--- 格式版本: 2 标题: "AMD and OpenAI: Collaborating Across Every Layer of the Stack" 原文链接: "https://newsroom.amd.com/news/aai-2026-openai-update/" 发布日期: "2026-07-23" 发布时间校准状态: "found" 发布时间需复核: "否" 发布时间来源: "rule:scrape:provider_published_at" 发布时间证据: "provider publishedAt: 2026-07-23" 发布时间校准原因: "规则确认唯一严格发布时间，来源 scrape:provider_published_at" 发布时间校准置信度: "high" 发布时间候选数量: 7 发布时间严格候选数量: 3 发布时间原页读取状态: "原页面已读取" 发布时间未找到原因: "" 发布时间校准时间: "2026-07-25T22:37:52+08:00" 发布时间仲裁状态: "skipped" 发布时间仲裁尝试次数: 0 发布时间仲裁耗时毫秒: 0 发现时间: "2026-07-25T22:32:27+08:00" 入库时间: "2026-07-25T14:37:52.853Z" 来源平台: "固定入口" 搜索渠道: "fixed_url" 搜索词: "https://www.amd.com/en/newsroom.html" 匹配关键词: - "GPU" - "deployment" - "performance" 相关厂家: - "AMD" - "OpenAI" 相关专家: [] 内容类型: "网页" 抓取工具: "Free Fetch + Defuddle" 清洗工具: "Defuddle Markdown + Defuddle/Readability 正文提取" 原始附件: [] AI优质: "是" AI打分: 100 AI分档: "高置信优质" AI质检状态: "通过" AI打分理由: "AMD官方新闻，详细披露与OpenAI在AI基础设施上的深度合作，涵盖Helios机柜级系统、MI400/MI500架构、软件栈优化及2026下半年部署计划，技术细节与商业信号均充分，时效性极高。" AI质检模型: "deepseek-v4-flash" AI质检时间: "2026-07-27T11:20:46+08:00" AI主题相关性: 20 AI来源权威性: 15 AI新颖性: 20 AI技术细节: 20 AI商业部署信号: 15 AI完整性: 10 采集批次: "2026年7月25日22点32分16秒" 采集批次ID: "20260725-223216-273" 去重键: "https://newsroom.amd.com/news/aai-2026-openai-update" --- ![AMD AAI2026 Keynote 6 16x9](https://newsroom.amd.com/images/2026/07/3aab3311-e70e-4e4a-9f5c-3106c4232975.jpg) Dr. Lisa Su (left), chair and CEO of AMD, speaks with Sachin Katti, vice president of Compute Strategy at OpenAI, during the keynote presentation at Advancing AI 2026 on Thursday, July 23, 2026, in San Francisco. At the annual event, company leaders, partners, developers, customers and enterprise leaders demonstrated how they use AMD technology to build, deploy and scale AI using AMD technology. (Credit: AMD) **Three things you need to know:** - OpenAI feeds AMD early insight into where models are heading; AMD turns that into silicon, systems and software. This loop has shaped the AMD Instinct™ MI400 generation and now extends toward MI500. - Work spanning Triton, Gluon, LLVM and AMD ROCm™ – plus Codex and agentic tools that help write GPU code – means improvements don’t stay locked to one workload; they strengthen the broader AMD ecosystem developers can build on. - OpenAI expects to bring AMD Helios™ online through multiple deployment partners starting in the second half of 2026, marking the initial phase of the 6-gigawatt AMD GPU deployment the companies announced in October 2025. At Advancing AI 2026, AMD and OpenAI showcased a partnership evolving from product collaboration to full-stack co-design. AMD Chair and CEO Dr. Lisa Su and OpenAI Vice President of Compute Strategy Sachin Katti discussed rising compute demand, the work underway to bring AMD Helios™ online, and the need to shape future infrastructure around emerging model requirements. AMD’s Vamsi Boppana and OpenAI’s Philippe Tillet then turned to the software behind that progress – from Triton and Gluon to compiler optimization and AI-assisted GPU programming. Together, the discussions revealed how close collaboration can turn advances in silicon and software into deployable performance for frontier AI systems. ## From MI300X to Helios Katti said AI models are becoming more capable, more agentic and useful across a broader range of tasks. As AI increasingly helps improve software, research and infrastructure itself, demand continues to rise for greater performance, memory, networking and efficiency. The AMD and OpenAI collaboration began with AMD Instinct MI300X GPUs and deepened with MI355X as the teams optimized the software stack, networking and large-scale deployment. The AMD Helios™ rackscale solution, with AMD Instinct™ MI455X GPUs and 6th Gen AMD EPYC™ "Venice" CPUs, has extended the relationship, with engineers from AMD and OpenAI working side by side across hardware, software and systems. OpenAI has had access to Helios systems for several months, allowing its teams to prepare the software and solution stack ahead of deployment. The companies are optimizing GPT-class workloads on the platform, debugging together, sharing data and making decisions quickly. OpenAI expects to begin bringing Helios online through multiple deployment partners in the second half of 2026, with deployments accelerating throughout 2027. This rollout will mark the first phase of the 6-gigawatt deployment the companies announced in October 2025. ## Shaping Future Infrastructure Together The collaboration extends beyond preparing today’s systems for deployment. AMD and OpenAI are aligning their roadmaps so future infrastructure is shaped by the workloads it will serve. At the frontier, performance depends on how compute, memory, networking, power, cooling, rack architecture, software and models operate together. OpenAI gives AMD early insight into how models are changing, where bottlenecks are emerging and what future training and inference workloads will require. AMD can translate those insights into advances across silicon, systems and software. That feedback loop has helped shape the AMD Instinct MI400 generation and is continuing as the companies look further ahead. Katti said OpenAI is excited by what AMD is designing with the Instinct MI500 generation, which looks set to deliver another significant leap in AI capabilities. ![AMD AAI2026 Keynote 5 16x9](https://newsroom.amd.com/images/2026/07/df599893-91c5-4812-bab1-f807506230fb.jpg) AMD AAI2026 Keynote 5 16x9 ## Turning Hardware Advances into Application Performance Tillet emphasized that there is no one-size-fits-all approach to GPU software. OpenAI chooses the programming model that best fits each workload. For research, where speed of iteration is critical, Triton remains a powerful tool for developing GPU kernels quickly. For performance-sensitive workloads such as inference, OpenAI has developed Gluon, a more hardware-aware programming language that gives engineers greater control over how software uses the GPU. AMD and OpenAI are collaborating across both. Their work now spans the software stack down to LLVM code generation, ensuring hardware advances translate into meaningful application performance. Codex is also becoming an increasingly valuable part of this process. It is already strong at helping engineers write Triton code and is becoming more capable with Gluon, allowing teams to explore implementations and adapt software to new hardware more rapidly. ## Using AI to Build Better AI Infrastructure AMD and OpenAI are also jointly researching how AI can improve the systems on which AI runs. Today, expert engineers invest substantial effort translating new models into efficient kernels, compilers, communication libraries and system configurations. AMD and OpenAI are developing technologies that could allow models and agents to automate more of that work The conversations at Advancing AI 2026 made clear that the AMD and OpenAI relationship is about more than deploying infrastructure at scale. By connecting model development with silicon, systems and software, the companies are creating a faster and more collaborative approach to building the infrastructure behind the next generation of AI. Press inquiries: [corporate.pressinquiry@amd.com](mailto:corporate.pressinquiry@amd.com)