UPDATED 15:12 EDT / APRIL 12 2024

Chris D'Agostino, chief technology officer at Databricks, talks with theCUBE about AI and machine learning at Google Cloud Next 2024 AI

DBRX launch by Databricks demonstrates how early gambles on industry direction can pay off

In late March, when Databricks Inc. launched DBRX, a general-purpose large language model, it marked another milestone in a strategy based on three big bets when the firm started in 2013.

“The first was that organizations were going to be moving to the cloud, second was that successful ones were going to be using open source, and the third was that machine learning would be really at the forefront,” said Chris D’Agostino (pictured), global field chief technology officer of Databricks. “DBRX is the culmination of a decades-long strategy.”

D’Agostino spoke with theCUBE Research analysts John Furrier and Savannah Peterson at Google Cloud Next 2024, during an exclusive broadcast on theCUBE, SiliconANGLE Media’s livestreaming studio. They discussed the integration of DBRX with MosaicML and how machine learning is being adopted throughout the Databricks portfolio. (* Disclosure below.)

Databricks leverages MosaicML acquisition

DBRX can be paired with Mosaic AI, a toolset for building and deploying AI models that is the outgrowth of Databricks’ MosaicML Inc. acquisition last year for an eye-catching $1.3 billion. MosaicML offers generative AI tools that can be used by Databricks customers to train and fine-tune models at a lower cost.

“We acquired MosaicML, and there’s a lot of press around the price point,” D’Agostino said. “DBRX is the first step in the results of that. You can build open models that perform as well as the proprietary ones and enable customers to do more with their own data in a very secure manner.”

Databricks’ CTO indicated that the company is also focused on the integration of machine learning in a way that will allow it to offer products and services beyond building and training large language models.

“In addition to creating an environment where people can build and train their own LLMs and other types of machine learning models, we are embedding machine learning inside of the Databricks platform,” D’Agostino said. “As new data comes in, we’ve trained models on existing data, and as the new data arrives we’re able to compare and contrast whether or not that new data is consistent.”

Here’s the complete video interview, part of SiliconANGLE’s and theCUBE Research’s coverage of Google Cloud Next 2024

(* Disclosure: TheCUBE is a paid media partner for Google Cloud Next 2024. Neither Google LLC, the primary sponsor for theCUBE’s event coverage, nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)

Photo: SiliconANGLE

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