fbpx

Mark Huang

Hear from Mark Huang at The AI Conference 2024!
Co-Founder
Gradient

Panel Discussion:

Building Agents

Panel Summary:

Atom icon for The AI Conference 2023, a groundbreaking two-day event on AGI, LLMs, Infrastructure, Alignment, AI Startups, and Neural Architectures.

Discover the key principles and methodologies in designing and implementing intelligent agents with our distinguished panel. 

Brain icon for The AI Conference 2023, a groundbreaking two-day event on AGI, LLMs, Infrastructure, Alignment, AI Startups, and Neural Architectures.The panelists will share their experiences in developing various types of agents and discuss the challenges and solutions to building robust, production-ready agentic systems.

 

2024 Panel Preview Topics

2023 Conference Video

2023 Slides

2023 Presentation Title:

The Next Million AI Systems

2023 Presentation Summary:

Atom icon for The AI Conference 2023, a groundbreaking two-day event on AGI, LLMs, Infrastructure, Alignment, AI Startups, and Neural Architectures.

Gradient’s mission is to provide the most seamless development platform for easily customizing open-source Language Models (LLMs) and integrating them seamlessly into various AI applications. Our users can leverage our simple APIs to power the next generation of AI-embedded products.

Brain icon for The AI Conference 2023, a groundbreaking two-day event on AGI, LLMs, Infrastructure, Alignment, AI Startups, and Neural Architectures.This presentation delves into the paradigm shift toward “The Next Million AI Systems.” By democratizing AI model creation, we can substantially reduce barriers to entry, allowing us to prioritize the development of holistic AI systems over standalone models. We will also explore the technical advantages of fine-tuning and the utilization of a mixture of experts, showcasing how these techniques enhance the robustness and adaptability of AI systems, ultimately redefining the AI landscape.
 

About | Mark Huang

Mark Huang is co-founder and Chief Architect at Gradient. Gradient helps enterprises automate business processes using agents. Their platform flexibly handles and incorporates private data to seamlessly deliver full AI automation.

Known for his pioneering work in LLMs and fine-tuning, Mark is a frequent contributor to the AI and MLOps community. Prior to Gradient, Mark led machine learning teams at Splunk and Box, transitioning over from a nearly decade-long career as an algorithmic trader at quantitative hedge funds like Stevens Capital, Paloma Partners, and TD Securities. Mark holds a dual bachelors degree in mathematics and finance from the University of Pennsylvania.