AMD ANNUAL DEVELOPER, CUSTOMER, & PARTNER CONFERENCE
Build AI Systems
That Scale
at Advancing AI
Join hands-on workshops, connect with fellow AI developers, meet the builders behind leading AI projects, and leave with practical skills and tools you can apply immediately.
- Build and deploy AI systems across compute environments
- Hear how leading technology teams optimize AI performance at scale
- Gain direct access to open-source AI infrastructure
- Learn directly from AI luminaries and AMD experts building the future of AI
📍 San Francisco Moscone Center • July 22-23
Real Attendee Feedback
What You’ll Get
Inside Advancing AI
AI LUMINARIES
Learn From the People Building the Field
Hear from researchers, founders, open-source leaders, and technical pioneers moving AI systems from research into production.
HANDS ON-WORKSHOPS
Build With Real Tools
Work through guided sessions using AI frameworks, models, tooling, and production-ready development workflows.
TECHNICAL DEEP DIVES
Go Deeper on Performance
Learn practical optimization techniques for inference, training, deployment, large-scale AI infrastructure and for enabling physical AI on AMD.
AMD AI LEADERSHIP
Get the AMD AI Roadmap
Hear where AMD is taking AI software, hardware, and open infrastructure—and what it means for developers.
DEVELOPER COMMUNITY
Meet Other AI Builders
Connect with developers, researchers, founders, and engineers working through similar AI application and infrastructure challenges.
ECOSYSTEM SHOWCASE
See Working AI Demos
Compare live demos across AI software, hardware, developer tooling, robotics, physical AI, and production infrastructure.
Learn From AI Industry Visionaries
More AI Luminary Speakers to Be Announced!
Featured Workshops
Build Your OpenClaw Agent with Multi-Modal Models
BEGINNER • WORKSHOP • HANDS-ON
This is a beginner level hands-on class which will show you how to build your own OpenClaw agent using opensource multi-modal models. This course will also show you how to set up an opensource model server with vLLM/SGLang and connect your agent to it.
You'll Learn
- How OpenClaw agents use multimodal models for text, image, and other inputs
- How to set up an open-source model server using vLLM or SGLang
- How to connect your AI agent to a model endpoint
- How to customize your agent for specific tasks and build custom skills for your needs
- How to add multiple agents and delegate different tasks to each
Prerequisites
- Basic Python familiarity
- Basic understanding of LLMs or multimodal models
- Laptop with development environment access
- No prior OpenClaw experience required
AI & Machine Learning
Cloud Computing
Instinct
EPYC
ROCm
Building Hybrid Multi-Agent Systems from Client to Cloud
INTERMEDIATE • WORKSHOP • HANDS-ON
This is an intermediate level session to show you how to set-up Agent Computers - a hybrid multi-agent system spanning your personal AI on a Ryzen™ AI PC and Frontier AI models deployed on AMD Instinct GPUs for most optimum token expenditure and performance.
You'll Learn
- How to structure a hybrid multi-agent system across client and cloud environments
- How to run personal AI workflows locally on a Ryzen AI PC
- How to connect local agents to frontier models deployed on AMD Instinct GPUs
- How to route tasks between local and cloud models based on performance, cost, and latency needs
- How hybrid agent architectures can reduce token spend while improving end-user responsiveness
Prerequisites
- Recommended: Build Your OpenClaw Agent with Multi-Modals Models
- Basic understanding of client/cloud architecture
- Comfort with hands-on technical workshopss
AI & Machine Learning
Cloud Computing
Instinct
Radeon
ROCm
Ryzen AI
ROCm® Certified Associate: Architecture, Programming, and Optimization
INTERMEDIATE • CERTIFICATION • HANDS-ON
The ROCm® Certified Associate program at Advancing AI 2026 consists of three 1-hour modules comprising hands-on training in ROCm Fundamentals, AMD GPU architecture, AI and HPC deployment, PyTorch, HIP programming, libraries, CUDA porting, profiling, and performance optimization. Successful completion of all three modules and a final exam are required for ROCm® Certified Associate certification.
