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Survey of AI Usage Among Over 9,000 Global Customers... Increased Proportion of Chatbots Among LLM Apps
Python is the Preferred AI Language for Developers... 123% Increase in the Amount of Unstructured Data Processed
Snowflake, a global data cloud company, announced that the proportion of chatbots among Large Language Model (LLM) apps has increased by 46% compared to May of last year.
Snowflake released the 'Data Trend 2024' report after surveying over 9,000 customers on their data and AI adoption patterns and trends. This report, which examines how global enterprise companies are leveraging AI technology and data in their businesses, analyzes that the proportion of text-input-based LLM apps is decreasing (82% in 2023, 54% in 2024) while interactive chatbots are increasing.
Furthermore, a survey conducted among the Streamlit developer community revealed that approximately 65% of respondents are working on LLM projects for business purposes. In reality, enterprise customers are using generative AI-based technologies in various ways to enhance productivity, efficiency, and analytical capabilities in their work.
Jennifer Belissent, Snowflake's Senior Director of Data Strategy, stated, "Interactive apps are programmed in a way that mimics how people actually interact, allowing for easy interaction with LLMs as if you were having a conversation with a person." She further emphasized, "Especially if the governance and security of the data that forms the foundation of LLM apps are ensured, interactive apps will meet the expectations of both businesses and users, leading to increased utilization."
Over 33,000 LLM Applications Built in 9 Months
Over 20,000 developers worldwide within the Snowflake Streamlit community have built over 33,143 LLM apps in the past nine months. Their preferred programming language was Python. Python usage on Snowflake's app development platform, Snowpark, increased 5.71 times last year. This is a higher figure compared to Scala and Java, which saw increases of 3.87 times and 1.31 times, respectively. Python accelerates prototyping and testing, boosting the overall speed of operations and the overall learning speed in the early stages of cutting-edge AI projects.
Recently, there has been an increase in instances where LLM apps are developed by programming on top of data management platforms. The utilization of Snowflake Native Apps, which enable app development directly on the Snowflake platform, has increased more than threefold between July of last year and January of this year, a period of seven months. Applications developed on a single data platform eliminate the need to export data copies to external vendors, leading to faster app development and deployment, as well as reduced operational and maintenance costs.
Increasing Importance of Data Governance Within Enterprises
With the adoption of AI, the analysis and processing of unstructured data within organizations has also increased. This process can uncover previously untapped data sources, and data governance becomes crucial for protecting sensitive personal information. According to the Snowflake report, the volume of unstructured data processed by companies over the past year has increased by 1.23 times. Global market research firm IDC estimates that up to 90% of the world's data is unstructured, including videos, images, and documents. Unlike structured data, where language model training has become commonplace, processing unstructured data presents a new opportunity for businesses to enhance their competitive edge.
Jennifer Belissent, Snowflake's Senior Director of Data Strategy, emphasizes that "data governance is not about controlling data but ultimately leveraging its value." She explains, "Snowflake categorizes governance into three pillars: data collection, data security, and data utilization. Customers can tag and categorize data to apply access and usage policies appropriate for their businesses." As a result, the number of Snowflake customers adopting data governance features has risen from 70% to 100%, and the number of queries running within governance has increased by 142%.
Furthermore, Belissent stated, "Each piece of data reveals how companies are responding to their challenges. By looking at these individual data points in their entirety, we can develop a comprehensive strategy for organizations to leverage cutting-edge AI technology opportunities." She continued, "The core strategy in the era of generative AI is not about fundamentally changing data but about immediately putting that strategy into action. To do this, it's crucial for companies to open and share data sources spread across their vast data ecosystems, breaking down data silos."
The full text of the 'Snowflake Data Trend 2024 Report' can be found here.
Website: https://www.snowflake.com/?lang=ko
Contact
Snowflake PR Agency
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Soobin Kim
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