The present disclosure describes techniques for adding a marker to a second document, the marker corresponding to a marker in a first document. The process may include identifying a token in a first document associated with a marker based upon a location of the marker in the first document. The process may further include identifying a particular token group that the token belongs to. The particular token group may be identified from a set of token groups for the first document. A particular token group from a set of token groups for the second document is then identified for the particular token group in the first document. A location for placing the marker in the second document is identified based upon the location of the particular token group in the second document. The marker is then placed in the second document at the identified location.

A method of pervasive memory augmentation includes receiving a request to augment a memory via a heads-up display having a field of view and generating one or more processor-readable memory cues that are connected to the memory. A cued content is generated based on the one or more processor-readable memory cues. The cued content is presented in a display space in the field of view of the heads-up display on a spaced repetition schedule.

A method of pervasive memory augmentation includes receiving a request to augment a memory via a heads-up display having a field of view and generating one or more processor-readable memory cues that are connected to the memory. A cued content is generated based on the one or more processor-readable memory cues. The cued content is presented in a display space in the field of view of the heads-up display on a spaced repetition schedule.

Disclosed in some examples are methods, systems, devices, and machine-readable mediums that provide an ability for an entity to independently commence, advance, and complete a resource allocation offer in a matter of minutes as opposed to weeks or months after an automated resource pre-committal process. The system, using and incorporating machine learning techniques and algorithms, may have several phases, including a setup phase, resource pre-committal phase, an import phase, a processing phase, a verification phase, a resource allocation offer phase, and a resource allocation phase in which the system allocates resources to a vendor.

Disclosed in some examples are methods, systems, devices, and machine-readable mediums that provide an ability for an entity to independently commence, advance, and complete a resource allocation offer in a matter of minutes as opposed to weeks or months after an automated resource pre-committal process. The system, using and incorporating machine learning techniques and algorithms, may have several phases, including a setup phase, resource pre-committal phase, an import phase, a processing phase, a verification phase, a resource allocation offer phase, and a resource allocation phase in which the system allocates resources to a vendor.

A computer implemented method includes receiving text data, detecting auto-generated text in the received text data to identify tags in the received text to distinguish between the auto-generated text and user generated text, and providing the tagged text data to a machine learning language model.

A computer program product, for automatically editing a medical record transcription, resides on a computer-readable medium and includes computer-readable instructions for causing a computer to obtain a first medical transcription of a dictation, the dictation being from medical personnel and concerning a patient, analyze the first medical transcription for presence of a first trigger phrase associated with a first standard text block, determine that the first trigger phrase is present in the first medical transcription if an actual phrase in the first medical transcription corresponds with the first trigger phrase, and insert the first standard text block into the first medical transcription.

A system for detecting service issues within multi-sourced service data. The system includes a memory and one or more electronic processors coupled to the memory. The electronic processors are configured to receive one or more data sets in near real time, and to enrich the dataset with one or more metadata parameters, pre-clean the data within the dataset, and determine one or more data points within the dataset that are semantically similar to each other. The electronic processors are also configured to generate a similarity score for each of the semantically similar data points, and determine one or more significant clusters within the dataset within a predefined lookback window. The electronic processors are also configured to analyze the determined significant clusters to determine the existence of one or more service issues, and generate a service alert based on the analysis determining that one or more service issues are present.

A system for detecting service issues within multi-sourced service data. The system includes a memory and one or more electronic processors coupled to the memory. The electronic processors are configured to receive one or more data sets in near real time, and to enrich the dataset with one or more metadata parameters, pre-clean the data within the dataset, and determine one or more data points within the dataset that are semantically similar to each other. The electronic processors are also configured to generate a similarity score for each of the semantically similar data points, and determine one or more significant clusters within the dataset within a predefined lookback window. The electronic processors are also configured to analyze the determined significant clusters to determine the existence of one or more service issues, and generate a service alert based on the analysis determining that one or more service issues are present.

In one aspect, a device may include a processor and storage accessible to the processor. The storage may include instructions executable by the processor to receive at least one image that indicates a first gesture being made by a person using a hand-based sign language, with at least part of the first gesture extending out of the image frame of the image. The instructions may then be executable to provide the image to a gesture classifier and to receive plural candidate first text words for the first gesture from the gesture classifier. The instructions may then be executable to use at least a second text word correlated to a second gesture to select one of the candidate first text words, combine the second text word with the selected first text word to establish a text string, and provide the text string to an apparatus different from the device.