cover of episode #459 – DeepSeek, China, OpenAI, NVIDIA, xAI, TSMC, Stargate, and AI Megaclusters

#459 – DeepSeek, China, OpenAI, NVIDIA, xAI, TSMC, Stargate, and AI Megaclusters

2025/2/3
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Dylan Patel: 我专注于半导体、GPU和AI硬件的研究与分析。DeepSeek模型的低廉成本与其高效的模型架构和训练技术有关,这使得它对其他公司产生了巨大的压力,并引发了关于美国对中国出口管制的讨论。同时,DeepSeek模型的出现也加剧了中美之间的科技竞争,并可能对台海局势产生影响。 从技术角度来看,DeepSeek模型的成功之处在于其混合专家模型和潜在注意力机制,这使得模型在训练和推理方面都更加高效。此外,DeepSeek公司拥有大量的GPU资源,这为其模型训练提供了强大的支持。然而,美国对中国的出口管制措施也限制了DeepSeek公司获取先进GPU的能力,这使得他们不得不采用一些创新的技术来提高效率。 从地缘政治角度来看,DeepSeek模型的出现加剧了中美之间的科技竞争,并可能对台海局势产生影响。美国政府实施出口管制,旨在限制中国获取先进AI技术的能力,但这种做法也可能导致中国采取反制措施,加剧国际紧张局势。 总的来说,DeepSeek模型的出现是一个重要的事件,它不仅对AI技术的发展具有重要意义,也对国际地缘政治格局产生了深远的影响。 Nathan Lambert: 我是艾伦人工智能研究所的研究科学家,专注于AI研究和开源AI模型。DeepSeek模型的开源权重和宽松的许可证,对AI行业产生了深远的影响,促使其他公司也向开源方向发展。DeepSeek模型的低廉成本与其高效的模型架构和训练技术有关,这使得它对其他公司产生了巨大的压力,并引发了关于美国对中国出口管制的讨论。 从技术角度来看,DeepSeek v3和DeepSeek R1都基于相同的预训练模型,但经过不同的后训练处理,分别得到指令模型和推理模型。DeepSeq R1模型的推理速度非常快,并且能够展示其推理过程,这使得它在推理任务中具有显著的优势。DeepSeq模型的低廉成本主要归功于其混合专家模型和潜在注意力机制,这两种技术都能够显著降低训练和推理的计算成本。 从开源角度来看,DeepSeek模型的开放权重和宽松的许可证,使得其他研究人员和公司能够更容易地访问和使用该模型,这促进了AI技术的开放和共享。然而,这也引发了关于数据安全和知识产权的担忧。 总的来说,DeepSeek模型的出现是一个重要的里程碑,它不仅推动了AI技术的发展,也对AI行业的开放和共享产生了深远的影响。

Deep Dive

Shownotes Transcript

Dylan Patel is the founder of SemiAnalysis, a research & analysis company specializing in semiconductors, GPUs, CPUs, and AI hardware. Nathan Lambert is a research scientist at the Allen Institute for AI (Ai2) and the author of a blog on AI called Interconnects. Thank you for listening ❤ Check out our sponsors: https://lexfridman.com/sponsors/ep459-sc) See below for timestamps, and to give feedback, submit questions, contact Lex, etc.

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EPISODE LINKS: Dylan’s X: https://x.com/dylan522p) SemiAnalysis: https://semianalysis.com/) Nathan’s X: https://x.com/natolambert) Nathan’s Blog: https://www.interconnects.ai/) Nathan’s Podcast: https://www.interconnects.ai/podcast) Nathan’s Website: https://www.natolambert.com/) Nathan’s YouTube: https://youtube.com/@natolambert) Nathan’s Book: https://rlhfbook.com/)

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OUTLINE: (00:00) – Introduction (13:28) – DeepSeek-R1 and DeepSeek-V3 (35:02) – Low cost of training (1:01:19) – DeepSeek compute cluster (1:08:52) – Export controls on GPUs to China (1:19:10) – AGI timeline (1:28:35) – China’s manufacturing capacity (1:36:30) – Cold war with China (1:41:00) – TSMC and Taiwan (2:04:38) – Best GPUs for AI (2:19:30) – Why DeepSeek is so cheap (2:32:49) – Espionage (2:41:52) – Censorship (2:54:46) – Andrej Karpathy and magic of RL (3:05:17) – OpenAI o3-mini vs DeepSeek r1 (3:24:25) – NVIDIA (3:28:53) – GPU smuggling (3:35:30) – DeepSeek training on OpenAI data (3:45:59) – AI megaclusters (4:21:21) – Who wins the race to AGI? (4:31:34) – AI agents (4:40:16) – Programming and AI (4:47:43) – Open source (4:56:55) – Stargate (5:04:24) – Future of AI

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