document (for example, document 1), the document index management module 140 keeps the identifier of document 1 unmodified, which is contrary to the example shown in Fig, 2B. Specifically, the identifier of updated document 1 is still “document 1”. In this way, it is only necessary to modify indexes for a deleted item (for example, “marvelous”) and added items (for example, “falling” and “down”) in the field. For a deleted item (for example, “marvelous”), modifying the index includes deleting the identifier of document 1 from the index for the item “marvelous” and for an added item (for example, “falling” or “down”), modifying the index includes adding the identifier of document I into a corresponding block of the index for the item “falling” or “down”, Furthermore, thanks to the identifier of the document not being modified, it is unnecessary to make any modifications to an index for an item in fields apart from the content field shown by block 521, for instance, it is unnecessary to modify an index for an item in the author field. Therefore, the number of indexes for items that should be modified is reduced significantly, thereby improving the efficiency of document updating.” (Paras. [0058-[0059] & Fig. 5B).
Thus, it would have been obvious to one of ordinary skill in the art, having the teachings of Huang and Statton at the time that the claimed invention was effectively filed, to have modified the systems and methods for data retrieval using embeddings, as taught by Statton, with the partial modification of indexes when documents are edited, as taught by Huang.
One would have been motivated to make such modification because Huang teaches “When some metadata fields of a document are indexed to the fulltext index, any update to the document would trigger reconstruction of the index for the whole document (including all the metadata fields of the document), which is a waste as the whole document (including all the metadata fields of the document) has to be processed again and again, a majority of which is unnecessary.” (Para. [0025]).
Huang and Statton explicitly teach all of the elements of the claimed invention as recited above except:
In response to the at least one change indicated in the difference report, update the vector index database by re-indexing the first vector embedding in the vector index database without re-indexing the second vector embedding in the vector index database;
However, in the related field of endeavor of indexing and searching dynamically changing search corpora, Topatan teaches:
In response to the at least one change indicated in the difference report, update the vector index database by re-indexing the first vector embedding in the vector index database without re-indexing the second vector embedding in the vector index database;
Topatan teaches “as new uploaded documents arrive at the indexing and searching system 110, as uploaded documents are removed, deleted, or modified,… the system 110 may update the online document and index storage elements 122” (Para. [0065]) thereby teaching using indicated change indicators such as “removed, deleted, or modified” to “update the online document and index storage elements”.
Statton teaches “Index of embeddings 164 may adhere to a RBAC model allowing for access control over read, write, update, and deletion of the index at a role-level” (Para. [0072]) and “database layer 320 is configured to insert new entries of vectors/embeddings into embeddings 164” (Para. [0104]). Therefore, Statton teaches causing an update to the index of embeddings 164.
Huang teaches updating only a portion of a document related to an edit/modification (Pars. [0058]-]0059] & Fig. 5B).
Therefore, Topatan in combination with Huang and Statton teach causing an update to the index of embeddings, taught by Statton, in response to an indicator that “uploaded documents are removed, deleted, or modified” causing “the system 110 [to] update the online document and index storage elements”, taught by Topatan, where the update is only applied to particular portions of the index related to the document without affecting other portions of the index related to the same document, as taught by Huang.
Thus, it would have been obvious to one of ordinary skill in the art, having the teachings of Topatan, Huang, and Statton at the time that the claimed invention was effectively filed, to have modified the partial modification of indexes when documents are edited, as taught by Huang, and the systems and methods for data retrieval using embeddings, as taught by Statton, with the various permission levels for accessing stored content, as taught by Topatan.
One would have been motivated to make such combination because Statton teaches a role-based access controls (RBAC) that “prevents users from accessing data they don't have permissions for” (Para. [0071]) and Topatan provides further detail and more nuanced choices in share permission options including “do not share”, “share with individual(s)”, “share with group”, “share with domain”, and “share publicly” (Paras. [0030]-[0034] & Fig. 2 Elements 214-222). It would have been obvious to a person having ordinary skill in the art that providing different permission choices for sharing access would increase the flexibility of users to pick the optimal permission settings for them and the stored data taught by Statton.
