Inference hardware

OpenAI Built Its Own Chip in 9 Months

OpenAI Built Its Own Chip in 9 Months

Richard Ho, VP of Hardware at OpenAI, details the development of 'Jalapeño,' OpenAI's first custom AI accelerator. The chip aims to drastically lower inference costs and empower full stack control, achieving a remarkable 9-month tape-out by leveraging AI in chip design. Jalapeño's blank-slate architecture brings memory and compute closer, delivering both high throughput and low latency, outperforming competitors even without speculative decoding, and proving that AI can supercharge expert productivity in complex engineering fields.

Jeff Dean: The 1% Rule for Building in AI

Jeff Dean: The 1% Rule for Building in AI

Jeff Dean discusses the evolution of AI, drawing parallels between Google's past breakthroughs (like fitting search in RAM and the origin of TPUs) and current challenges. He emphasizes that AI is becoming an energy problem, driving the need for specialized inference hardware. Dean highlights 'context engineering' and multi-agent systems as crucial for long-running, complex AI tasks, and offers advice for startups on finding niches where they can outperform larger entities by focusing on specific domains, data, and models. He stresses the importance of clear specifications for agents and 'taste' in problem selection, encouraging founders to question fundamental assumptions and automate the scientific method to build 'AI that builds AI.'