ROUNDtable
# AI Applications
# GPU Orchestration
# Kubernetes Clusters
# CAST AI
Serving LLMs in Production: Performance, Cost & Scale // CAST AI Roundtable
Experimenting with LLMs is easy. Running them reliably and cost-effectively in production is where things break.
Most AI teams never make it past demos and proofs of concept. A smaller group is pushing real workloads to production—and running into very real challenges around infrastructure efficiency, runaway cloud costs, and reliability at scale.
This session is for engineers and platform teams moving beyond experimentation and building AI systems that actually hold up in production.
Ioana Apetrei, Igor Šušić & Adam Becker · Feb 19th, 2026
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Pavol Bielik, Aniket Singh, Mohan Mahadevan & 1 content:more content:speaker · Jun 14th, 2024
Deploying AI models in manufacturing involves navigating several technical challenges such as costly data acquisition, class imbalances, data shifts, leakage, and model degradation over time. How can you uncover the causes of model failures and prevent them effectively?
This discussion covers practical solutions and advanced techniques to build resilient, safe, and high-performing AI systems in the manufacturing industry.
# AI Models
# AI Systems
# Manufacturing Industry
# LatticeFlow
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Davis Blalock, Bandish Shah, Abhi Venigalla & 3 content:more content:speakers · Apr 12th, 2024
DBRX is designed to be especially capable of a wide range of tasks and outperforms other open LLMs on standard benchmarks. It also promises to excel at code and math problems, areas where others have struggled.
Our panel of experts will get into the technical nuances, potential applications, and implications of DBRx for businesses, developers, and the broader tech community.
This session is a great opportunity to hear from insiders about how DBRX's capabilities can benefit you.
# LLMs
# DBRX
# Databricks
# Databricks.com
Frank Liu, Jiang Chen & Yujian Tang · Mar 15th, 2024
Engineering deep-dive into the world of purpose-built databases optimized for vector data. In this live session, we explore why non-purpose-built databases fall short in handling vector data effectively and discuss real-world use cases demonstrating the transformative potential of purpose-built solutions. Whether you're a developer, data scientist, or database enthusiast, this virtual roundtable offers valuable insights into harnessing the full potential of vector data for your projects.
# Vector Database
# MLOps
# Zilliz
# Zilliz.com
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Ilona Logvinova, Nayur Khan, Mohamed Abusaid & 1 content:more content:speaker · Feb 2nd, 2024
Do you build or buy?
Check the QuantumBlack team discussing the different sides of buying vs building your own GenAI solution.
Let's look at the trade-offs companies need to make - including some of the considerations of using black box solutions that do not provide transparency on what data sources were used.
Whether you are a business leader or a developer exploring the space of GenAI, this talk provides you with valuable insights to prepare you for how you can be more informed and prepared for navigating this fast-moving space.
# GenAI Buy
# Build
# Commercial
# Open Source
# QuantumBlack
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Darek Kłeczek, Michelle Marie Conway, Oliver Chipperfield & 2 content:more content:speakers · Dec 15th, 2023
Step into the fascinating world of Language Model Management (LLMs) in a Regulated Environment! Join us for an enlightening chat where we'll explore the intricacies of managing models within highly regulated settings, focusing on compliance and effective strategies.
This is your opportunity to be part of a dynamic conversation that delves into the challenges and best practices of Model Management in Regulated Environments. Secure your spot today and stay tuned for an enriching dialogue on navigating the complexities of navigating the regulated terrain. Don't miss out on the chance to broaden your understanding and connect with peers in the field!
# Model Management
# Regulated Environment
# Weights & Biases
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Kevin Stumpf, Derek Salama, Eddie Esquivel & 2 content:more content:speakers · Sep 26th, 2023
Getting an ML application into production is more difficult than most teams expect—but with the right preparation, it can be done efficiently! Join us for this exclusive roundtable, where 4 machine learning experts from Tecton will discuss some of the most common challenges and best practices to avoid them.
With over 35 years of combined experience in MLOps at companies like AWS, Google, Lyft, and Uber, and 15 years of experience at Tecton spent helping customers like FanDuel, Plaid, and HelloFresh getting ML models into production, the presenters will share how factors like organizational structure, use cases, tech stack, and more, can create different types of bottlenecks. They’ll also share best practices and lessons learned throughout their careers on how to overcome these challenges.
# ML Application
# Production
# Tecton 0.6