Regarding Claim 2:
Topatan, Huang, and Statton further teach:
The programmable circuitry is to update the vector index database by:
Comparing a first checksum of the first chunk of the at least one document corresponding to a third time with a second checksum of a third chunk of the at least one document corresponding to a fourth time; and
Statton teaches “by comparing new chunk IDs to the chunk table, backup manager 154 can determine if the data already exists on the system. If the chunks already exist, data can be discarded and metadata for an object updated to reference the existing chunk.” (Para. [0057]).
Statton further teaches “Chunk metadata 220 may include a chunkfile table that describes respective physical or virtual locations of chunkfiles on storage system 115, along with other metadata about the chunkfile, such as a checksum, encryption data, compression data, etc.” (Para. [0059]) and the “types of data may be..according to time or dates” (Para. [0066])Therefore, Statton teaches comparing a checksum identifying a chunks at different times.
After determining that the second checksum is different from the first checksum, causing replacement of the first chunk and a corresponding first vector in the vector index database by the third chunk and a corresponding second vector without replacing other chunks of the at least one document in the vector index database.
Statton teaches “Because file system 153 changes over time due to creation of new objects, modification of existing objects, and deletion of objects, backups 142 will differ” and “a given backup of backups 142 may be a full backup or an incremental backup” (Para. [0034]). Statton further teaches “by comparing new chunk IDs to the chunk table, backup manager 154 can determine if the data already exists on the system.” (Para. [0057]) and “Chunk metadata 220 may include a chunkfile table that describes respective physical or virtual locations of chunkfiles on storage system 115, along with other metadata about the chunkfile, such as a checksum, encryption data, compression data, etc.” (Para. [0059]). Therefore, Statton teaches comparing checksum of a new chunk of a modified existing object to another checksum and reflecting the modification of existing objects through the modified chunk(s) without replacing other chunks that have not been modified in order to perform incremental backup at a chunk level.
Regarding Claim 3:
Topatan, Huang, and Statton further teach:
Wherein at least a second change indicated in the difference report is represented by a change indicator in the difference report, the change indicator is indicative of the document having a first name in the input data set at the first time and having a second name in the input data set at the second time,
Statton teaches “metadata information describing the backup data, such as file names, sizes, timestamps, and backup versions” (Para. [0004]) thereby teaching that the documents have names. Statton also teaches “a given backup of backups 142 may be a full backup or an incremental backup” (Para. [0034]) thereby teaching difference reports reflecting modifications/changes between increments.
Topatan teaches “as new uploaded documents arrive at the indexing and searching system 110, as uploaded documents are removed, deleted, or modified,… the system 110 may update the online document and index storage elements 122” (Para. [0065]) thereby teaching using indicated change indicators such as “removed, deleted, or modified” to “update the online document and index storage elements”.
Therefore, Statton in combination with Topatan teaches modifying file names at different timestamps and detecting the modification indicator causing an update to the document identifier in the index storage elements.
The programmable circuitry to generate a third vector embedding for the document by generating an updated document identifier corresponding to the second name of the document.
Statton teaches “metadata information describing the backup data, such as file names, sizes, timestamps, and backup versions” (Para. [0004]) thereby teaching that the documents have names.
Topatan teaches “as new uploaded documents arrive at the indexing and searching system 110, as uploaded documents are removed, deleted, or modified,… the system 110 may update the online document and index storage elements 122” (Para. [0065]) thereby teaching using indicated change indicators such as “removed, deleted, or modified” to “update the online document and index storage elements”.
Therefore, Statton in combination with Topatan teaches modifying file names at different timestamps and detecting the modification causing an update to the document identifier in the index storage elements.
Regarding Claim 4:
Topatan, Huang, and Statton further teach:
Wherein the difference report includes a change indicator indicative of a second document of the input data set at the second time being a modified version relative to the second document in the input data set at the first time,
Statton teaches “metadata information describing the backup data, such as file names, sizes, timestamps, and backup versions” (Para. [0004]) thereby teaching that the documents have different versions. Statton also teaches “a given backup of backups 142 may be a full backup or an incremental backup” (Para. [0034]) thereby teaching difference reports reflecting modifications/changes between increments.
