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 article
We 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 article
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