OpenAI 发布首款自研推理芯片 Jalapeño,由 Broadcom 制造
阅读原文· techcrunch.comOpenAI 周三公布其首款自研推理处理器 Jalapeño,由 Broadcom 设计制造,专为推理系统优化,OpenAI 自身 AI 模型参与了芯片开发。早期测试显示能效比显著优于当前顶尖替代方案。该芯片旨在降低实时编码模型的运行成本,但预训练等高性能任务仍将依赖 Nvidia GPU。OpenAI 称此举使其能全栈优化芯片架构、内核、内存系统、调度等基础设施,以提升模型速度、可靠性和经济性。
On Wednesday, OpenAI unveiled its first custom-built inference processor, designed and manufactured in collaboration with Broadcom. Named Jalapeño, the new processor was designed specifically for the unique needs of OpenAI’s inference systems. OpenAI’s own AI models assisted in the development of the chip, the company said.
While the chip is still being tested, OpenAI says early results show significantly better performance-per-watt than current state-of-the-art alternatives.
The partnership was officially announced in October, but OpenAI’s chip plans have long been rumored as a way to reduce the company’s dependence on Nvidia’s GPUs. Google and Amazon have both built custom chips to serve a similar purpose, often called “AI accelerators” — silicon designed specifically to speed up machine learning workloads.
OpenAI president Greg Brockman explained the company’s approach to chip development on its in-house podcast, shortly after the Broadcom partnership was announced.
“We have a deep understanding of the workload,” Brockman said in the episode. “We’ve really been looking for specific workloads that are underserved, [and asking] how can we build something that will be able to accelerate what’s possible?”
Jalapeño is specifically designed for inference, the process of running pre-built AI models in response to user commands. In the announcement, OpenAI emphasized the chip’s low operating cost when running real-time coding models. It’s likely that more performance-intensive tasks like pre-training will still rely on Nvidia hardware, but even small reductions in inference costs could do a lot to improve the company’s bottom line.
Optimizing that inference system may prove to be a crucial factor in the economics of AI going forward — and it’s likely to take place at every level of the stack. OpenAI is already building agentic products like Codex and the models that power them, as well as data centers to run those models. Moving into purpose-built chips lets the company go even further in that process, as the company explained in its announcement.
“OpenAI is not only developing frontier models or building products on top of them; it is designing the infrastructure underneath them: chip architecture, kernels, memory systems, networking, scheduling, deployment systems, and product experience,” the company wrote. “Because OpenAI operates across the stack, each layer can be optimized around the same goal: making its models faster, more reliable, and more affordable for users.”