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20VC: Why Foundation Model Performance is Not Diminishing But Models Are Commoditising, Why Nvidia Will Enter the Model Space and Models Will Enter the Chip Space & The Right Business Model for AI Software with David Luan, Co-Founder @ Adept

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Manage episode 425280595 series 73567
内容由The Twenty Minute VC and Harry Stebbings提供。所有播客内容(包括剧集、图形和播客描述)均由 The Twenty Minute VC and Harry Stebbings 或其播客平台合作伙伴直接上传和提供。如果您认为有人在未经您许可的情况下使用您的受版权保护的作品,您可以按照此处概述的流程进行操作https://zh.player.fm/legal

David Luan is the CEO and Co-Founder at Adept, a company building AI agents for knowledge workers. To date, David has raised over $400M for the company from Greylock, Andrej Karpathy, Scott Belsky, Nvidia, ServiceNow and WorkDay. Previously, he was VP of Engineering at OpenAI, overseeing research on language, supercomputing, RL, safety, and policy and where his teams shipped GPT, CLIP, and DALL-E. He led Google's giant model efforts as a co-lead of Google Brain.

In Today's Episode with David Luan We Discuss:

1. The Biggest Lessons from OpenAI and Google Brain:

  • What did OpenAI realise that no one else did that allowed them to steal the show with ChatGPT?
  • Why did it take 6 years post the introduction of transformers for ChatGPT to be released?
  • What are 1-2 of David's biggest lessons from his time leading teams at OpenAI and Google Brain?

2. Foundation Models: The Hard Truths:

  • Why does David strongly disagree that the performance of foundation models is at a stage of diminishing returns?
  • Why does David believe there will only be 5-7 foundation model providers? What will separate those who win vs those who do not?
  • Does David believe we are seeing the commoditization of foundation models?
  • How and when will we solve core problems of both reasoning and memory for foundation models?

3. Bunding vs Unbundling: Why Chips Are Coming for Models:

  • Why does David believe that Jensen and Nvidia have to move into the model layer to sustain their competitive advantage?
  • Why does David believe that the largest model providers have to make their own chips to make their business model sustainable?
  • What does David believe is the future of the chip and infrastructure layer?

4. The Application Layer: Why Everyone Will Have an Agent:

  • What is the difference between traditional RPA vs agents?
  • Why is agents a 1,000x larger business than RPA?
  • In a world where everyone has an agent, what does the future of work look like?
  • Why does David disagree with the notion of "selling the work" and not the tool?
  • What is the business model for the next generation of application layer AI companies?

  continue reading

1218集单集

Artwork
icon分享
 
Manage episode 425280595 series 73567
内容由The Twenty Minute VC and Harry Stebbings提供。所有播客内容(包括剧集、图形和播客描述)均由 The Twenty Minute VC and Harry Stebbings 或其播客平台合作伙伴直接上传和提供。如果您认为有人在未经您许可的情况下使用您的受版权保护的作品,您可以按照此处概述的流程进行操作https://zh.player.fm/legal

David Luan is the CEO and Co-Founder at Adept, a company building AI agents for knowledge workers. To date, David has raised over $400M for the company from Greylock, Andrej Karpathy, Scott Belsky, Nvidia, ServiceNow and WorkDay. Previously, he was VP of Engineering at OpenAI, overseeing research on language, supercomputing, RL, safety, and policy and where his teams shipped GPT, CLIP, and DALL-E. He led Google's giant model efforts as a co-lead of Google Brain.

In Today's Episode with David Luan We Discuss:

1. The Biggest Lessons from OpenAI and Google Brain:

  • What did OpenAI realise that no one else did that allowed them to steal the show with ChatGPT?
  • Why did it take 6 years post the introduction of transformers for ChatGPT to be released?
  • What are 1-2 of David's biggest lessons from his time leading teams at OpenAI and Google Brain?

2. Foundation Models: The Hard Truths:

  • Why does David strongly disagree that the performance of foundation models is at a stage of diminishing returns?
  • Why does David believe there will only be 5-7 foundation model providers? What will separate those who win vs those who do not?
  • Does David believe we are seeing the commoditization of foundation models?
  • How and when will we solve core problems of both reasoning and memory for foundation models?

3. Bunding vs Unbundling: Why Chips Are Coming for Models:

  • Why does David believe that Jensen and Nvidia have to move into the model layer to sustain their competitive advantage?
  • Why does David believe that the largest model providers have to make their own chips to make their business model sustainable?
  • What does David believe is the future of the chip and infrastructure layer?

4. The Application Layer: Why Everyone Will Have an Agent:

  • What is the difference between traditional RPA vs agents?
  • Why is agents a 1,000x larger business than RPA?
  • In a world where everyone has an agent, what does the future of work look like?
  • Why does David disagree with the notion of "selling the work" and not the tool?
  • What is the business model for the next generation of application layer AI companies?

  continue reading

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