Group 1 - The core observation made by Greg Brockman is that as computational power and data scale rapidly expand, foundational research is making a comeback, and the importance of algorithms is once again highlighted as a key bottleneck for future AI development [1][21][22] - Brockman emphasizes that both engineering and research are equally important in driving AI advancements, and that OpenAI has always maintained a philosophy of treating both disciplines with equal respect [3][6][8] - OpenAI has faced challenges in resource allocation between product development and research, sometimes having to "mortgage the future" by reallocating computational resources originally intended for research to support product launches [8][9][10] Group 2 - The concept of "vibe coding" is discussed, indicating a shift towards serious software engineering practices, where AI is expected to assist in transforming existing applications rather than just creating flashy projects [11][12] - Brockman highlights the need for a robust AI infrastructure that can handle diverse workloads, including both long-term computational tasks and real-time processing demands, which is a complex design challenge [16][18][19] - The future economic landscape is anticipated to be driven by AI, with a diverse model library emerging that will create numerous opportunities for engineers to build systems that enhance productivity and efficiency [24][25][27]
OpenAI掌门人曝GPT-6瓶颈,回答黄仁勋提问,几乎为算力“抵押未来”
3 6 Ke·2025-08-16 04:04