![]() ![]() The new toolkit interacts and integrates with existing services, and is available to data scientists and engineers through our Python package. Users can point to a folder and direct the toolkit to upload the documents, convert them, and ultimately analyse the contents of the text, tables, and figures. We’re also releasing deepsearch-toolkit, a Python package, where users can programmatically upload and convert documents in bulk. DS4SD has a simple drag-and-drop interface, making it very easy for non-experts to use. It allows users to upload documents in an interactive fashion to inspect a document’s conversion quality. To help achieve this goal, we’re now publicly releasing a key component of the Deep Search Experience, our automatic document conversion service. Opening up Deep Search to the scientific communityįollowing the launch of the Generative Toolkit for Scientific Discovery (GT4SD) in March, the availability of DS4SD marks the next leap toward our ultimate goal of building an Open Science Hub for Accelerated Discovery. But now, we’re making deep search even more versatile and accessible with the release of Deep Search for Scientific Discovery (DS4SD), an open-source toolkit for scientific research and businesses. IBM Research’s Deep Search already allows scientists and businesses to search mountains of unstructured data. In fact, IDC estimates that 80% of all global data will be unstructured by 2025. These documents are packed with valuable information, but their contents are often not easy to search, because they’re in an unstructured format that can’t easily be transferred to a database. ![]() Every organization is built on documents, from legal briefs, financial statements, and technical specifications, to research papers, and slide decks. ![]()
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