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Machine Learning and AI

Event Welcome

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Machine Learning and AI

Closing Remarks

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Machine Learning and AI

Live Panel: Infrastructure in an Agentic World

If the future is agentic, what does this mean for Infrastructure?
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Machine Learning and AI

Bringing AI Into the Real World

Join us as we delve into the high-level design and architecture that enabled the creation of Ray-Ban Meta, a best-in-class AI wearable used by millions. To make AI truly useful, it must be seamlessly integrated into our daily lives, providing reliable and high-performance capabilities. However, achieving this requires overcoming real-world physical limitations through innovative engineering […]
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Machine Learning and AI

Agentic Observability – Making LLM Apps Debuggable, Trustworthy, and Scalable

As LLM applications evolve into multi-agent systems and power complex decision-making workflows, the ability to observe and debug their behavior becomes a core engineering challenge. These systems are dynamic, non-deterministic, and increasingly reliant on external tools and APIs making traditional monitoring approaches insufficient. At Fiddler, we’ve worked with enterprise and federal teams deploying LLMs at […]
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Machine Learning and AI

Agentic Solution for Data Warehouse Access

Meta manages a large-scale data warehouse where security is a critical component. Every day, teams across Meta are tasked with managing access to the data they oversee and obtaining access to data through internal data products. In this talk, we delve into the challenges of managing internal data access at Meta’s scale and its growing […]
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Machine Learning and AI

How to Prepare Your Agents for the Ice(berg) Age

In a future world where agents interact with billions of users, many of these agents will also have to interact with data querying tools to provide answers grounded in facts. As enterprise data analytics is rapidly moving towards open table formats like Apache Iceberg, these agents need to be able to speak to Iceberg-based data. […]
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Machine Learning and AI

Live Panel: GenAI Startups

We will explore the world of reinforcement learning, post training and what it’s like to build a startup on open models.
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Machine Learning and AI

Q&A Session

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Machine Learning and AI

Silent Errors in Large-Scale LLM training: Challenges and Lessons Learned

GPU cluster reliability is a growing challenge as AI models and the clusters that host them grow to unprecedented scale. Insidious errors such as Silent Data Corruptions (SDCs) are particularly difficult to address due to their highly elusive and non-deterministic nature, and their effect on large-scale LLM training and inference is poorly understood. In this […]
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Machine Learning and AI

Agentic Evals

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Machine Learning and AI

Beyond RAG: Production-Ready AI Agents Powered by Enterprise-Scale Data

At Snowflake, we’ve been pursuing how to use Agents and AI to let any business user talk to their data. Enterprise data isn’t always tidy—and AI agents need more than great retrieval to drive real value. In this session, we’ll share what we’ve learned at Snowflake about enabling agents that deeply understand and reason over […]
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