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大喵(8年前端讲师,能教你学会编程)
2周前
我得说,这个观点/认知我在23年初刚刚接触ai并用它写过一点点代码后就有了,我很难想象到了25年中才有人终于写文章正经说,在我看来这种文章早在23年初就应该出现(我之所以自己没写也是因为我不常写博客,并且我觉得在那个时候写,一定会被人骂“你就是见不得ai好,你前端要被ai已死了,你还想回光返照一下”),简直离谱,只能说大部分拿ai写代码的要么全在吹,要么就是本来就不怎么会写代码的。。。直到前两个月,我发了几篇推文说,你都想从事程序员/软件开发了,难道仅仅因为ai能写,你就拿不出半年时间学一下,把基本功打好吗?
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Mr Panda
3周前
今年的wwdc 一年都不专业,这可是全世界市值最强的公司,他们有着全世界最好的设计师、工程师、产品经理, 结果就给我们看这些东西。 ipad os 真是太能忽悠了,在我看来苹果公司就是想继续让用户既买macbook, 又要买ipad 。
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Mr Panda
3个月前
吴军在他的一篇专栏文章里,提到人形机器人是一个伪命题,就是人的执念,其实解决不了什么问题。
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***土隹
3个月前
大半年过去了,回头再看当初苹果在AI上吹的牛,原来库克说的Apple Intelligence就是你可以在Apple产品里使用别人家的AI。
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Susan/STEM MOM
5个月前
Dave's Garage对于Deepseek 的评价,10个小时破百万。他还是不错的,算是我的硬核博主单。 Title: Deepseek R1 Explained by a Retired Microsoft Engineer Author: Dave's Garage Upload Date: 2025-01-28T02:47:25Z URL: Let me help break this detailed technical presentation into time blocks, providing context for each section to help build a comprehensive understanding: 0:00-2:30 Introduction and Context Setting Dave Plumber, a retired Microsoft engineer from the MS-DOS and Windows 95 era, introduces Deep Seek R1 as a "Sputnik moment" in AI development. He frames this Chinese open-source AI model as a significant technological milestone that's challenging Western assumptions about AI dominance. 2:30-5:00 Economic Impact and Market Significance A critical discussion of how Deep Seek R1's reported $6 million development cost has rattled the tech industry, particularly affecting Nvidia and Microsoft stock prices. The presenter draws an apt analogy: it's like building a Ferrari in your garage using Chevy parts, which challenges the entire premium AI development ecosystem. 5:00-8:30 Technical Architecture Explanation Details Deep Seek R1's fundamental architecture as a distilled language model. Dave explains how it leverages larger AI models like GPT-4 or Meta's Llama as scaffolding, using an insightful apprenticeship analogy to explain model distillation - where a smaller model learns from larger ones without needing to replicate their entire knowledge base. 8:30-12:00 Training Methodology Deep Dive Explores how Deep Seek R1 combines insights from multiple AI architectures, comparing it to assembling a panel of experts to train one exceptional student. This section includes practical demonstrations of the model's capabilities, including its handling of sensitive topics like Tiananmen Square. 12:00-15:30 Hardware Requirements and Accessibility Detailed discussion of running Deep Seek R1 on various hardware configurations, from high-end AMD Threadrippers to consumer-grade MacBooks and even $249 Ora Nano systems. This section emphasizes the model's accessibility compared to traditional AI infrastructure requirements. 15:30-19:00 Limitations and Trade-offs Thoughtful analysis of the model's potential drawbacks, including increased likelihood of hallucinations and limitations in specialized knowledge domains. Dave draws parallels to the early personal computing era, suggesting Deep Seek R1 might represent a similar democratizing force in AI. 19:00-22:30 Global Implications and Competition Examines how Deep Seek R1's release affects the global AI landscape, particularly its impact on American tech companies and their business models. Discusses the potential democratization of AI access worldwide. 22:30-25:00 Critical Analysis and Skepticism Addresses skepticism about Deep Seek's development claims, including the possibility of undisclosed state-level support and strategic implications for global AI competition. 25:00-27:00 Conclusion and Channel Information Wraps up with final thoughts on Deep Seek R1's significance and includes standard YouTube engagement requests and information about Dave's other content, including his book on autism spectrum experiences. This timeline breakdown reveals how Dave skillfully builds from basic concepts to complex implications, helping viewers understand both the technical and strategic significance of Deep Seek R1 in the evolving AI landscape.
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