Topatan teaches “as new uploaded documents arrive at the indexing and searching system 110, as uploaded documents are removed, deleted, or modified,… the system 110 may update the online document and index storage elements 122” (Para. [0065]) thereby teaching using indicated change indicators such as “removed, deleted, or modified” to “update the online document and index storage elements”.
Therefore, Statton in combination with Topatan teaches modifying versions at different timestamps and detecting the modification causing an update to the index storage elements, effectively removing and replacing the old version with the modified/new version of the document represented in the embeddings.
The programmable circuitry to cause an update to the vector index database by removing the second document corresponding to the first time and inserting the modified version of the second document in the vector index database.
Statton teaches “metadata information describing the backup data, such as file names, sizes, timestamps, and backup versions” (Para. [0004]) thereby teaching that the documents have different versions. Statton further teaches multiple documents by teaching “An embedding is a numerical-typically a vector-representation of a piece of information, for example, text, documents, images, audio, etc.” (Par. [0072]).
Topatan teaches “as new uploaded documents arrive at the indexing and searching system 110, as uploaded documents are removed, deleted, or modified,… the system 110 may update the online document and index storage elements 122” (Para. [0065]) thereby teaching using indicated change indicators such as “removed, deleted, or modified” to “update the online document and index storage elements”.
Therefore, Statton in combination with Topatan teaches modifying versions at different timestamps and detecting the modification causing an update to the index storage elements, effectively removing and replacing the old version with the modified/new version of the document represented in the embeddings.
Regarding Claim 5:
Topatan, Huang, and Statton further teach:
Wherein the difference report includes a change indicator indicative of a second document in the input data set at the second time that is not in the input data set at the first time,
Statton teaches “metadata information describing the backup data, such as file names, sizes, timestamps, and backup versions” (Para. [0004]) and “Database layer 320 is configured to insert new entries of vectors/embeddings into embeddings 164” (Para. [0104]) thereby teaching an indicator of the input data being new/not existing at a first time and inserting new entries into embeddings 164 at a second time. Statton further teaches multiple documents by teaching “An embedding is a numerical-typically a vector-representation of a piece of information, for example, text, documents, images, audio, etc.” (Par. [0072]).
The programmable circuitry to cause an update to the vector index database by inserting the second document in the vector index database.
Statton teaches “metadata information describing the backup data, such as file names, sizes, timestamps, and backup versions” (Para. [0004]) and “Database layer 320 is configured to insert new entries of vectors/embeddings into embeddings 164” (Para. [0104]) thereby teaching an indicator of the input data being new/not existing at a first time and inserting new entries into embeddings 164 at a second time.
Regarding Claim 6:
Topatan, Huang, and Statton further teach:
Wherein the difference report includes a change indicator indicative that a second document of the input data set at the first time is not in the input data set at the second time,
Statton teaches “metadata information describing the backup data, such as file names, sizes, timestamps, and backup versions” (Para. [0004]) thereby teaching tracking the data over time. Statton further teaches multiple documents by teaching “An embedding is a numerical-typically a vector-representation of a piece of information, for example, text, documents, images, audio, etc.” (Par. [0072]).
Topatan teaches “as new uploaded documents arrive at the indexing and searching system 110, as uploaded documents are removed, deleted, or modified,… the system 110 may update the online document and index storage elements 122” (Para. [0065]) thereby teaching using indicated change indicators such as “removed, deleted, or modified” to “update the online document and index storage elements”.
Therefore, Statton in combination with Topatan teaches removing or deleting documents at different times and detecting the modification causing an update to the index storage elements, effectively removing or deleting the corresponding index storage elements to reflect the removed or deleted documents.
The programmable circuitry to cause an update to the vector index database by removing a document identifier of the second document from the vector index database.
Statton teaches “metadata information describing the backup data, such as file names, sizes, timestamps, and backup versions” (Para. [0004]) thereby teaching tracking the data over time.
