The Twenty Minute VC (20VC): Venture Capital | Startup Funding | The Pitch

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

Jun 24, 2024

David Luan, CEO of Adept and former VP at OpenAI, shares insights on the future of AI models. He explores the evolution of foundation models, predicts Nvidia's move into the model space, and discusses the potential commoditization of models. Luan also touches on the importance of improving reasoning and memory in AI systems and the impact of AI on organizational structures and pricing models.

56:06

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David Luan

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Quick takeaways

Foundation models show no signs of diminishing returns, with only a few key providers expected to dominate.

Nvidia likely to enter the model space for competitive advantage, emphasizing the importance of model commoditization.

AI models need to focus on reasoning capabilities beyond simple scaling, driving advancements in broader data collection methods.

Deep dives

Transition from Research Paper Writing to Solving Major Scientific Problems

The shift in AI focus post-Transformer era was highlighted, moving away from research paper writing towards solving major scientific problems. OpenAI's strategy of tackling significant scientific challenges was recognized early on, emphasizing problem-solving over publishing research papers.

New axes of improving model performance beyond just raw compute

01:06

Importance of Vertical Integration in Enterprise Workflows

01:18

Solving Reasoning and the Future of LLM Providers

01:35

Navigating the Open versus Closed Debate in AI Systems Development

03:10

Intro

4min

Evolution of AI Models and OpenAI's Approach

7min

Advancing Model Performance with Increasing Compute

8min

Enhancing Model Reasoning and the Evolving Landscape of AI Models

15min

Exploring the Distinction Between Traditional RPA and New Agents

3min

Evolving AI Pricing Models and Organizational Impact

16min

Gratitude for an Insightful Discussion and Business Recommendations

4min

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?

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The Twenty Minute VC (20VC): Venture Capital | Startup Funding | The Pitch

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

Episode guests

Podcast summary created with Snipd AI

Quick takeaways

Deep dives

Transition from Research Paper Writing to Solving Major Scientific Problems

Potential of Improved Model Performance and Compute Usage

Evolution of Model Development Towards Reasoning Skills

Contrasting RPA and Agent Systems

Future Vision for AI Agents

New axes of improving model performance beyond just raw compute

Importance of Vertical Integration in Enterprise Workflows

Solving Reasoning and the Future of LLM Providers

Navigating the Open versus Closed Debate in AI Systems Development

Get the Snipd
podcast app

AI-powered
podcast player

Discover
highlights

Save any
moment

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The Twenty Minute VC (20VC): Venture Capital | Startup Funding | The Pitch

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

Episode guests

Podcast summary created with Snipd AI

Quick takeaways

Deep dives

Transition from Research Paper Writing to Solving Major Scientific Problems

Potential of Improved Model Performance and Compute Usage

Evolution of Model Development Towards Reasoning Skills

Contrasting RPA and Agent Systems

Future Vision for AI Agents

New axes of improving model performance beyond just raw compute

Importance of Vertical Integration in Enterprise Workflows

Solving Reasoning and the Future of LLM Providers

Navigating the Open versus Closed Debate in AI Systems Development

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