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20VC: AI's Biggest Questions: The Commoditisation of LLMs, Open vs Closed: Who Wins, Model Size vs Data Quality, Why Google are Vulnerable and Apple are the Dark Horse

Nov 24, 2023

Des Traynor, Co-founder of Intercom, and Yann LeCun, AI pioneer at Meta and NYU, dive into the future of AI. They dissect the fight between open-source and closed models, emphasizing the rise of collaborative approaches. The duo also tackles the commoditization of large language models and the critical importance of data diversity. They explore the shift in AI business models towards outcome-based pricing and debate the roles of intelligent assistants—highlighting Apple's unique position against giants like Google and Amazon.

33:24

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Episode guests

Yann LeCun

Des Traynor

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Quick takeaways

There will likely be only five or six major foundational model companies in the world in the next three to five years, with companies like Meta, Google, Microsoft, OpenAI, and Apple leading the way in training these models.

The debate between open-source and closed AI models continues, with open-source allowing for greater collaboration, innovation, and contributions, while closed models offer advantages in terms of understanding, control, and differentiation.

Deep dives

The future of AI model providers

According to the panelists, there will likely be only five or six major foundational model companies in the world in the next three to five years, with companies like Meta, Google, Microsoft, OpenAI, and Apple leading the way in training these models. While some believe in the commoditization of language models (LLMs), others argue that there is still a lack of equal quality among LLMs and that it is a work in progress.

The Future of AI: Transitioning to Consumption-Based Pricing

01:29

Sponsoring Injections into the LLM and Google's Future in AI

02:05

The Importance of Cultural and Personal Data Sets for AI Models

01:16

Intro

2min

The Future of AI: Open-Source vs. Closed Models

8min

Navigating Value: Infrastructure vs. Application in AI

3min

Rethinking AI Business Models

5min

The Role of Co-Pilots in AI: Incumbents vs Startups

2min

The Future of Intelligent Assistants

13min

Des Traynor is a Co-Founder of Intercom, and has built and led many teams within the company, including Product, Marketing, and Customer Support.

Yann LeCun is VP & Chief AI Scientist at Meta and Silver Professor at NYU affiliated with the Courant Institute of Mathematical Sciences & the Center for Data Science. He was the founding Director of FAIR and of the NYU Center for Data Science.

Emad Mostaque is the Co-Founder and CEO @ StabilityAI, the parent company of Stable Diffusion. Stability are building the foundation to activate humanity’s potential.

Jeff Seibert is the Founder & CEO @ Digits, building the future of AI-powered accounting. Digits have raised funding from the likes of Peter Fenton @ Benchmark and 20VC.

Tomasz Tunguz is the Founder and General Partner @ Theory Ventures, just announced last week, Theory is a $230M fund that invests $1-25m in early-stage companies that leverage technology discontinuities into go-to-market advantages.

Douwe Kiela is the CEO of Contextual AI, building the contextual language model to power the future of businesses.

Cris Valenzuela is the CEO and co-founder of Runway, the company that trains and builds generative AI models for content creation.

Richard Socher is the founder and CEO of You.com. Richard previously served as the Chief Scientist and EVP at Salesforce. Before that, Richard was the CEO/CTO of AI startup MetaMind, acquired by Salesforce in 2016.

In Today's Episode We Discuss:

Foundational Models: Analysis

Will foundational models become commoditized?
Who are the major players? What are their different strengths?
Who will win? Who will lose?
How important is the size of the model vs the quality of the data?

2. Open vs Closed:

What are the biggest pros and cons of an open ecosystem for LLMs?
Why is it naive to think that open-source LLMs will prevail?
What will determine which method wins?

3. An Analysis of the Incumbents:

Why is Google the most vulnerable? What can they do to regain ground?
Why is Apple the sleeping giant? How could they win the next wave of AI?
What should Amazon do today to compete with Microsoft?

4. The Future: Doom and Gloom?

Why is it ridiculous to assume AI systems want to dominate?
Why will AI create a renaissance of creativity and human freedom?
What role should regulation play in the advancement and progression of AI?

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