Topatan teaches “as new uploaded documents arrive at the indexing and searching system 110, as uploaded documents are removed, deleted, or modified,… the system 110 may update the online document and index storage elements 122” (Para. [0065]) thereby teaching using indicated change indicators such as “removed, deleted, or modified” to “update the online document and index storage elements”.
Therefore, Statton in combination with Topatan teaches removing or deleting documents at different times and detecting the modification causing an update to the index storage elements, effectively removing or deleting the corresponding index storage elements to reflect the removed or deleted documents.
Regarding Claim 7:
Topatan, Huang, and Statton further teach:
Wherein the vector index database includes a first index object API name different from the updated index object API name corresponding to the updated vector index database.
Statton teaches “metadata information describing the backup data, such as file names, sizes, timestamps, and backup versions” (Para. [0004]) thereby teaching tracking the data over time.
Statton further teaches “Backup manager 154 may generate and manage chunk metadata 220 for generating, viewing, retrieving, or restoring objects stored as chunks (and references thereto) within chunkfiles, for any of backups 142. Stored objects may be represented and manipulated using logical files for identifying chunks for the objects.” (Para. [0057]) where “Interface module 240 of storage system 105 may execute an interface by which other systems or devices may create, modify, delete, and/or delete backup data for backups 142. Interface module 240 may execute and present an API.” (Para. [0062]), thereby teaching an index having an object name related to an API for creation, modification, and/or deletion, and “By leveraging the robust file system 153, data platform 150 incorporating response generation platform 158 incorporates (or enables) ‘AI Ready’ for RAG-assisted large language models (LLMs) through an on-demand index of embeddings 164 that are provided just-in-time to the application requesting the data. The data may be secured through RBAC control models.” (Para. [0077]). Therefore, Statton teaches on-demand index of embeddings, that has previously been modified, provided to applications requesting data for Rag-assisted LLMs and including object names related to an API.
Regarding Claim 8:
Some of the limitations herein are similar to some or all of the limitations of Claim 1.
Topatan, Huang, and Statton further teach:
At least one non-transitory machine-readable medium comprising machine-readable instructions to cause at least one processor circuit to perform steps (Statton – Para. [0011]).
Regarding Claim 9:
All of the limitations herein are similar to some or all of the limitations of Claim 2.
Regarding Claim 10:
All of the limitations herein are similar to some or all of the limitations of Claim 3.
Regarding Claim 11:
All of the limitations herein are similar to some or all of the limitations of Claim 4.
Regarding Claim 12:
All of the limitations herein are similar to some or all of the limitations of Claim 5.
Regarding Claim 13:
All of the limitations herein are similar to some or all of the limitations of Claim 6.
Regarding Claim 14:
All of the limitations herein are similar to some or all of the limitations of Claim 7.
Regarding Claim 15:
All of the limitations herein are similar to some or all of the limitations of Claim 1.
Regarding Claim 16:
All of the limitations herein are similar to some or all of the limitations of Claim 2.
Regarding Claim 17:
All of the limitations herein are similar to some or all of the limitations of Claim 3.
Regarding Claim 18
All of the limitations herein are similar to some or all of the limitations of Claim 4.
Regarding Claim 19:
All of the limitations herein are similar to some or all of the limitations of Claim 5.
Regarding Claim 20:
All of the limitations herein are similar to some or all of the limitations of Claim 6.
Regarding Claim 21:
All of the limitations herein are similar to some or all of the limitations of Claim 7.
Response to Amendment
Applicant’s Amendments filed on 10/29/2025 and included in the Request for Continued Examination filed on 12/30/2025, are acknowledged and accepted.
Response to Arguments
On pages 15-17 of the Remarks filed on 10/29/2025, Applicant argues, with respect to the amended claims and Step 2A, Prong 2 of the 101 Analysis, that “even if independent claim 1 does recite a judicial exception (a point not conceded), claim 1 as a whole integrates the judicial exception into a practical application. As noted above, independent claim 1 defines operations of programmable circuitry interacting with a storage system, an interface circuitry, a database, and an LLM query engine to cause the LLM query engine to access the updated vector index database via the interface circuitry based on a query and an updated index object API name. Accordingly, claim 1 as a whole is directed to a practical application in the areas of computers, databases, storage systems, and LLMs.”Upon further time spent considering the filed claim amendments and in light of Applicant’s arguments, it was determined that the claim amendments overcome the 35 U.S.C. § 101 rejection and thus, the 35 U.S.C. § 101 rejection of claims 1-21 as being directed to an abstract idea without significantly more has been withdrawn.
