In this new era of generative artificial intelligence, big data companies are innovating, and new companies are working in novel ways. At the Data Cloud Summit, Snowflake Inc. has sought to outline how it plans to help businesses of all sizes with its AI tools, including with Snowflake Notebooks.

Technology has been moving quickly, according to Chris Van Pelt (pictured, right), co-founder and chief information security officer of Weights & Biases Inc., which aims to build the best tools possible for AI developers.

Snowflake’s Amanda Kelly and Weights & Biases’ Chris Van Pelt talks to theCUBE about Snowflake Notebooks.

“We started about six years ago when the world looked a little different than it does today in terms of the AI stack,” Val Pelt said. “But have just been thrilled to watch this space grow and to work with really cool companies like Snowflake and products like Streamlit to help developers ultimately build better models.”

Van Pelt and Amanda Kelly (left), Streamlit product director at Snowflake, spoke with theCUBE Research analysts Dave Vellante and Rebecca Knight at Data Cloud Summit, during an exclusive broadcast on theCUBE, SiliconANGLE Media’s livestreaming studio. They discussed Snowflake Notebook’s goal to empower developer workflows and the path forward for AI development. (* Disclosure below.)

Snowflake Notebooks is integrated to make things easy for users

Snowflake Notebooks, introduced last November, has entered public preview. While some may be asking why the world needs another notebook, Kelly said it’s about having the right tool for the job. 

“There’s a lot of great notebooks out there, and we have a lot of great partners like Hex that are being really next-generation experiences,” she said. “What we’re trying to do with Snowflake is really make sure that when you have a question about your data, when you have something you need to get done today, you are really no more than one click right away from having that answer.”

That’s why Snowflake built a very integrated notebook, according to Kelly. It involves bringing in various features, including scheduling, Python and SQL cell mixing and more.

“We’re really optimizing for the types of tasks that people want to do on Snowflake. Then, we’re bringing the best of Snowflake,” she said. “The integrations with Unistore, the integrations with Cortex, all of that together in one notebook, so it’s really easy to accomplish anything you want to do with your Snowflake data.”

The notebook interface is a common paradigm for data scientists and those doing experimentation and working with models, according to Val Pelt. Anytime someone is doing machine learning modeling, it starts with the data.

“You need to be able to quickly get data from whatever sources there might be. And Snowflake Notebooks actually makes it really easy,” he said.

There’s been lots of talk recently about productivity booms. While that might not be the case in broader society, it is the case for developers, according to Van Pelt.

“I’d be working on a programming problem and scratch my head and say, ‘Hey, how do I do that?’ The first place I’d go is Google. Now the first place I go is, is ChatGPT or Claude or whatever kind of large language model interface I might choose,” he said. “There’s also the copilot integrations, where I essentially get nice auto-complete that is just, as a developer, it’s magical when it works.”

Here’s the complete video interview, part of SiliconANGLE’s and theCUBE Research’s coverage of Data Cloud Summit:

(* Disclosure: Snowflake Inc. and Weights & Biases Inc. sponsored this segment of theCUBE. Neither Snowflake, Weights & Biases nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)

Photo: SiliconANGLE