Digging into new AI models is one of the most exciting parts of my job here at Datavolo. However, having a new toy to play with can easily be overshadowed by the large assortment of issues that come up when you’re moving your code from your laptop to a production...
AI systems need data all along the spectrum of unstructured, structured, and multi-modal. The protocols by which these diverse types of data are both acquired and delivered are as varied as the data types themselves. At the same time data volumes and latency requirements grow ever stronger which demands solutions which scale down and up first – then out. In other words we need maximum efficiency, we can’t resort to remote procedure calls for every operation, and we need to support hundreds if not thousands of different components or tools in the same virtual machine.
Innovation is the driving force behind human progress and we believe in the power of technology to enable humans to push beyond the boundaries of what’s possible. In this rapidly evolving landscape, staying ahead of the curve is what sets good organizations apart from the great ones. Over the years, the realm of possibility has expanded in both incremental steps and monumental leaps. Let’s take a closer look at the transformative journey from “Big Data” to Generative AI.