About this Event
Join us in the heart of New York City for a free ML/AI mega-meetup featuring an incredible lineup of ML experts, data scientists, and DevOps professionals.
Dive into scaling AI in production, optimizing ML workflows, and more in data science. This is a great opportunity to mingle with the best tech minds NYC has to offer over some good food. and save your spot
Featuring:
- AIOps at Reasonable Scale by Ciro Greco, Founder and CEO @ Bauplan
This session explores the unique security challenges of ML systems in the GenAI era and provides actionable strategies to safeguard them. Learn why traditional approaches fall short and how to fortify your ML lifecycle to stay ahead in an evolving threat landscape.
We have pioneered the concept of “ML for the 99%” with the ML at reasonable scale series, and recently discussed what changed with the new AI wave (spoiler: not much, the fundamentals stay!). In the talk, we review the basics of ML in production and stress what changed and what didn’t in the era of LLMs.
- Protecting ML Systems in the GenAI Era by Yuval Fernbach, VP, CTO MLOps @ JFrog
Generative AI and machine learning systems are reshaping industries but also introducing new security risks. The reliance on vast data, rapid deployment cycles, and automated pipelines in MLOps has expanded the attack surface, exposing vulnerabilities to data poisoning, adversarial inputs, and pipeline exploitation.
This session explores the unique security challenges of ML systems in the GenAI era and provides actionable strategies to safeguard them. Learn why traditional approaches fall short and how to fortify your ML lifecycle to stay ahead in an evolving threat landscape.
- Integrating Tech to Unlock Generative AI by Liron Freind Saadon, Head of Dev Rel @ NVIDIA
An Ideal MLOps platform in the Generative Al era is a comprehensive solution that supports the entire machine learning lifecycle, from data preparation and model development to model deployment and monitoring. It should provide seamless integration of tools and technologies that enable organizations to build, deploy, and manage machine learning models with ease. In this talk, we'll review some of the tools and solutions that exist to build, deploy, and scale GenAl workloads across different environments successfully.
- Human-in-the-loop feedback, agentic systems by Ari Kaplan, Head of Evangelism, Databricks
Discover how incorporating continuous human guidance ensures ethical, accurate, and context-aware outputs, while autonomous agentic systems push the boundaries of Al, enabling proactive decision-making and complex problem-solving. - Networking/Happy Hour
and save your spot
Event Venue & Nearby Stays
45 Rockefeller Plaza 27th floor, 45 Rockefeller Plaza, New York, United States
USD 0.00
