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Origin is primarily a GUI software with a spreadsheet front end. Unlike popular spreadsheets like Excel, Origin's worksheet is column oriented. Each column has associated attributes like name, units and other user definable labels. Instead of cell formula, Origin uses column formula for calculations.
Google Sheets – as part of Google Workspace; iRows – closed since 31 December 2006; JotSpot Tracker – acquired by Google Inc. Smartsheet – Online spreadsheet for project management, interactive Gantt, file sharing, integrated with Google Apps [8] Sourcetable [9] – AI spreadsheet that generates formulas, charts, SQL, and analyzes data.
A screenshot of the Coda document editor (2022) Coda is a document editor that uses features from spreadsheets, presentation documents, word processor files, and apps.
[33] [34] Generative AI planning systems used symbolic AI methods such as state space search and constraint satisfaction and were a "relatively mature" technology by the early 1990s. They were used to generate crisis action plans for military use, [35] process plans for manufacturing [33] and decision plans such as in prototype autonomous ...
Sheets’ native file format has been OpenDocument since version two and previously used its own XML format, compressed with ZIP. Sheets also has the ability to import several spreadsheet formats, including XLS ( Microsoft Excel ), Applix Spreadsheet , Quattro Pro , CSV , dBase, Gnumeric , SXC ( OpenOffice.org XML ), Kexi and TXT.
Related: 5 Ways To Use AI To Generate Passive Income. Grammarly. If you aren’t using this AI-powered language tool already, it’s time to start. This free app takes seconds to download and can ...
Perhaps the stock investors are most excited about when it comes to AI is Palantir Technologies (NASDAQ: PLTR). While a number of big tech companies have been rushing to create the best AI models ...
Generative pretraining (GP) was a long-established concept in machine learning applications. [16] [17] It was originally used as a form of semi-supervised learning, as the model is trained first on an unlabelled dataset (pretraining step) by learning to generate datapoints in the dataset, and then it is trained to classify a labelled dataset.
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