With George Gilbert, Rob Strechay and Andy ThuraiThe recent Databricks Data+AI Summit attracted a large audience and, like Snowflake Summit, featured a strong focus on large language models, unification and bringing AI to the data.While customers demand a unified platform to access all their data, Databricks Inc. and Snowflake Inc. are attacking the problem from different perspectives. In our view, the market size justifies the current enthusiasm seen around both platforms, but it’s unlikely that either company has a knockout blow for the other. This is not a head-on collision.Rather, Snowflake is likely years ahead in terms of operationalizing data

In the weeks leading up to the Snowflake Summit in June, speculation focused on how Snowflake Inc. would define its vision for the new modern data stack, where applications were being constructed from a set of data elements that can be composed and launched at scale.Today’s applications are being driven by real-time data generated by people, places, things and activities, leading major platforms, such as Snowflake, to develop innovative ways to connect disparate data sources. An enterprise desire to inform and automate decision-making means that data must also be accessible, not locked in application silos

Imagine a world where enterprises can harness the hidden intelligence locked within their vast repositories of data, unleashing its transformative potential.This vision has taken a significant step toward reality with the partnership between Nvidia Corp. and Snowflake Inc. The convergence of their expertise in artificial intelligence and data management has created a powerful alliance that promises to revolutionize enterprise AI using Large Language Models.“Everybody’s got the sense of what generative AI can do,” said Manuvir Das (pictured, left), vice president of enterprise computing at Nvidia