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cover of episode The Push for America to Open Source AI
People
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Marc Andreessen
联合创始人和风险投资家，专注于人工智能和技术领域的投资。
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NLW
知名播客主持人和分析师，专注于加密货币和宏观经济分析。
Topics
NLW: DeepSeek的AI模型对美国在人工智能领域的领先地位提出了挑战，尤其是在开源与闭源的辩论中。我观察到，DeepSeek的应用程序因其高质量的推理模型而受欢迎。虽然OpenAI最初是开源的，但后来出于安全考虑改变了政策，停止完全分享研究成果。然而，许多人质疑OpenAI的闭源策略，认为这更多是出于竞争而非安全考虑。DeepSeek的出现改变了关于开源与闭源AI的讨论，促使我们重新思考美国的AI发展策略。 Eric Schmidt: (通过AI生成) DeepSeek的R1推理模型在逻辑任务上与OpenAI的GPT-4相当，且成本更低，其整个模型集合都是开源的，允许任何人复制和构建。中国公司正在成为事实上的开源领导者，而大多数美国公司则保持封闭，这是一个奇怪的转变。为了保持竞争力，美国必须支持开源生态系统的发展。DeepSeek的成功质疑了预训练的重要性，并展示了如何通过强化学习以更低的成本进行推理训练。我认为DeepSeek的发布标志着一个转折点，美国创新的前进道路不仅包括加强开源开发，还包括鼓励分享培训方法和增加对人工智能研发的投资。 Marc Andreessen: (通过NLW引用) 我认为对开源AI的恐惧是为了监管和扼杀开源AI。关于AI的秘密已经泄露，开源实现将大量涌现。每个人都知道如何编写transformer，如何进行RLHF，如何使用强化学习进行推理。除了DeepSeek和LLAMA之外，还将有成千上万的开源实现。这无法被放回盒子里。 Sam Altman: (通过NLW引用) 我认为OpenAI可能在开源问题上站错了队，需要新的开源策略。

Deep Dive

Chapters
The emergence of DeepSeek, a Chinese AI company, has challenged the US's dominance in AI. DeepSeek's open-source models are surprisingly competitive, raising questions about the US's closed-source approach and its implications for future AI development. The discussion covers the cost-effectiveness and performance of DeepSeek's models compared to those of OpenAI.
  • DeepSeek's AI models challenge US AI dominance.
  • DeepSeek's open-source approach contrasts with the closed-source models of US companies.
  • Cost-effectiveness and performance of DeepSeek's models are key discussion points.

Shownotes Transcript

With China’s DeepSeek making waves in AI, pressure is mounting for the U.S. to rethink its stance on open-source models. Former Google CEO Eric Schmidt argues that America's edge in AI may depend on supporting open development. Meanwhile, Sam Altman suggests OpenAI may need a new approach. Is the era of closed AI coming to an end?Brought to you by:

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