You'll Learn
- ROCm ecosystem architecture, installation, compatibility, and deployment workflows
- HIP programming fundamentals and CUDA-to-HIP migration strategies
- GPU architecture concepts, benchmarking, and profiling methodologies
- Building and optimizing AI/HPC applications using ROCm libraries and PyTorch
- Debugging, tuning, and profiling GPU workloads with rocprof and ROCm tools
- Memory optimization, occupancy tuning, and mixed precision acceleration techniques
- Practical performance engineering workflows for AMD Instinct GPUs
Prerequisites
- Familiarity with Linux command-line environments
- Basic programming experience in Python or C/C++
- Foundational understanding of GPU computing or AI/ML workflows
- Recommended: prior exposure to PyTorch, CUDA, or HPC development concept
AI & Machine Learning
Cloud Computing
Ryzen AI
Radeon
ROCm
Instinct
Enabling Physical AI on AMD
BEGINNER • INTERMEDIATE • HANDS-ON
In this beginner-to-intermediate session, users will execute multimodal vision and language models for robotics on the Ryzen™ AI iGPU via ROCm and Python.The session covers model loading and examines how vision and language pipelines integrate to produce actionable robot behavior.
You'll Learn
- How multimodal vision and language models support Physical AI and robotics workflows
- How to load and run models on the Ryzen™ AI iGPU using ROCm and Python
- How vision and language pipelines work together to interpret inputs and generate robot actions
- How AMD software and hardware capabilities can support local Physical AI development
Prerequisites
- Basic Python familiarity
- General understanding of AI models, LLMs, or computer vision concepts
- Beginner-level familiarity with robotics or agent workflows helpful, but not required
Robotics & Physical AI
AI & Machine Learning
Ryzen Embedded
Developer Giveaways
Win Real Hardware.
Build Beyond the Event.
Onsite attendees will have chances to take home developer systems and AAI-ready hardware including AMD Ryzen AI Halo Developer platforms, Radeon GPUs, AI PCs, AMD apparel and more.
Frequently Asked Questions
The Practical Stuff, Answered.
The event is free to attend but registration is required. This event is designed for AI and ML engineers, software developers, data scientists, researchers, and anyone interested in building or experimenting with GPU-accelerated AI using AMD hardware. Sessions are geared toward a range of experience levels.
Register for AAI then build your agenda the week of June 8th. Workshops are first come first serve so be sure to arrive early and secure your spot! Walk-ins are allowed if space permits, but advance registration is strongly recommended.
The program includes a keynote presentation, technical and featured talks, 30+ hands-on workshop sessions, ROCm certification classes and ample networking opportunities with AMD engineers and developer community members.
A laptop is not required for main-stage technical sessions. However, it is required for select workshops, including:
- Build Your OpenClaw Agent with Multi-Modals Models
- Real2Sim for Embodied Data Generation
- Vibe Coding with Local Models
- Building Hybrid Multi-Agent Systems from Client to Cloud
- At scale RL with VERL and MILES
- How To Start Generating Video Clips in 30 Mins on AMD GPUs
- Unlocking LLM Inference Performance with ROCm FlyDSL
- Enterprise AI Reference Stack
- Scaling AI Education and Research with the AMD University ProgramÂ
- Run Agentic AI in Minutes with AMD Blueprints & AIMs
- Inference Performance Tuning with AI Agents
- Accelerating vLLM Inference on AMD Instinct GPUs with AMD ATOM
Member Experience
AMD AI Developer Program
Join the AMD AI Developer Program for workshop prep, Developer Cloud access details, onsite member perks, and resources to keep building after the event.
BUILDING WHAT'S NEXT
Join 1,000+ DevelopersÂ
at Advancing AI
Hands-on workshops and technical sessions are first come first served.
Register Today
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