On pages 20-22 of the Remarks filed on 10/29/2025, Applicant argues, with respect to the 103 rejection, that “The alleged Statton/Topatan combination does not teach or suggest” the amended limitations because “Statton describes that file system data includes objects and that "Objects that are stored may include files, virtual machines, databases, applications, pods, container, any of workloads 154, system images, directory information, or other types of objects used by application system 102." Statton, para. [0030]. Statton describes that objects "may also be referred to as 'backup objects'…accordingly, the embeddings of Statton correspond to objects such as text, documents, images, audio, etc.” and “In connection with FIG. 3, Statton describes two embeddings depicted as hashed circles in a backup. Id. at para. [0073] ("Two embeddings are shown as generated from data objects (hashed circles) in backups 142, but index of embeddings 164 may have many millions of embeddings."). As such, embeddings in Statton have a one-to-one correspondence with a corresponding data object, such as a document. Statton does not teach or suggest a "first vector embedding corresponding to a first chunk of the document of the input data set" and a "second vector embedding corresponding to a second chunk of the document of the input data set, the first chunk corresponding to one or more first words in the document, the second chunk corresponding to one or more second words in the document," as set forth in claim 1.”Applicant’s argument is convincing the Statton nor Topatan teach all of the amended limitations, thus necessitating the new grounds of rejection presented above.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Behnen et al. (U.S. Pre-Grant Publication No. 2015/0363483) teaches populating text indexes with partial index update operations that process new sets of documents or incremental changes to a set of documents.
Lyle et al. (U.S. Patent No. 8,417,679) teaches updating an index is disclosed. An indication of one or more changes to be made to data is received. The one or more changes are written to a storage medium prior to updating one or more file name index entries. One or more file name index entries are updated prior to writing a new index tree root. A new index tree root is written.
Randall (U.S. Pre-Grant Publication No. 2010/0241621) teaches The scheduler is configured to process each document identifier in a set of the document identifiers by determining a content change frequency of the document corresponding to the document identifier, determining a first score for the document identifier that is a function of the determined content change frequency of the corresponding document, comparing the first score against a threshold value, and scheduling the corresponding document for indexing based on the results of the comparison.The reference further teaches “The Content Checksum 308 can be used to determine whether the content of a web page has changed. When web pages have identical content, they will also have the same Content Checksum 308. The URL scheduler 202 can compare these content fingerprints 308 with previous content fingerprints obtained for the corresponding URL (e.g., identified by URL FP 302 in the history log record 300) on a previous crawl to ascertain whether the web page has changed since the last crawl.” (Para. [0032]).
Sharma et al. (U.S. Pre-Grant Publication No. 2015/0293960) teaches maintaining the consistency of an index of a database. The real-time index system can receive data associated with an inconsistency detected in the index, compute an index key value from the received data, and obtain the index record and data record associated with the computed index key value. The real-time index system can further compare the data in the data record with the corresponding data in the index record to identify a mismatch in data between the data in the index record and the data in the data record. The real-time index system can maintain the consistency of the index by modifying a portion of data in the index record to be consistent with a corresponding portion of data in the data record.The reference further teaches “ When the real-time index system receives an update data from the database in response to a change in data of a data record stored in the database table, the real-time index system obtains the index record associated with the data record using an index key value included in the update data.” (Para. [0021]).
Gupta et al. (U.S. Patent No. 10,013,440) teaches portions of the index structure may be selected for updating, and an updated version of the portion of the index structure generated in another storage location different than a current storage location for the index structure such that the index structure may be searched in order to perform access requests. Updating the portion of the index structure may include compacting the portion of the index structure and/or merging the portion of the index structure with a sub-index structure generated from a portion of a log of index updates that may be maintained. The current portion of the index structure may then be replaced with the updated version of the current portion so that the updated version may be evaluated when searches of the index structure are performed.
