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Artificial intelligence is being used for everything from automating workflows to assisting customers and even creating art.

Dataiku Ltd. calls this Everyday AI. Its a systematic approach to embedding AI into the organization in a way that makes it part of the routine of doing business. Dataiku has teamed up with cloud-based data warehousing giant Snowflake Inc. to set organizations up for everyday AI and the machine learning-heavy future.

We believe that AI will become so pervasive in all of the business processes, all the decision-making that organizations have to go through, and that its no longer this special thing that we talk about, said Kurt Muehmel (pictured, right), chief customer officer of Dataiku. Its the day-to-day life of our businesses. And we cant do that without partners like Snowflake, because theyre bringing together all of that data and ensuring that there is the computational horsepower behind that to drive.

Muehmel and Ahman Khan (pictured, left), head of artificial intelligence and machine learning strategy at Snowflake, spoke with theCUBE industry analysts Lisa Martin and Dave Vellante at Snowflake Summit, during an exclusive broadcast on theCUBE, SiliconANGLE Medias livestreaming studio. They discussed Everyday AI, making AI scalable and accessible, scaling data science and more. (* Disclosure below.)

One of the biggest issues in AI, historically, has been the amount of data and processing power it takes to train and run machine learning models. Dataiku and Snowflake took advantage of the scalable nature of cloud computing using Snowflakes infrastructure and, using push-down optimization, made AI more accessible and easier to manage.

Any kind of large-scale data processing is automatically pushed down by Dataiku into Snowflakes scalable infrastructure, Khan explained. So you dont get into things like memory issues or situations where your pipeline is running overnight and it doesnt finish in time.

The AI focus relates to two big announcements Snowflake made during the summit that include its Snowpark and Streamlit products, including the ability to run Python in Snowflake and easily incorporate models into Dataiku.

You can now, as a Python developer, bring the processing to where the data lives rather than move the data out to where the processing lives, Khan said. The predictions that are coming out of models that are being trained by Dataiku are then being 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 completely in Python, which makes me super excited as a Python developer.

Heres the complete video interview, part of SiliconANGLEs and theCUBEs coverage of the Snowflake Summit event:

(* Disclosure: TheCUBE is a paid media partner for the Snowflake Summit event. NeitherSnowflake Inc., the sponsor for theCUBEs event coverage, nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)

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Inside 'Everyday AI' and the machine learning-heavy future - SiliconANGLE News