--- title: Zyphra description: This discussion brings together Zyphra and AMD to explore how enterprises can make AI more efficient, scalable, and reliable across the entire AI lifecycle, from model design to infrastructure. image: https://webinars.techstronglearning.com/hubfs/Gemini_Generated_Image_h0mlduh0mlduh0ml.jpg --- Driving AI Efficiency at Scale: A Conversation with Zyphra and AMD No video selected Select a video type in the sidebar. No video selected Select a video type in the sidebar. This discussion brings together Zyphra and AMD to explore how enterprises can make AI more efficient, scalable, and reliable across the entire AI lifecycle, from model design to infrastructure. Quentin Anthony of Zyphra explains how the company evolved from smaller hybrid state space and attention models to building frontier-scale models and deploying them via an inference cloud running on AMD Instinct GPUs. He emphasizes that efficiency is not only a hardware problem but also an architectural choice, as well as one of people and processes, highlighting how AI agents can offload repetitive engineering tasks while expert humans continue to guide research and system design. Yao Fu from AMD focuses on what it takes to deliver large-scale, stable, and observable AI training environments. He highlights AMD’s open-source stack, including ROCm.ai and the Primus Safe framework, which provides reference designs for scalable, fault-tolerant training on Kubernetes-based infrastructure. Together, they address the shifting balance between training and inference, the rise of agentic workflows, and the growing importance of heterogeneous compute to support a wide range of modern AI workloads. ![Quentin Anthony\_headshot-modified](https://webinars.techstronglearning.com/hs-fs/hubfs/Quentin%20Anthony_headshot-modified.png?width=1246&height=1246&name=Quentin%20Anthony_headshot-modified.png "Quentin Anthony_headshot-modified") ### Quentin Anthony ###### VP of AI Engineering - Zyphra Quentin Anthony is VP of AI Engineering at Zyphra, where he leads performance optimization for training and inference of novel model architectures on heterogeneous hardware. Quentin has contributed to many open-source model training pipelines, including GPT-NeoX-20B, Pythia, RWKV, RedPajama-INCITE, and Covenant-72B. With over seven years of experience in high-performance computing and distributed deep learning—spanning Ohio State's Network-Based Computing Laboratory, EleutherAI, StabilityAI, and Microsoft Research's DeepSpeed team—Quentin has contributed to the development of hardware-aware co-design of model architectures, GPU kernels, and communication runtimes for higher training throughput and efficiency. He was lead author of the systems technical report for ZAYA1, the first large-scale mixture-of-experts model trained entirely on AMD Instinct MI300X GPUs, AMD Pensando networking, and ROCm open software.  ![Yao-Fu\_Headshot-modified](https://webinars.techstronglearning.com/hs-fs/hubfs/Yao-Fu_Headshot-modified.png?width=282&height=282&name=Yao-Fu_Headshot-modified.png "Yao-Fu_Headshot-modified") ### Yau Fu ###### PhD., Director, Software Development - AMD Dr. Yao Fu is a Director of Software Development in the AMD AI Group, where he leads efforts in distributed training solutions and performance optimization. Prior to focusing exclusively on training solutions, he spearheaded strategic AI solutions and competitive performance enhancements across AMD platforms—including AI PCs, data center CPUs, and embedded devices. With over six years of experience as a system architect for data center solutions at Xilinx/AMD, Dr. Fu has pioneered foundational methodologies that optimize FPGA-based deep learning solutions for higher throughput, lower latency, and improved power efficiency. His INT8 optimization methodology is widely adopted across deep learning inference solutions on UltraScale and UltraScale+ devices. ![Guy Currier-modified-2](https://webinars.techstronglearning.com/hs-fs/hubfs/Guy%20Currier-modified-2.png?width=447&height=447&name=Guy%20Currier-modified-2.png "Guy Currier-modified-2") ### Guy Currier ###### Research Director - The Futurum Group  Guy is responsible for positioning, go-to-market, and sales guidance across technologies and markets. He has decades of field experience describing technologies, their business and community value, and how they are evaluated and acquired. Guy’s specialty areas include AI, DevOps/cloud-native, enterprise applications, application integration, Big Data, governance-risk-compliance, containerization, virtualization, HPC, CPUs-GPUs-xPUs, and systems lifecycle management. Guy started his technology career as a research director for technology media company Ziff Davis, with stints at PC Magazine, eWeek, and CIO Insight. Prior to joining Visible Impact, he worked at Dell, including postings in marketing, product, and technical marketing groups for a wide range of products, including engineered systems, cloud infrastructure, enterprise software, and mission-critical cloud services. 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