Production-grade gen AI solutions at Nissan with Snowflake Cortex AI (AIM252)
Snowflake's Journey with Generative AI and Nissan
Introduction
The speaker, Chase Ginther, is an AI Solution Architect Leader at Snowflake, who works closely with the product and engineering team to bring AI and Machine Learning features to market, collaborating with customers like Nissan.
The talk will cover:
What Snowflake is doing in the Generative AI space and how they are enabling customers to build Generative AI solutions and applications.
Nissan's journey with Generative AI, specifically how they have leveraged Snowflake's capabilities to bring a use case to life.
Snowflake's Approach to Generative AI
Snowflake has built a unified platform for end-to-end Generative AI and Machine Learning, focusing on:
Ease of use: Providing a fully managed and tightly integrated infrastructure, with accessibility through interfaces like SQL, Python, and REST.
Efficiency: Allowing customers to build their AI and Machine Learning stacks where their data resides, enabling faster time to value.
Trusted: Providing governance for both data and models within a single ecosystem.
Snowflake's Generative AI capabilities include:
Hosting a number of pre-trained models from leading providers like AI21 Labs, Meta, and Mistral, allowing fine-tuning.
Offering Cortex Analyst, a managed service for natural language to SQL translation.
Providing Cortex Search, a feature for building unstructured data retrieval application pipelines.
Introducing a Chat API service for building Agentic applications.
Generative AI's Impact on Natural Language Processing
Generative AI and Large Language Models have greatly simplified and accelerated traditional Natural Language Processing (NLP) projects.
Use cases like call center transcript analysis, sales team interaction summaries, and customer feedback analysis can now be easily implemented using Snowflake's Cortex AI platform.
The key benefits are the ease of use, with simple SQL statements to leverage pre-trained models, and the ability to govern the entire data pipeline within Snowflake's platform.
Nissan's Journey with Generative AI
The automotive industry has undergone significant changes in the last 5 years, with shifts in electrification, autonomous driving, and digital transformation.
Nissan's Digital Transformation and Consumer Insights team focuses on leveraging data and insights to navigate these turbulent waters, with three strategic pillars: Visualize, Predict, and Transform.
The use case presented is about improving customer experience using unstructured data, such as online customer reviews, to unlock the power of organic customer voice.
Nissan has been able to categorize millions of reviews with an 87% accuracy rate using Snowflake's Cortex AI platform, measuring sentiment and providing benchmarking opportunities to improve customer experience.
The key benefits Nissan has experienced with Snowflake include:
Reduced implementation timelines by about 2 months.
Ability to handle large data sets efficiently.
Intuitive and easy-to-use interface.
The advantage of bringing compute to the data.
Next Steps and Future Plans
Nissan is looking to expand their use of Generative AI, including using conversational interfaces for specific questions, solutions to problems, and comparison across dealers and brands.
They also plan to leverage Generative AI for quick feedback on new product launches and organic brand tracking to understand how consumers perceive their brand and products.
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