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Snowflake Reviews the Rise of the Chatbot

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Large language models (LLMs) are increasingly being used to create chatbots with 46% of apps falling into this category in May 2023, and the percentage continuing to rise. This shows a shift from LLM applications with text-based input, 82% in 2023 and 54% in 2024, to those with iterative text input and offering the ability to sustain a natural conversation. LLM projects are increasingly dedicated to generative AI apps that improve workforce productivity, efficiency, and insights.

These statistics are based on usage data from more than 9,000 Snowflake customers and are summarised in the company’s Data Trends 2024 report. The report focuses on how global enterprise business and technology leaders are using resources such as AI to build data foundations and transform future business operations.

“Conversational apps are on the rise because that’s the way humans are programmed to interact. And now it is even easier to interact conversationally with an application,” says Jennifer Belissent, principal data strategist at Snowflake. “We expect this trend to continue as it becomes easier to build and deploy conversational LLM applications, particularly knowing that the underlying data remains well governed and protected.”

The report also shows more than 20,000 developers in Snowflake’s Streamlit community have built over 33,000 LLM apps in the past nine months. Python is the programming language of choice when developing AI projects due to its ease of use, active community of developers, and vast ecosystem of libraries and frameworks.

In terms of where application development is taking place, the trend is towards programming LLM applications directly on the platform on which the data is managed. This is indicated by a 311% increase in Snowflake native apps between July 2023 and January 2024.

In terms of usage, AI is allowing companies to increase analysis and processing of unstructured data, enabling them to discover untapped data sources but requires a modern approach to data governance to protect sensitive and private data. The report found that enterprises have increased unstructured data processing by 123% in the past year.

“Data governance is not about locking down data, but ultimately about unlocking the value of data,” said Belissent. “We break governance into three pillars: knowing data, securing data and using data to deliver value. Our customers are using new features to tag and classify data so that appropriate access and usage policies can be applied. The use of all data governance functions has increased, and as a result, the number of queries of protected objects has increased, but when the data is protected, it can be used securely.”

She concludes: “The important thing to understand is that the era of generative AI does not require a fundamental change in data strategy. It does, however, require accelerated execution of the strategy.”

The Snowflake Data Trends Report 2024 was generated from aggregated, anonymised data detailing usage of the Snowflake Data Cloud and its integrated features and tools. It examines patterns and trends in data and AI adoption across more than 9,000 global Snowflake accounts. The Snowflake Data Cloud provides insight into the state of data and AI, including which technologies are the fastest growing.

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