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.

In his post-summit analysis, theCUBE’s industry analyst Dave Vellante noted that the vision outlined by Snowflake in its keynote presentations and product announcements during the week reflected the company’s intention to be the number one platform on which this new breed of data applications will be built.

“This week’s Snowflake Summit further confirmed our expectations with a strong top line message of ‘All Data/All Workloads’ and a technical foundation that supports an expanded number of ways to access data,” Vellante said. “Squinting through the messaging and firehose of product announcements, we believe Snowflake’s core differentiation is its emerging ability to be a complete platform for data applications. Just about all competitors either analyze data or manage data.”

Vellante was joined during the Snowflake Summit event by theCUBE industry analysts George Gilbert and Lisa Martin. They discussed the latest news and shed light on key messages through interviews with company executives, customers and industry analysts on theCUBE, SiliconANGLE Media’s livestreaming studio. (* Disclosure below.)

Here are three key insights you might have missed:

1. Native apps and container services caught the attention of industry analysts.

Snowflake’s container announcements during the Summit were significant, according to several of the analysts interviewed on theCUBE. Snowflake is containerizing the Nvidia Inc. stack within Snowpark Container Services, extending its reach into advanced analytics and artificial intelligence applications.

“I thought container services would be my number one choice of the new announcements,” Sanjeev Mohan, principal at SanjMo, said in an interview on theCUBE. “Interestingly, what it does is large language models, which are of course the big thing these days, so now there are four different ways of accessing LLMs. You can containerize it in open source, you can use Streamlit, you have native LLMs like Document AI, and call LLMs through an API like OpenAI. So, this is how the platform is expanding.”

Snowflake’s enhancements to its container service offering were designed to provide data scientists with more streamlined workflows.

“It’s container services … kind of blows the lid off of Snowflake processing,” Tony Baer, principal at dbInsights LLC, said in his analysis on theCUBE. “It basically addresses all the limitations that data scientists were complaining about. They don’t want to work through user defined functions. They want to execute directly on the data; and with container services, you can do exactly that.”

Diversity in data types and workloads was another key theme at the Snowflake Summit. This included reinforcement of the company’s commitment to a unified platform through native capabilities.

“Snowflake is saying: ‘We’re providing all this infrastructure inviting in the native apps,’” Doug Henschen, vice president and principal analyst at Constellation Research Inc., said during theCUBE’s interview. “That’s another important topic here today, the native apps. They now have 25 companies that have built 40 native apps that are in production.”

Here’s theCUBE’s complete video interview with Tony Baer, Doug Henschen and Sanjeev Mohan:

2. Snowflake’s CEO takes aim at renaissance in software development and a business plan for AI.

Over a decades-long career in the industry, Snowflake Chief Executive Officer Frank Slootman (pictured) has demonstrated an ability to skillfully navigate shifting technology currents. From his time at the helm of Data Domain Inc., which was acquired by EMC in a high-profile bidding war, to his six-year tenure leading the innovative Service Now Inc., Slootman has shown a knack for spotting and acting on key innovation trends.

He is in the midst of several rapidly moving developments at Snowflake and opened up about these in an exclusive conversation with theCUBE during Snowflake Summit. Foremost among these was his vision for the company as a pathway for budding software entrepreneurs.

“We’ve massively lowered what it takes to start a software business,” Slootman said. “If you wanted to build and publish and monetize an application, what does that take to do historically? You’ve got to raise venture capital, and you’ve got to staff up. You go buy tons of hardware, and then you need to have a scalable, enterprise-grade, high-trust platform. You pretty much give up before you’ve got started. So we created a full stack, where not only can I build it, not only can I sell it to the enterprise because it’s on the Snowflake platform, but now I can market it through our marketplace.”

Snowflake is also focusing its AI portfolio on making the business case for adopting the technology. The company’s recently expanded partnership with Microsoft Corp. on the Azure OpenAI Service highlighted its focus on adapting models to meet specific business requirements.

“It’s all very fun to feed the entire ‘Great Gatsby’ into your prompt and then let it summarize … but what is the economic value of that?” Slootman asked. “There’s a reason that search became such a gigantic thing, because there was a business model to pay for it. There needs to be a business model that’s going to pay for AI as well. In business, we need to see returns for spend. That’s a very important thing that’s going on in cloud, in general, because people are consuming, consuming, consuming.”

Here’s theCUBE’s complete video interview with Frank Slootman:

3. Collaboration with Nvidia will help Snowflake close its gap in supervised AI/ML tools.

At the same time that Slootman makes the case for leveraging AI in a business model, he is also moving to strengthen Snowflake’s hand in supervised tooling. This was made clear when Snowflake and Nvidia teamed up during the Summit to provide customers with capabilities for building custom generative AI applications more easily in a secure cloud. Snowflake customers can now access LLM foundation models using the end-to-end generative AI framework Nvidia NeMo.

Asked directly during an exclusive interview on theCUBE if this would allow Snowflake to potentially leapfrog competitors in the supervised learning market, Christian Kleinerman, senior vice president of product at Snowflake, offered a succinct reply.

“One hundred percent; in some ways you can say that generative AI is resetting the race,” he said. “When you have partners with this type of technology, you might start on the pole position, like you’re leading.”

In resetting the race, Snowflake is also positioning the process for leveraging LLMs and generative AI for broader enterprise use. As Manuvir Das, vice president of enterprise computing at Nvidia, noted in his interview with theCUBE, AI is following the same trajectory as the cloud.

“So many enterprise companies were skeptical about the cloud,” Das said. “Well, what has happened? The cloud has essentially become enterprise grade. I think LLMs are on the same path. They have to become enterprise grade.”

Here’s theCUBE’s complete video interview with Christian Kleinerman and Manuvir Das:

To watch more of theCUBE’s coverage of the Snowflake Summit event, here’s our complete event video playlist:

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

Photo: SiliconANGLE