Data proliferation has already complicated research. Its not going to get better.

There is no doubt that there is more data available today than at any point in history.

Truth be told, it is highly unlikely that as we move forward in time there will ever be a period where there is less data to sort through on one day than there was the day before. For researchers of all kinds, more is not necessarily better. 

According to a 2023 article by Petroc Taylor 1 , global data is forecast to increase 180% from 64.2 zettabytes in 2020 to over 180 zettabytes by 2025. That staggering increase in data proliferation was calculated before generative AI really came onto the scene. With tools like ChatGPT available to just about anyone, nearly everyone is now focused on how to use these tools to increase productivity, create new content or both. All this activity will potentially result in more “noise” for researchers. More academic journals. More news. More patent filings. More everything. 

For researchers focused on bringing new products to market or managing corporate risk, this is going to complicate things. Many of these researchers depend on patent data to understand the technical landscape in which they are operating and to reduce risk associated with things such as intellectual property infringement. To complicate matters, patent data often needs to be combined with proprietary data to complete a research project and achieve a good outcome. Researchers need new search methodologies that simplify their workflow while helping them efficiently find relevance in the constantly increasing volume of available data. 

At FluidityIQ, we believe that any research project is a dynamic, living, breathing process that theoretically could have no end, although could support multiple outcomes over time. Search tools that rely solely on Boolean search strings or that render a result that represents a single point in time, are not adequate today nor will they be viable with the current data proliferation rates.  

For that reason, we have developed a patent pending approach to research that combines cutting edge AI with a researcher’s existing knowledge base to simplify the process of identifying relevant patents in support of specific research goals. This process is not a black box, and it is not just sticking off-the-shelf AI tools on top of a pile of data to let the researcher sort through the hallucinations and other challenges created by some AI tools. Our solution provides the researcher with a guided experience where they can leverage advanced AI tools to acquire relevant information, curate search results, update their knowledge library dynamically and produce valuable stakeholder output. 

Importantly, our process ensures that patent information can be combined with customer’s proprietary information without the need to move their sensitive data into the FluidityIQ cloud. Research is proprietary and we think it makes sense to provide tools and an enhanced capability rather than try to control a customer relationship by controlling access to their own research. We want to help customers streamline their research process while maintaining tight data security. 

1 Amount of data created, consumed, and stored 2010-2020, with forecasts to 2025, by Petroc Taylor, November 16, 2023. Sourced from Statista

For more information about FluidityIQ and how we achieve results for our customers, reach out to us directly at info@fluidityiq.com.