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İçerik EPIIPLUS 1 Ltd / Azeem Azhar and Azeem Azhar tarafından sağlanmıştır. Bölümler, grafikler ve podcast açıklamaları dahil tüm podcast içeriği doğrudan EPIIPLUS 1 Ltd / Azeem Azhar and Azeem Azhar veya podcast platform ortağı tarafından yüklenir ve sağlanır. Birinin telif hakkıyla korunan çalışmanızı izniniz olmadan kullandığını düşünüyorsanız burada https://tr.player.fm/legal özetlenen süreci takip edebilirsiniz.
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AI in 2025 – A global perspective, with Kai-Fu Lee

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Manage episode 458878246 series 2615510
İçerik EPIIPLUS 1 Ltd / Azeem Azhar and Azeem Azhar tarafından sağlanmıştır. Bölümler, grafikler ve podcast açıklamaları dahil tüm podcast içeriği doğrudan EPIIPLUS 1 Ltd / Azeem Azhar and Azeem Azhar veya podcast platform ortağı tarafından yüklenir ve sağlanır. Birinin telif hakkıyla korunan çalışmanızı izniniz olmadan kullandığını düşünüyorsanız burada https://tr.player.fm/legal özetlenen süreci takip edebilirsiniz.

Kai-Fu Lee joins me to discuss AI in 2025. Kai-Fu is a storied AI researcher, investor, inventor and entrepreneur based in Taiwan. As one of the leading AI experts based in Asia, I wanted to get his take on this particular market.

Key insights:

  • Kai-Fu noted that unlike the singular “ChatGPT moment” that stunned Western audiences, the Chinese market encountered generative AI in a more “incremental and distributed” fashion.
  • A particularly fascinating shift is how Chinese enterprises are adopting generative AI. Without the entrenched SaaS layers common in the US, Chinese companies are “rolling their own” solutions. This deep integration might be tougher and messier, but it encourages thorough, domain-specific implementations.
  • We reflected on a structural shift in how we think about productivity software. With AI “conceptualizing” the document and the user providing strategic nudges, it’s akin to reversing the traditional creative process.
  • We’re moving from a training-centric world to an inference-centric one. Models need to be cheaper, faster and less resource-intensive to run, not just to train. For instance, his team at ZeroOne.ai managed to train a top-tier model on “just” 2,000 H100 GPUs and bring inference costs down to 10 cents per million tokens—a fraction of GPT-4’s early costs.
  • In 2025, Kai-Fu predicts, we’ll see fewer “demos” and more “AI-first” applications deploying text, image and video generation tools into real-world workflows.

Connect with us:

  continue reading

185 bölüm

Artwork
iconPaylaş
 
Manage episode 458878246 series 2615510
İçerik EPIIPLUS 1 Ltd / Azeem Azhar and Azeem Azhar tarafından sağlanmıştır. Bölümler, grafikler ve podcast açıklamaları dahil tüm podcast içeriği doğrudan EPIIPLUS 1 Ltd / Azeem Azhar and Azeem Azhar veya podcast platform ortağı tarafından yüklenir ve sağlanır. Birinin telif hakkıyla korunan çalışmanızı izniniz olmadan kullandığını düşünüyorsanız burada https://tr.player.fm/legal özetlenen süreci takip edebilirsiniz.

Kai-Fu Lee joins me to discuss AI in 2025. Kai-Fu is a storied AI researcher, investor, inventor and entrepreneur based in Taiwan. As one of the leading AI experts based in Asia, I wanted to get his take on this particular market.

Key insights:

  • Kai-Fu noted that unlike the singular “ChatGPT moment” that stunned Western audiences, the Chinese market encountered generative AI in a more “incremental and distributed” fashion.
  • A particularly fascinating shift is how Chinese enterprises are adopting generative AI. Without the entrenched SaaS layers common in the US, Chinese companies are “rolling their own” solutions. This deep integration might be tougher and messier, but it encourages thorough, domain-specific implementations.
  • We reflected on a structural shift in how we think about productivity software. With AI “conceptualizing” the document and the user providing strategic nudges, it’s akin to reversing the traditional creative process.
  • We’re moving from a training-centric world to an inference-centric one. Models need to be cheaper, faster and less resource-intensive to run, not just to train. For instance, his team at ZeroOne.ai managed to train a top-tier model on “just” 2,000 H100 GPUs and bring inference costs down to 10 cents per million tokens—a fraction of GPT-4’s early costs.
  • In 2025, Kai-Fu predicts, we’ll see fewer “demos” and more “AI-first” applications deploying text, image and video generation tools into real-world workflows.

Connect with us:

  continue reading

185 bölüm

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