Inside “Everyday AI” and the Future of Machine Learning

Artificial intelligence is used for everything from automating workflows to customer support and even creating art.

Dataiku Ltd. calls it “everyday AI”. It is a systematic approach to integrating AI into the organization in a way that integrates it into the routine of business. Dataiku has partnered with cloud-based data warehousing giant Snowflake Inc. to build organizations for everyday AI and the future of machine learning.

“We believe that AI will become so pervasive in all business processes, in all decision-making that organizations have to go through, and it’s no longer this special thing we’re talking about,” said Kurt Muehmel (pictured, right) , Customer Manager of Dataiku. “It is the daily life of our companies. And we can’t do that without partners like Snowflake, because they bring all that data together and make sure there’s the computing power behind it to drive.

Muehmel and Ahman Khan (pictured, left), chief artificial intelligence and machine learning strategists at Snowflake, spoke with theCUBE industry analysts Lisa Martin and Dave Vellante at the Snowflake Summit, during an exclusive broadcast on theCUBE, SiliconANGLE Media’s live streaming studio. They discussed everyday AI, making it scalable and accessible, scaling data science and more. (*Disclosure below.)

AI for everyone

One of the biggest problems with AI, historically, has been the amount of data and processing power needed to train and run machine learning models. Dataiku and Snowflake leveraged the scalable nature of cloud computing by using Snowflake’s infrastructure and, through push-down optimization, made AI more accessible and manageable.

“Any kind of large-scale data processing is automatically pushed by Dataiku into Snowflake’s scalable infrastructure,” Khan explained. “That way you don’t get into memory issues or situations where your pipeline runs overnight and doesn’t finish on time.”

The focus on AI relates to two big announcements made by Snowflake at the summit which include its Snowpark and Streamlit products, including the ability to run Python in Snowflake and easily integrate models into Dataiku.

“You can now, as a Python developer, bring the processing to where the data is rather than moving the data to where the processing is,” Khan said. “Predictions from models trained by Dataiku are then used downstream by these data applications for most of our customers. I can write a complete data application without writing a single line of JavaScript CSS or HTML. I can write it entirely in Python, which makes me super excited as a Python developer.

Here’s the full video interview, which is part of SiliconANGLE and theCUBE’s coverage of the Snowflake Summit event:

(*Disclosure: TheCUBE is a paid media partner for the Snowflake Summit event. Neither Snowflake Inc., the sponsor of theCUBE event coverage, nor other sponsors have editorial control over content from theCUBE or SiliconANGLE .)

Photo: SiliconANGLE

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Sherry J. Basler