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

20VC: Raising $500M To Compete in the Race for AGI | Will Scaling Laws Continue: Is Access to Compute Everything | Will Nvidia Continue To Dominate | The Biggest Bottlenecks in the Race for AGI with Eiso Kant, CTO @ Poolside

Oct 7, 2024

Eiso Kant, Co-founder and CEO of Poolside.ai, dives into the competitive world of Artificial General Intelligence (AGI) funding, sharing insights on their recent $500M raise. He discusses how Poolside differentiates itself from other AI models and the challenges of competing with giants like Nvidia. The conversation touches on scaling laws, the future of model performance, and whether $600M is sufficient to remain relevant in the rapidly evolving AI landscape. Kant also explores the dynamics of AI infrastructure and the emotional journey of entrepreneurs.

01:10:32

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Eiso Kant

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Quick takeaways

Poolside is uniquely positioned in the AGI race by focusing on AI tools specifically for software development, leveraging vast code datasets.

The interplay between compute accessibility and data generation is crucial, with Poolside generating synthetic data to enhance AI model performance.

Startups must carve out unique niches amid aggressive corporate spending and price wars in AI development to ensure survival and growth.

Deep dives

The Race for AGI

The journey towards Artificial General Intelligence (AGI) is likened to a race, emphasizing urgency and commitment. There is an ongoing competition among companies to establish themselves in the field of AGI, and the current period is viewed as a foundational moment that will shape the future. Investment rounds, like the recent $500 million funding, are critical for companies to gain traction in this race. The speakers stress the importance of capitalizing on this moment by giving everything they have towards achieving significant advancements in AI.

Understand Costs to Compete in AI

01:49

Invest in Integration to Harvest Innovation

04:05

Costly Foundations for AI's Future

03:40

Strategic Independence: The Value of Choosing Partners Wisely

04:08

Intro

4min

Exploring AGI and Data Dynamics

13min

The Competitive Landscape of AI Infrastructure

16min

The AI Hardware Race: NVIDIA's Dominance and Market Dynamics

10min

The Obsession Behind Entrepreneurial Success

2min

Decentralization vs Centralization in Tech

20min

Valuing Experiences Over Possessions

3min

Gratitude and Startup Financial Insights

3min

Eiso Kant is the Co-Founder and CTO of Poolside.ai, building next-generation AI for software engineering. Just last week, Poolside announced their $500M Series B valuing the company at $3BN. Prior to Poolside, Eiso founded Athenian, a data-enabled engineering platform. Before that, he built source{d} - the world’s first company dedicated to applying AI to code and software.

1. Raising $600M to Compete in the AGI Race:

What is Poolside? How does Poolside differentiate from other general-purpose LLMs?
How much of Poolside’s latest raise will be spent on compute?
How does Eiso feel about large corporates being a large part of startup LLM provider’s funding rounds?
Why did Poolside choose to only accept investment from Nvidia?
Is $600M really enough to compete with the mega war chests of other LLMs?

2. The Big Questions in AI:

Will scaling laws continue? Have we reached a stage of diminishing returns in model performance for LLMs?
What is the biggest barrier to the continued improvement in model performance; data, algorithms or compute?
To what extent will Nvidia’s Blackwell chip create a step function improvement in performance?
What will OpenAI’s GPT5 need to have to be a gamechanger once again?

3. Compute, Chips and Cash:

Does Eiso agree with Larry Ellison; “you need $100BN to play the foundation model game”? What does Eiso believe is the minimum entry price?
Will we see the continuing monopoly of Nvidia? How does Eiso expect the compute landscape to evolve?
Why are Amazon and Google best placed when it comes to reducing cost through their own chip manufacturing?
Does Eiso agree with David Cahn @ Sequoia, “you will never train a frontier model on the same data centre twice”?
Can the speed of data centre establishment and development keep up with the speed of foundation model development?

4. WTF Happens to The Model Layer: OpenAI and Anthropic…

Does Eiso agree we are seeing foundation models become commoditised?
What would Eiso do if he were Sam Altman today?
Is $6.6BN really enough for OpenAI to compete against Google, Meta etc…?
OpenAI at $150BN, Anthropic at $40BN and X.ai at $24BN. Which would Eiso choose to buy and why?

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