In this article, we explore the use of the GPT-3 large language model to extract data from documents for a leading Private Equity Co. In plain English: We used AI to read a document and put the answers into a spreadsheet. Millions of documents can be read at the same cost as one human. Complex questions can be asked with better-than-human performance reading comprehension. Extracting answers to questions into a spreadsheet enables analytics across document dimensions, time for example. Other potential use cases could include better-than-human performance on data entry, document text extraction, and screen scraping (which requires a human to pinpoint the required data).
Read articleOpenness and transparency are the cornerstones of well-functioning democracies and market economies. See how data technology providers have an opportunity to disproportionately impact the environment, economy, and society by providing access to trusted information.
Read articleThis month we are announcing a stack of features and improvements that make running our platform locally as a developer, on-premise, or privately in your own cloud even easier. These improvements have been spurred on by our customers, partners, and community who use our technology to aggregate data into private ESG data hubs, power seamless data collection & sharing, and automate Meltano jobs with Matatika managed configuration.
Read articleWe are delighted to announce the Matatika Community Edition - a FREE version of the Matatika Platform. With this significant step, we are making automated and intelligent information even more accessible. Distributed as a set of docker services, our Community Edition is designed for data teams to evaluate and develop with Matatika. Hugely reducing the investment required to collect, combine, and share information.
Read articleIf you love PowerBI but you want it to work better. If you are wondering why your Snowflake costs are escalating. If you want to manage data better and drill down deeper, read this months' product update.
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