Video: ResourceSpace 10.1 unleashes the power of GPT-3 AI for metadata processing

ResourceSpace is about to get even more powerful with the release of version 10.1.

This new version includes a highly anticipated feature: the integration of OpenAI's GPT-3 AI language model for metadata processing.

GPT-3, the latest and largest language model developed by OpenAI, is receiving a lot of media attention for its remarkable capabilities in natural language processing. With its advanced algorithms and massive training capabilities, GPT-3 has the ability to generate human-like text, complete tasks, and even create new content.

The potential applications for this technology are vast, and many industries are exploring ways to incorporate GPT-3 into their workflows to improve efficiency, accuracy, and creativity. The integration of GPT-3 into ResourceSpace is just one example of the many exciting developments in the world of GPT-3 and its impact on various fields.

With this integration ResourceSpace can be configured to automatically process metadata using the powerful natural language processing capabilities of GPT-3. Simply by configuring a prompt on an output metadata field, and selecting an input field to use as the source, ResourceSpace can automatically generate the output field's value.

This has tremendous implications for automating metadata processing tasks. Here are a few examples of how this integration can be used:

  • Automated title/summary generation: With GPT-3, ResourceSpace can automatically generate concise and descriptive titles and summaries from large blocks of text - either extracted from a PDF file, from subtitles from a video file, or pulled in from a Collection Management System (CMS) or Product Information Management (PIM) system via our various integrations. Given a prompt such as "Generate a title using the following text" ResourceSpace will generate a title or succinct summary in seconds.
  • Keyword extraction: With GPT-3, ResourceSpace can automatically extract meaningful keywords from a block of text. By providing a prompt such as "Extract keywords from the following text" ResourceSpace can quickly generate a list of relevant keywords that can be used for searching, categorization, and more. Need it to be more specific? Just ask. If you want a list of all countries mentioned in the text for your 'Country' metadata field, just configure the prompt "Extract a list of countries from the following text".
  • Automatic categorisation: GPT-3 integration can also be used to automatically categorise digital assets based on their content. Given an existing list of categories, ResourceSpace can use GPT-3 to analyse the content of a digital asset and select the most appropriate category. This not only saves time but also ensures consistent and accurate categorization, making it easier to find and manage digital assets. Additionally, the automated categorization can be used to generate custom reports and statistics, providing valuable insights into the types and distribution of digital assets.

These are just a few examples - as the prompts are entirely user configurable, there are potentially unlimited applications for metadata processing, and, as more advanced AI models become available we will continue to explore new and innovative ways to incorporate AI into ResourceSpace's features and capabilities.

In conclusion, the integration of GPT-3 into ResourceSpace provides a level of automation never before seen, freeing up valuable time for digital asset managers and allowing them to focus on more strategic tasks. Find out more about in our Knowledge Base. We're really looking forward to exploring the potential for this technology with our users.