In an increasingly data-centric world, geospatial data has emerged as a pivotal player in helping us unravel the intricacies of our environment and make well-informed decisions. This treasure trove of information guides us in tracking everything from the movements of people and goods to the rapid spread of natural disasters. However, traditional methods of dissecting geospatial data can often prove to be intricate and time-consuming.
Relevance of Generative AI in Digital Era
Enter Generative AI, a groundbreaking technology that is reshaping the way we approach geospatial data analysis. Generative AI models possess the extraordinary ability to generate entirely new data, encompassing maps, images, and text, all based on existing datasets. This innovative approach dramatically streamlines the process of analyzing geospatial data, uncovering hidden insights that were once obscured.
In the webinar, Hari Subhash, Director of Community, Content Strategy, and Enablement at Kinetica, talks about the Large Language Models (LLMs) and how they are deployed in geospatial data analysis. LLMs are a category of artificial intelligence models capable of generating text, performing language translation, crafting creative content, and providing informative answers to your queries.
In today’s scenario, he talked about how there is a big lag in data analytics today especially when in response to a query. The response to a query can take days when with Kinetica it will only take seconds to respond to a query.
Why Kinetica then?
Kinetica is a real time engine that can power conversations with your data. It is built for workloads at petabyte scale. It is 8x faster than Databricks, 13x faster than Clickhouse and 240x faster than Post-GIS.
It has in data functions which enable analytical enquiry. It has 150+ spatial functions modeled after the ST function library from Post GIS. Kinetica is focusing on having the database have a deep integration with generative AI.
The developer edition comes free which requires docker for installation. There is also a shared fully managed cluster in the cloud with 10GB of Space. Kinetical also provides a set Kinetica examples repo that is actually collection of sample workbooks that showcase different features.
Kinetica’s advanced Generative AI capabilities can simplify the formulation of sophisticated geospatial algorithms, even when dealing with massive datasets.
Through this, Large Language Models (LLMs) can now promptly generate complex geo-joins, ST_Geometry functions, and geo-graph solvers. It can create maps and images from geospatial data and conduct geospatial queries using natural language.
All this can be achieved by simply expressing a question in plain English and executing the operations within mere seconds. Potential risks and threats can be identified and geospatial data can be used to discern trends and patterns. The potential of Generative AI is immense it’s reshaping the landscape of geospatial data analysis.
