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Liquid Mode taps Adobe's AI engine, Sensei, to analyze a PDF and automatically rebuild it for mobile devices. After a few months of quiet testing, Liquid Mode is being publicly rolled out in Adobe ...
Document AI combines text data, which has a time dimension, with other types of data, such as the position of an address in a business letter, which is spatial. Historically in machine learning spatial data was analyzed using a convolutional neural network , and temporal data using a recurrent neural network .
AIDC is the process or means of obtaining external data, particularly through the analysis of images, sounds, or videos. To capture data, a transducer is employed which converts the actual image or a sound into a digital file. The file is then stored and at a later time, it can be analyzed by a computer, or compared with other files in a ...
The Computer Go Room on the K Go Server (KGS) for online discussion and running "bots" Two Representative Computer Go Games, an article about two computer Go games played in 1999, one with two computers players, and the other a 29-stone handicap human-computer game; What A Way to Go describes work at Microsoft Research on building a computer Go ...
an Office suite; allows to export (and import, with accuracy limitations) PDF files. Microsoft Word 2013: Proprietary: Desktop software. The 2013 edition of Office allows PDF files to be converted into a format that can be edited. Nitro PDF Reader: Trialware: Text highlighting, draw lines and measure distances in PDF files. Nitro PDF Pro ...
writing computer code based on requirements expressed in natural language. speech-to-text; Beyond traditional NLP, the transformer architecture has had success in other applications, such as: biological sequence analysis; video understanding; protein folding (such as AlphaFold) evaluating chess board positions.
As AI begins to seep into our daily lives, new technology from Microsoft, Zoom, and Google now allows people to skip Zoom meetings and send robot notetakers on their behalf.
Machine-readable data must be structured data. [1]Attempts to create machine-readable data occurred as early as the 1960s. At the same time that seminal developments in machine-reading and natural-language processing were releasing (like Weizenbaum's ELIZA), people were anticipating the success of machine-readable functionality and attempting to create machine-readable documents.
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