NVIDIA LLM Developer Day - A Free Virtual Event
8:00–9:15 a.m. PT - The Fast Path to Developing With LLMs
Learn practical methods for designing and implementing LLM-powered systems on real-world business data using popular, ready-to-go LLM APIs—no specialized hardware, model training, or tricky deployment required. We'll show techniques for engineering effective inputs to the models (“prompts”) and how to combine LLMs with other systems, including business databases, with toolkits like LangChain. Join us and learn how to build LLM systems to generate tangible business results.
David Taubenheim, Senior Solutions Engineer, NVIDIA
9:30–10:45 a.m. PT - Tailoring LLMs to Your Use Case
Push LLMs beyond the quality limits of off-the-shelf models and APIs by customizing them for domain-specific applications. We'll discuss strategies for preparing datasets and showcase gains from different forms of customization using practical, real-world examples. Join us and learn about model tuning techniques applicable for both API-based and self-managed LLMs.
Christopher Pang, Senior Solutions Engineer, NVIDIA
9:30–10:45 a.m. PT - Large Language Models and Generative AI for Life Sciences
In this session, we'll explore foundational AI models in biology, as well as practical protein engineering and design applications supported by real-world examples. We'll discuss recent biology breakthroughs and apply that to how you can use LLMs to predict protein structure and function and encode protein data computationally. Attendees will learn techniques for how to use NVIDIA BioNeMo™, a generative AI platform for drug discovery, to simplify and accelerate training of models on their own data, ensuring easy and scalable deployment of models for drug discovery applications.
Chelsea Sumner, PharmD, RPh, Healthcare AI Startups Lead, NVIDIA
Chris Dallago, Senior Solutions Architect, NVIDIA
11:00 a.m.–12:15 p.m. PT - Reinventing the Complete Cybersecurity Stack With AI Language Models
Cybersecurity is a data problem, and one of the most effective ways of contextualizing data is via natural language. With the advancement of LLMs and accelerated compute, we can represent security data in ways that expand our detection and data generation techniques. In this session, we’ll discuss advancements in LLMs, including how to leverage them throughout the cybersecurity stack, from copilots to synthetic data generation.
Bartley Richardson, PhD, Director of Cybersecurity Engineering, NVIDIA
11:00 a.m.–12:15 p.m. PT - Running Your Own LLM
Optimizing and deploying LLMs on self-managed hardware—whether in the cloud or on premises–can produce tangible efficiency, data governance, and cost improvements for organizations operating at scale. We'll discuss open, commercially licensed LLMs that run on commonly available hardware and show how to use optimizers to get both lower-latency and higher-throughput inference to reduce compute needs. Join us and learn how to scale up self-managed LLMs to accommodate unique business and application requirements.
Emily Apsey, Senior Technical Marketing Engineering Manager, NVIDIA
12:30–1:00 p.m. PT - Technical Ask-the-Experts
In this session, we'll answer any additional questions that attendees may have, beyond those discussed during the sessions.
Ozzy Johnson, Director of Solutions Engineering, NVIDIA
Adriana Flores Miranda, Senior Solution Architecture Manager, NVIDIA
10:00–11:30 a.m. GMT - EMEA: Technical Ask-the-Experts
In this session, we'll recap LLM Developer Day content and answer any questions that attendees may have.
Ekaterina Sirazitdinova, Senior Deep Learning Data Scientist, NVIDIA
Miguel Martinez, Senior Deep Learning Data Scientist, NVIDIA
Ross Verrall, Enterprise Services Lead, NVIDIA
A free virtual event, hosted by the NVIDIA Deep Learning Institute.
November 17, 8:00 a.m. PT / 5:00 p.m. CEST
Join us for an exciting and interactive day delving into cutting-edge techniques in large-language-model (LLM) application development.
LLM Day will offer hands-on, practical guidance from LLM practitioners, who will share their insights and best-practices for getting started with and advancing LLM application development.