Neagovici-Negoescu et al. (U.S. Pre-Grant Publication No. 2006/0074911) teaches a change log stored in a database to batch index documents for search queries. The content of the site is batched and shipped in bulk from the server to an indexer. The change log keeps track of the changes to the content of the site. The indexer incrementally requests updates to the index using the change log and batches the changes so that the bandwidth usage and processor overhead costs are reduced.
Bai et al. (U.S. Pre-Grant Publication No. 2012/0317105) teaches updating an index and sequencing search results based on the updated index in a terminal. The method comprises: retrieving whether there is any modification in a file; if there is any modification in the file, performing an increment index the modified file to generate new index file, wherein the increment index includes a number of times that the modified file is selected historically; merging the new index file into the original index file; obtaining key words input by the user; querying the search results related to the key words, sequencing the search results according to the relevance between the search results and the key words and the number of times that the modified file is selected historically and displaying the sequenced search results to the user. By the present invention, the user experience of the mobile terminal is improved.
Bloomfield (U.S. Pre-Grant Publication No. 2014/0046949) teaches new text associated with an updated document is compared with existing embedded index items within the updated document and with existing contextual text within the updated document associated with the existing embedded index items. A determination is made as to whether any of the new text includes candidate text for at least one new index item that is not already indexed within the existing embedded index items using a contextual index compendium including contextual index item generation rules and the existing contextual text within the updated document associated with the existing embedded index items. At least one new index item is generated, using the contextual index item generation rules, in response to determining that at least one portion of the new text includes the candidate text that is not already indexed within the existing embedded index items.
Kumar et al. (U.S. Pre-Grant Publication No. 2014/0236962) teaches systems and methods for regularly updating portions of a merged index are provided. Initially, upon receiving an indication that modifications have occurred to content of web-based documents, dynamic update of index (DUI) objects that identify the documents and expose the modified content are composed by ascertaining relative positions of the modified content within the documents, and packaging identifiers of the documents, the relative positions, and metadata underlying the modified content into a message. The DUI objects are applied to an overloading index that maintains structured records of recent modifications. In particular, portions of the overloading index are targeted utilizing the document identifiers and the relative positions specified by the DUI object, thereby updating the targeted portions within the overloading index corresponding to the modified content without rewriting the entire overloading index. Periodically, an association process is invoked for grouping the merged index with the overloading index for search purposes.The reference further teaches “the updated overloading index 330 is generated, as discussed above, upon applying just those recent modifications to the set of documents, such as updated metadata, to the targeted portions of the merged index. Because, the entire overloading index 335 is not replaced, and because only the updated information is applied, which in many cases may be a very small portion of the entire merged index, the update process 305 is an intelligent operation that conserves processing time and resources. Accordingly, the update process 305 of the present invention may be invoked more frequently, thereby providing an up-to-date updated overloading index 330 that is responsive to, and reflective of, changes to the set of documents.” (Para. [0059])
Solheim et al. (U.S. Pre-Grant Publication No. 2015/0370791) teaches indexing and searching features including the use of a configurable schema as part of providing partial update support of one or more aspects of an electronic document or documents, but are not so limited. In an embodiment, a system is configured to provide search services including partial update functionality based in part on use of a configurable schema to manage partial document updates and/or query processing operations. A method of one embodiment operates to use a configurable schema to define a number of merge sets that group various document attributes based in part on data source, update, and/or usage parameters to provide an efficient partial update mechanism.
Williams (U.S. Pre-Grant Publication No. 2009/0193406) teaches bulk updates of a search index for an information repository. In embodiments, a batched set of update requests is run and a set of documents to be updated based on the set of requests is identified. In embodiments, a bulk update method to use is selected based on an estimate of the cost of performing the bulk update. In embodiments, a bulk update method based on updating only the indexes of the documents to be updated may be used instead of a bulk update method that involves re-indexing the full set of documents in the repository.
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/ROBERT F MAY/Examiner, Art Unit 2154 2/6/2025
/BORIS GORNEY/Supervisory Patent Examiner, Art Unit 2154