AI and Advanced Analytics in Manufacturing and the Supply Chain
Greg Sloyer, PhD., Manufacturing Industry Principal, Snowflake
There are opportunities within and across organizations to take advantage of AI, leading to improvements in the way we make supply chain, manufacturing and other operations decisions. Learn how organizations are applying advanced analytics and GenAI as well as recommendations on how to improve the success rate of implementation by ensuring key foundational elements are in place.
Accelerate Your Enterprise AI with Snowflake Cortex AI
Carlos Carrero, Global Principal Architect, Snowflake
Learn how to talk to your data using Snowflake Enterprise AI capabilities. From extracting information from your data using Large Language Models via Cortex AI to building Chatbots that can use structured and unstructured data to answer questions about your own products. All in an easy, efficient and secured way.
Advanced Analytics and the Retail Data Cloud
Leslie Lorenz, Head of Retail, Americas, Snowflake
Learn how organizations are leveraging advanced analytics and AI to boost performance in the Retail and Consumer Goods Industry, as well as touch on human centric AI and how it is changing the world of retail data and technology.
Build a Data Foundation to Fuel Generative AI
Anubhav Srivastava, Sr. Specialist, Data & AI, Worldwide Public Sector, AWS Canada
Data has long been considered a strategic asset by organizations, but generative AI puts a renewed emphasis on the importance of a data strategy. Whether you are building your own model or customizing a foundation model, your data is a key differentiator for generative AI, so you need a data strategy that supports relevant, high-quality data. In this session, learn about the data tools that can fuel your generative AI strategy and the common data patterns required to transform your generative AI application from a generic tool to a program that truly knows your business and your customer.
Mastering Prompt Engineering for Generative AI
Alexander Medvedev, Senior Partner Solutions Architect, AWS Canada
Prompt Engineering has proven to be a key skill for data-scientists in the Generative AI era, often having a huge impact in the quality of outputs from Large Language Models (LLMs). In this session, we will dive into common Prompt Engineering techniques, share best practices and tips, and explore how to implement those in AWS through Amazon Bedrock or Amazon SageMaker.
Amazon Nova
Amazon Nova: Revolutionizing AI with Advanced Multimodal Understanding
Abhinav Sarin, Worldwide Public Sector, AWS Canada
Discover the transformative potential of Amazon Nova, a groundbreaking family of AI models engineered to fluently understand and process a diverse range of inputs including text, images, audio, and video. This overview highlights how Amazon Nova is establishing new AI benchmarks through its exceptional capabilities in complex visual reasoning, sophisticated agentic workflows, and deep functional expertise across key enterprise verticals. Explore its industry-first video understanding on Amazon Bedrock, unparalleled customizability via self-service fine-tuning and model distillation, and superior price-performance delivering lower costs at equivalent or better latency. Learn how Amazon Nova can empower your next generation of AI applications, from intelligent document analysis to automated API execution and dynamic UI actuation.
Trusted Data for Trusted GenAI Outcomes
Gopinath Sankaran, Vice President Strategic Cloud Ecosystems, Informatica
As new Generative AI and Next Gen Analytics technology captures imaginations for businesses and consumers alike, enterprises have a unique opportunity to harness the power of AI to drive value in their own businesses.
Join us in this session where you will learn how to accelerate and transform business outcomes with next gen analytics and generative AI. Discover how Trusted Data delivers Trusted Analytics and GenAI outcomes and can help your business meet its objectives. Explore practical steps to prepare your business for successful adoption of AI using Informatica’s Intelligent Data Management Cloud (IDMC).
You’ll also learn about:
- Drivers for Trusted Data in Analytics and AI use cases
- Things to address for enterprise grade GenAI
- How Informatica and partners can support your transformation journey
Informatica GenAI Blueprint: Building Enterprise Grade Generative AI Applications
Rajeev Srinivasan, Director, Ecosystem Solutions | Strategic Cloud Ecosystems, Informatica
Are you looking to implement GenAI in your enterprise? Do you need to integrate enterprise-specific data into your GenAI applications? Join us for a session on how Informatica’s Intelligent Data Management Cloud™ (IDMC) can enhance your GenAI initiatives on AWS by providing trusted, governed data and metadata from within your enterprise, boosting the accuracy and reliability of your GenAI outcomes. We’ll also showcase how you can leverage the powerful collaboration between IDMC and Amazon Bedrock to drive your GenAI use cases.
From Classic Machine Learning to Generative AI: How Has Data Management Evolved?
There is a vast spectrum of AI deployments in various industry verticals. Classic machine learning is getting productionized, generative AI is having its moment, and multimodal AI is about to be mainstream. Through all these leaps of evolution in models and AI techniques, data management has only slightly evolved. Barring vector databases, data teams still struggle with old methods of data wrangling that only slow them down. In this talk, I will cover the various challenges and deployment alternatives we have encountered over the past few years, and introduce a few scenarios where data management, when done right, could significantly accelerate AI in production.
Carlos Carrero
Vishakha Gupta-Cledat
Leslie Lorenz
Mark MacIver
Alexander Medvedev
Gopinath Sankaran
Abhinav Sarin
Greg Sloyer, PhD.,
Rajeev Srinivasan
Anubhav Srivastava
