Christian Kleinerman | EVP of Product

These 10 sessions exemplify some of the groundbreaking innovation in Snowflake, as well as some of the ways that our customers, of any scale, region and industry, continue to use the Data Cloud platform to rewrite the book on success.

Sessions

What's New: Building AI Chat Experiences with RAG in Snowflake Cortex, WN202

Looking to bring more value out of documents and other text data? Join us to learn about the latest serverless LLM functions and how you can get up and running with RAG-based AI chat experiences within minutes inside Snowflake.

Data Ingestion with Snowflake: Learn Best Practices and What's New, DE218

Data ingestion should not be hard! In this session, Snowflake product experts will provide an overview of what ingestion methods exist today with Snowflake, and when and why to use which ingestion option. Join us to gain a holistic understanding of how ingestion works in Snowflake, and see some of the latest capabilities in action. You'll also learn about Snowflake's native connectors such as PostgreSQL, and how it can remove friction from your data ingestion workload. In addition, we'll discuss the connectors' strengths and ideal use cases.

Document AI: Accelerate and Automate Information Extraction from PDFs at Scale, AI301

The need for a streamlined document-processing operation with a collaborative framework that empowers businesses to make data-driven decisions has never been more critical. Approximately 80% of all data is unstructured, underscoring the vast, untapped potential that lies within documents of all formats. Existing processes are labor-intensive, costly and do not scale, making them ineffective and siloed to different teams. This session will be a comprehensive presentation that explores the transformative power of Document AI in revolutionizing document processing, and democratizing both the process and data across all stakeholders, from engineering to operations.

Unify Customer Data, Deliver Exceptional Experiences and Delight Customers with Snowflake and Salesforce, MA201

Customers have long grappled with data silos across their core marketing systems and central data platform. Without a frictionless way to unify customer and business data, marketers are faced with a daunting decision: either overspend and increase privacy risk, or work with an incomplete data set that hinders tailored experiences that drive the business forward. The good news for marketing and sales departments everywhere is those days are over. With Snowflake and Salesforce’s bi-directional data sharing capabilities, customers can now unify their customer and business data, accelerate decision-making, streamline business processes and power truly differentiated experiences.

Hands-On Lab: Master Streaming Data Pipelines Using Dynamic Tables, DE217

In this hands-on lab, you'll learn how to build streaming and continuous data pipelines using Snowflake features, and master the pipeline using data validation and quality check technique. You'll learn how to perform some important data cleanup, aggregation, monitoring and alerting task in our data pipeline using Dynamic Tables and other features like Snowpark. You'll also hear about the latest Dynamic Tables improvements.

Talk to Your Data: The New Era of Data Analysis Powered by AI, WN102

Join us for an exciting journey into the future of AI and data. Discover how Snowflake Copilot, a breakthrough AI-powered SQL assistant, turbocharges data analysis while maintaining robust security and governance. In this session, we’ll explore Copilot's transformative impact on enterprise analytics and offer a sneak peek into what’s next: enabling business users to converse with their data directly. Prepare to unlock new levels of efficiency and insight!

Productionalizing Gen AI Models: Lessons from the World's Best ML teams, AI118

AI is poised to add $15.7 trillion to the global economy by 2030, with generative AI at the forefront of this revolution, marking a transformative shift across sectors. In this talk, Lukas Biewald will unpack the impact and potential of gen AI models and share practical insights learned from the best ML teams in the world who are building and implementing AI in production. He will share specific insights on deploying Gen AI models into real-world applications, emphasizing LLM evaluation, data set management, model experimentation and optimization. This session is a call to action for ML teams looking to leverage AI's full potential responsibly, and to expedite putting AI into production. Please note: Theaters are first come, first seated.

Overcoming the Complexities of Deploying Generative AI, AI126

The last year has seen significant progress in training state-of-the-art foundation LLMs. Enterprises have sought to quickly deploy these models into their products, leading to the need to ramp up inference solutions in their infrastructure. However, deploying inference solutions involves its own level of complexity, requiring end users to choose and orchestrate across hardware, software and the requirements of the products the inferencing is needed for. This session will explore how NIM abstracts away this complexity for technical users — tightly coupling and simplifying the SDKs, hardware and model doing the hard work for the technical team implementing the inferencing pipeline. Join to also learn how NIM enables this natively in any environment without data entering or leaving. Please note: Theaters are first come, first seated. If this session is full, please sign up for the overflow session here.

How to Build and Scale an Entirely Open Source AI Stack, AI119

If you're looking to interact with LLMs today, you have two paths forward: fine-tune an open source LLM or leverage an existing model API. In this session, you'll learn when it's appropriate and useful to leverage open source LLMs, as well as how to build and scale a fully open source and reproducible gen AI application. This session will cover the role open source plays in model bias awareness, code security and observability, long-term infrastructure considerations and attracting top talent. You'll also learn how to assemble your own open source gen AI stack and what to consider in your architecture. We'll pull back the curtain on some critical, but less talked about processes in LLM development, such as how our team accelerates pre-training. We'll also show you how to reproduce this yourself using open source tools such as Modin and Streamlit. Please note: Theaters are first come, first seated. If this session is full, please sign up for the overflow session here.