Abstract: A document capture server receives a document image from a document capture client and processes the image into an electronic document containing textual content. During capture, the document capture server determines a graphical layout of the document, extracts keywords from the document, classifies the document accordingly, and calls an artificial intelligence (AI) platform to gain insights on the textual content. The AI platform analyzes the textual content and returns additional, insightful data such as a sentiment of the textual content. The document capture server can validate the additional data, integrate the additional data in a process or workflow, and/or provide the textual content and the additional data to a content repository or a computing facility operating in an enterprise computing environment. The document capture server can provide validated data to the AI platform to improve future analyses by the AI platform.

Abstract: A summarizer can be invoked by a user to summarize content. Once started, the summarizer can examine the content, determine a main body of the content, extract texts from the main body, concatenate the texts into a text block, and make a call to an artificial intelligence (AI) platform. The call can contain the text block and specify a user-configurable summarization range for summarizing the text block. The AI platform is operable to generate a sentiment of the text block and a summary of the text block in the summarization range and return them to the summarizer. The summarizer, in turn, can instruct an application on the user device to generate a window or page for displaying the sentiment and the summary in the summarization range on the user device, in real time and in context of the content that the user is viewing, reading, or listening.

Abstract: A summarizer can be invoked by a user to summarize content. Once started, the summarizer can examine the content, determine a main body of the content, extract texts from the main body, concatenate the texts into a text block, and make a call to an artificial intelligence (AI) platform. The call can contain the text block and specify a user-configurable summarization range for summarizing the text block. The AI platform is operable to generate a sentiment of the text block and a summary of the text block in the summarization range and return them to the summarizer. The summarizer, in turn, can instruct an application on the user device to generate a window or page for displaying the sentiment and the summary in the summarization range on the user device, in real time and in context of the content that the user is viewing, reading, or listening.

Abstract: The invention relates to methods of tagging analytes in a sample.

Abstract: A document capture server receives a document image from a document capture client and processes the image into an electronic document containing textual content. During capture, the document capture server determines a graphical layout of the document, extracts keywords from the document, classifies the document accordingly, and calls an artificial intelligence (AI) platform to gain insights on the textual content. The AI platform analyzes the textual content and returns additional, insightful data such as a sentiment of the textual content. The document capture server can validate the additional data, integrate the additional data in a process or workflow, and/or provide the textual content and the additional data to a content repository or a computing facility operating in an enterprise computing environment. The document capture server can provide validated data to the AI platform to improve future analyses by the AI platform.

Abstract: A document capture server receives a document image from a document capture client and processes the image into an electronic document containing textual content. During capture, the document capture server determines a graphical layout of the document, extracts keywords from the document, classifies the document accordingly, and calls an artificial intelligence (AI) platform to gain insights on the textual content. The AI platform analyzes the textual content and returns additional, insightful data such as a sentiment of the textual content. The document capture server can validate the additional data, integrate the additional data in a process or workflow, and/or provide the textual content and the additional data to a content repository or a computing facility operating in an enterprise computing environment. The document capture server can provide validated data to the AI platform to improve future analyses by the AI platform.

Abstract: The invention relates to methods of tagging analytes in a sample.

Abstract: A summarizer can be invoked by a user to summarize content. Once started, the summarizer can examine the content, determine a main body of the content, extract texts from the main body, concatenate the texts into a text block, and make a call to an artificial intelligence (AI) platform. The call can contain the text block and specify a user-configurable summarization range for summarizing the text block. The AI platform is operable to generate a sentiment of the text block and a summary of the text block in the summarization range and return them to the summarizer. The summarizer, in turn, can instruct an application on the user device to generate a window or page for displaying the sentiment and the summary in the summarization range on the user device, in real time and in context of the content that the user is viewing, reading, or listening.

Abstract: A summarizer can be invoked by a user to summarize content. Once started, the summarizer can examine the content, determine a main body of the content, extract texts from the main body, concatenate the texts into a text block, and make a call to an artificial intelligence (AI) platform. The call can contain the text block and specify a user-configurable summarization range for summarizing the text block. The AI platform is operable to generate a sentiment of the text block and a summary of the text block in the summarization range and return them to the summarizer. The summarizer, in turn, can instruct an application on the user device to generate a window or page for displaying the sentiment and the summary in the summarization range on the user device, in real time and in context of the content that the user is viewing, reading, or listening.

Abstract: The invention provides a non-invasive technique for the detection and quantification of the immune repertoire, in a biological sample containing a plurality of distinct cell populations. Methods are conducted using sequencing technology to detect and enumerate immune repertoire within a heterogeneous biological sample.

Abstract: The invention relates to methods of tagging analytes in a sample.

Abstract: The invention relates to methods of tagging analytes in a sample.

Abstract: A summarizer can be invoked by a user to summarize content. Once started, the summarizer can examine the content, determine a main body of the content, extract texts from the main body, concatenate the texts into a text block, and make a call to an artificial intelligence (AI) platform. The call can contain the text block and specify a user-configurable summarization range for summarizing the text block. The AI platform is operable to generate a sentiment of the text block and a summary of the text block in the summarization range and return them to the summarizer. The summarizer, in turn, can instruct an application on the user device to generate a window or page for displaying the sentiment and the summary in the summarization range on the user device, in real time and in context of the content that the user is viewing, reading, or listening.

Abstract: A document capture server receives a document image from a document capture client and processes the image into an electronic document containing textual content. During capture, the document capture server determines a graphical layout of the document, extracts keywords from the document, classifies the document accordingly, and calls an artificial intelligence (AI) platform to gain insights on the textual content. The AI platform analyzes the textual content and returns additional, insightful data such as a sentiment of the textual content. The document capture server can validate the additional data, integrate the additional data in a process or workflow, and/or provide the textual content and the additional data to a content repository or a computing facility operating in an enterprise computing environment. The document capture server can provide validated data to the AI platform to improve future analyses by the AI platform.

Abstract: The invention relates to methods of tagging analytes in a sample.

Abstract: The invention relates to methods of tagging analytes in a sample.

Abstract: The invention relates to methods of tagging analytes in a sample.

Abstract: The invention provides a non-invasive technique for the detection and quantification of the immune repertoire, in a biological sample containing a plurality of distinct cell populations. Methods are conducted using sequencing technology to detect and enumerate immune repertoire within a heterogeneous biological sample.

Abstract: The invention relates to methods of tagging analytes in a sample.

Abstract: A method in system for latency buffered scoreboarding in a graphics pipeline of a graphics processor. The method includes receiving a graphics primitive for rasterization in a raster stage of a graphics processor and rasterizing the graphics primitive to generate a plurality pixels related to the graphics primitive. An ID stored to account for an initiation of parameter evaluation for each of the plurality of pixels as the pixels are transmitted to a subsequent stage of the graphics processor. A buffer is used to store the fragment data resulting from the parameter evaluation for each of the plurality of pixels by the subsequent stage. The ID and the fragment data from the buffering are compared to determine whether they correspond to one another. The completion of parameter evaluation for each of the plurality of pixels is accounted for when the ID and the fragment data match and as the fragment data is written to a memory.