NVIDIA创始人兼首席执行官黄仁勋近日在一次公开评论中，对OpenAI首席执行官Altman的宏大芯片投资计划表示了质疑。Altman计划筹集高达7万亿美元的资金，以建立一个庞大的芯片供应网络，以满足人工智能领域日益增长的芯片需求。然而，黄仁勋对此持有不同观点，他认为当前的算力成本已经显著下降，如此庞大的投资可能并不实际。
黄仁勋强调，芯片行业的重点已经从单纯增加产能转向了提升芯片的复杂性和效率。他表示，尽管人工智能的发展需要强大的计算能力，但这并不必然意味着需要天文数字的资金投入。他指出，随着技术的进步，算力成本的降低已经成为趋势，因此花费数万亿美元来扩大产能显得过于激进。
此外，知名芯片架构师Keller也对Altman的计划提出了批评。他幽默地表示，实现同样的芯片梦，他相信自己只需要不到1万亿美元就能完成。Keller的观点进一步强化了对于Altman计划成本效益的质疑，暗示通过更高效的设计和创新或许能以更小的代价达到目标。
这一讨论反映了业界对于AI芯片发展路径的分歧，一方面，有人主张通过大规模投资推动产能扩张；另一方面，有人认为应更注重技术创新和成本优化。随着AI技术的快速发展，如何平衡投资与效率，将成为行业未来的关键议题。
英语如下：
News Title: “Jensen Huang Critiques Altman’s Chip Ambition: Trillions Invested, But Costs Have Significantly Declined”
Keywords: Altman’s Chip Vision, Jensen Huang’s Comments, Keller’s Mockery
News Content: NVIDIA’s founder and CEO, Jensen Huang, recently expressed skepticism about OpenAI CEO Altman’s ambitious plan to invest up to $7 trillion in building a massive chip supply network to cater to the growing demand for chips in the AI sector. Huang believes that the current cost of computing power has significantly dropped, making such a colossal investment questionable.
Huang emphasized that the focus of the chip industry has shifted from merely increasing production capacity to enhancing chip complexity and efficiency. While acknowledging that AI development requires substantial computing power, he argues that it doesn’t necessarily entail astronomical financial outlays. He pointed out that with technological advancements, the decline in computational power costs has become a trend, rendering a trillion-dollar expansion in capacity too aggressive.
Furthermore, renowned chip architect Keller also criticized Altman’s plan, joking that he could achieve a similar chip dream for less than a trillion dollars. Keller’s perspective reinforces doubts about the cost-effectiveness of Altman’s proposal, suggesting that more efficient design and innovation might achieve the goal at a lower cost.
This debate reflects the industry’s分歧 on the path for AI chip development. On one hand, some advocate for large-scale investment to boost capacity; on the other hand, others emphasize technological innovation and cost optimization. As AI technology rapidly evolves, striking a balance between investment and efficiency will be a crucial issue for the industry’s future.
【来源】https://www.cls.cn/detail/1597132
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