We are tokenizing patent ownership. This opens up transactions that simply are not possible today. The special purpose vehicle (SPV) is like a ‘trust’ that exists to hold and execute the patent transactions on the owner side without the owner being involved. The smart contract has self-executing elements and handles trust issues. The invention utilizes artificial intelligence (AI).

Techniques are described herein for enabling autonomous agents to generate conclusive answers. An example of a conclusive answer is text that addresses concerns of a user who is interacting with an autonomous agent. For example, an autonomous agent interacts with a user device, answering user utterances, for example questions or concerns. Based on the interactions, the autonomous agent determines that a conclusive answer is appropriate. The autonomous agent formulates the conclusive answer, which addresses multiple user utterances. The conclusive answer provided to the user device.

Techniques are described herein for enabling autonomous agents to generate conclusive answers. An example of a conclusive answer is text that addresses concerns of a user who is interacting with an autonomous agent. For example, an autonomous agent interacts with a user device, answering user utterances, for example questions or concerns. Based on the interactions, the autonomous agent determines that a conclusive answer is appropriate. The autonomous agent formulates the conclusive answer, which addresses multiple user utterances. The conclusive answer provided to the user device.

A system and method perform cross-modal information retrieval, by generating a graph representing the set of media objects. Each node of the graph corresponds to a media object and is labeled with a set of features corresponding to a text part of the respective media object. Each edge between two nodes represents a similarity between a media part of the two nodes. A first relevance score is computed for each media object of the set of media objects that corresponds to a text-based score. A second relevance score is computed for each media object by inputting the graph into a graph neural network. The first relevance score and the second relevance score are combined to obtain a final ranking score for each media object.

A system and method perform cross-modal information retrieval, by generating a graph representing the set of media objects. Each node of the graph corresponds to a media object and is labeled with a set of features corresponding to a text part of the respective media object. Each edge between two nodes represents a similarity between a media part of the two nodes. A first relevance score is computed for each media object of the set of media objects that corresponds to a text-based score. A second relevance score is computed for each media object by inputting the graph into a graph neural network. The first relevance score and the second relevance score are combined to obtain a final ranking score for each media object.

There is disclosed a computer-implemented method and system for generating a set of training objects for training a machine learning algorithm (MLA) to determine query similarity based on textual content thereof, the MLA executable by the system. The method comprises retrieving, from a search log database of the system, a first query and other queries with associated search results. The method then comprises selecting a subset of query pairs such that: a query difference in queries in the pair is minimized and a results difference in respective search results is maximized.

An improved data structure approach, and corresponding computational systems and methods are described to provide a technical approach that can be used for improving computational performance where a blockchain data structure is being accessed continuously or periodically for validation of recordals of one or more events that have taken place. A hybrid off-chain (or off-contract)/on-chain solution is utilized to provide a mechanism for establishing data linkages between the off-chain (or off-contract) records and on-chain data payloads.

An improved data structure approach, and corresponding computational systems and methods are described to provide a technical approach that can be used for improving computational performance where a blockchain data structure is being accessed continuously or periodically for validation of recordals of one or more events that have taken place. A hybrid off-chain (or off-contract)/on-chain solution is utilized to provide a mechanism for establishing data linkages between the off-chain (or off-contract) records and on-chain data payloads.

Searching for documents includes retrieving objects from a physical media image using a camera from a smartphone, a user selecting a subset of the objects, forming a search query based on the subset of objects, and applying the search query to a search engine to search for the documents. Retrieving objects from a media image may include waiting for a view of the camera to stabilize. Waiting for the view of the camera to stabilize may include detecting changing content of a video flow provided to the camera and/or using motion sensors of the camera to detect movement. Retrieving objects may include the smartphone identifying possible subsets of objects in the media image. The user selecting a subset of the objects may include the smartphone presenting at least some of the possible subsets to the user and the user selecting one of the possible subsets.

Methods, systems, and devices supporting querying disparate data sources are described. Querying disparate data sources may include receiving an input for data stored at a first data source from a plurality of data sources, selecting a first data connector from a plurality of data connectors, wherein the first data connector corresponds to the first data source, and identifying a first query language corresponding to the first data source from a plurality of query languages. Querying the disparate data sources may further include generating a converted query based at least in part on the first query language and retrieving the data from the first data source using the first data connector based at least in part on the converted query.