Bring AI Inference Home. Lose the Token Tax.
Abstract
Your AI bill is growing faster than the workloads behind it with coding agents and agentic workflows. Every task burns more tokens and sensitive context leaves your perimeter. Someone else is holding the meter. In this session, Saad will demo Launchpad for AI, a packaged private AI inference stack for running open-source models on AMD Instinct GPUs on-prem. He'll show how intelligent routing sends requests to local or frontier models based on policy, with token metering and governance YOU control.
July 22, 2026 2:20 PM - 2:35 PM PDT
Speakers
Related Sessions
-
Unlocking Secure Enterprise Intelligence at Scale with Cisco
Unlocking Secure Enterprise Intelligence at Scale with Cisco
As organizations transition from AI experimentation to production-scale infrastructure, demand for high-performance compute must be matched by security and reliability. This session explores Cisco's vision for secure, high-performance AI environments and a framework for accelerating AI deployment while mitigating risks associated with large-scale data processing. Learn how the Cisco UCS C845A M8 and AMD are enabling the next generation of enterprise AI.;As organizations transition from AI experimentation to production-scale infrastructure, demand for high-performance compute must be matched by security and reliability. This session explores Cisco's vision for secure, high-performance AI environments and a framework for accelerating AI deployment while mitigating risks associated with large-scale data processing. Learn how the Cisco UCS C845A M8 and AMD are enabling the next generation of enterprise AI.
July 23, 2026
-
Build an MRI Analysis Agent with AMD Blueprints
Build an MRI Analysis Agent with AMD Blueprints
Build and deploy an AI-powered MRI analysis agent in minutes using the AMD mri-doc Solution Blueprint. Run a Gradio-based pipeline that accepts DICOM, NIfTI, and standard image formats, applies tissue segmentation and anomaly detection, and generates LLM-drafted clinical reports on AMD Instinct GPUs. Then customize: swap the LLM AIM, reuse an existing model endpoint, or extend the pipeline for your specific clinical workflow.;Build and deploy an AI-powered MRI analysis agent in minutes using the AMD mri-doc Solution Blueprint. Run a Gradio-based pipeline that accepts DICOM, NIfTI, and standard image formats, applies tissue segmentation and anomaly detection, and generates LLM-drafted clinical reports on AMD Instinct GPUs. Then customize: swap the LLM AIM, reuse an existing model endpoint, or extend the pipeline for your specific clinical workflow.
July 23, 2026
-
Right Size Your Memory Footprint to Move IT Refresh Forward
Right Size Your Memory Footprint to Move IT Refresh Forward
Memory has rarely been in such short supply and is impeding customer data center refresh plans. In this interactive conversation, we’ll discuss tips and tools for right-sizing memory configurations to help move your data center efficiency initiatives forward and preserve ROI. Bring your questions and our experts will provide answers!;Memory has rarely been in such short supply and is impeding customer data center refresh plans. In this interactive conversation, we’ll discuss tips and tools for right-sizing memory configurations to help move your data center efficiency initiatives forward and preserve ROI. Bring your questions and our experts will provide answers!
July 23, 2026
-
Training at Scale with AMD Primus
Training at Scale with AMD Primus
Primus makes large-scale training on Instinct reliable, debuggable and highly performant. It supports the latest OSS training frameworks, models, and is expanding support to new, cutting-edge model architectures, training techniques, and datatypes. SOTA pre and post training performance with Primus, proven at scales of thousands of GPUs, positions an AMD Instinct GPU as a competitive solution for model development at frontier labs, enterprises, and AI startups.;Primus makes large-scale training on Instinct reliable, debuggable and highly performant. It supports the latest OSS training frameworks, models, and is expanding support to new, cutting-edge model architectures, training techniques, and datatypes. SOTA pre and post training performance with Primus, proven at scales of thousands of GPUs, positions an AMD Instinct GPU as a competitive solution for model development at frontier labs, enterprises, and AI startups.
July 23, 2026
-
Scaling AI in Production with Vultr
Scaling AI in Production with Vultr
Explore how enterprises can scale AI from training to inference using AMD-powered infrastructure on Vultr. Through a deep dive into the University of Cambridge's Tessera model, learn how organizations can accelerate AI deployment, improve operational efficiency, and scale globally. The session also highlights real-world AI initiatives across healthcare, retail, finance, manufacturing, and hospitality.;Explore how enterprises can scale AI from training to inference using AMD-powered infrastructure on Vultr. Through a deep dive into the University of Cambridge's Tessera model, learn how organizations can accelerate AI deployment, improve operational efficiency, and scale globally. The session also highlights real-world AI initiatives across healthcare, retail, finance, manufacturing, and hospitality.
July 23, 2026
-
Inside AMD IT: Our Enterprise AI Journey
Inside AMD IT: Our Enterprise AI Journey
How is AMD using AI to transform its own enterprise IT? Go inside AMD IT's AI journey – from early experimentation to scaled deployment. Learn about AMD IT’s multi-year AI strategy and its strategic investment in Data platform to enable AI to automate mega process workflows, accelerate delivery, and drive measurable business outcomes. Whether you are starting your AI journey or scaling existing initiatives, this insider view offers practical lessons on strategy, adoption, and change.;How is AMD using AI to transform its own enterprise IT? Go inside AMD IT's AI journey – from early experimentation to scaled deployment. Learn about AMD IT’s multi-year AI strategy and its strategic investment in Data platform to enable AI to automate mega process workflows, accelerate delivery, and drive measurable business outcomes. Whether you are starting your AI journey or scaling existing initiatives, this insider view offers practical lessons on strategy, adoption, and change.
July 23, 2026
-
Lessons Learned Training ZAYA1-74B End-to-End on AMD
Lessons Learned Training ZAYA1-74B End-to-End on AMD
ZAYA1-74B is a 74B-parameter MoE (4B active) pretrained and post-trained end-to-end on AMD MI300X. We share what it took: a co-designed stack with CCA attention, expert-context-parallel folding, and sliding-window layers that halve KV cache, plus an RL pipeline that sharpens math and code and hardens multi-turn agentic tool use. The result is a competitive long-context, Apache 2.0 model, proving the full train-to-RL loop runs effectively on AMD.;ZAYA1-74B is a 74B-parameter MoE (4B active) pretrained and post-trained end-to-end on AMD MI300X. We share what it took: a co-designed stack with CCA attention, expert-context-parallel folding, and sliding-window layers that halve KV cache, plus an RL pipeline that sharpens math and code and hardens multi-turn agentic tool use. The result is a competitive long-context, Apache 2.0 model, proving the full train-to-RL loop runs effectively on AMD.
July 23, 2026
-
Production-Ready AI Training and Inference with Vultr
Production-Ready AI Training and Inference with Vultr
AI teams need more than GPUs to move models into production. Hear how organizations build training pipelines and deliver production inference on Vultr using AMD Instinct GPUs and ROCm, with attention to data locality, secure networking, Kubernetes orchestration, benchmarking, cost controls, and scale-out operations. Attendees will leave with a blueprint for running AI workloads that are fast, portable, and ready for production use.;AI teams need more than GPUs to move models into production. Hear how organizations build training pipelines and deliver production inference on Vultr using AMD Instinct GPUs and ROCm, with attention to data locality, secure networking, Kubernetes orchestration, benchmarking, cost controls, and scale-out operations. Attendees will leave with a blueprint for running AI workloads that are fast, portable, and ready for production use.
July 23, 2026