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

20VC: Is More Compute the Answer to Model Performance | Why OpenAI Abandons Products, The Biggest Opportunities They Have Not Taken & Analysing Their Race for AGI | What Companies, AI Labs and Startups Get Wrong About AI with Ethan Mollick

Jul 31, 2024

Ethan Mollick, an Associate Professor at the Wharton School and Co-Director of the Generative AI Lab, dives into the pressing issues within AI. He discusses how adding more compute might not yield better models, and why OpenAI may be mishandling consumer product development. Ethan critiques the startup landscape and the challenges of AI adoption, emphasizing the need for user-centered approaches. He also explores the importance of local connections in Venture Capital and the evolving role of AI in education as we approach AGI.

01:08:50

Creator website

Episode guests

Ethan Mollick

AI Summary

Highlights

AI Chapters

Episode notes

Podcast summary created with Snipd AI

Quick takeaways

Ethan Mollick emphasizes the need for companies to realign their product strategies to meet consumer demands amid OpenAI's AGI ambitions.

The rapid advancements in AI models raise questions about their practical implications, highlighting the necessity for ongoing evaluation in transforming industries.

Integrating AI into workplaces requires clear guidelines and training to alleviate employee fears and maximize productivity improvements.

Deep dives

OpenAI's Pursuit of AGI

OpenAI is focusing on achieving Artificial General Intelligence (AGI), prioritizing the development of technologies that could lead to this goal. The company is currently generating substantial revenue, even without a fully developed product offering beyond their chatbot and API. There's a notable contrast between prevailing funding trends and the anticipated emergence of AGI, as many startups appear to be investing in technologies that may not survive an AGI-dominated landscape. This paradox leads to the question of how these companies can thrive if AGI, as perceived by investors, arrives sooner than expected.

Learning Demands Active Engagement with AI

01:29

Master the Craft of AI Integration

01:19

Transparency in AI Use Breeds Innovation

01:19

Embrace Multimodal AI for Innovation

02:01

Intro

4min

From Entrepreneurship to AI: A Journey of Innovation and Education

2min

Navigating the AI Landscape with Llama 3.1

18min

The Importance of Local Connections in Venture Capital and AI

2min

Navigating AI Adoption and Its Challenges

17min

AI's Role in the Future of Education

13min

AI's Energy Landscape and Its Societal Impact

10min

Reflections on AI Insights and Key Industry Resources

3min

Ethan Mollick is the Co-Director of the Generative AI Lab at Wharton, which builds prototypes and conducts research to discover how AI can help humans thrive while mitigating risks. Ethan is also an Associate Professor at the Wharton School of the University of Pennsylvania, where he studies and teaches innovation and entrepreneurship, and also examines the effects of artificial intelligence on work and education. His papers have been published in top journals and his book on AI, Co-Intelligence, is a New York Times bestseller.

In Today's Episode with Ethan Mollick We Discuss:

1. Models: Is More Compute the Answer:

How has Ethan changed his mind on whether we have a lot of room to run in adding more compute to increase model performance?
What will happen with models in the next 12 months that no one expects?
Why will open models immediately be used by bad actors, what should happen as a result?
Data, algorithms, compute, what is the biggest bottleneck and how will this change with time?

2. OpenAI: The Missed Opportunity, Product Roadmap and AGI:

Why does Ethan believe that OpenAI is completely out of touch with creating products that consumers want to use?
Which product did OpenAI shelve that will prove to be a massive mistake?
How does Ethan analyse OpenAI's pursuit of AGI?
Why did Ethan think Brad, COO @ OpenAI's heuristic of "startups should be threatened if they are not excited by a 100x improvement in model" is total BS?

3. VCs, Startups and AI Labs: What the World Does Not Understand:

What do Big AI labs not understand about big companies?
What are the biggest mistakes companies are making when implementing AI?
Why are startups not being ambitious enough with AI today?
What are the single biggest ways consumers can and should be using AI today?

Get the Snipd
podcast app

Unlock the knowledge in podcasts with the podcast player of the future.

AI-powered
podcast player

Listen to all your favourite podcasts with AI-powered features

Discover
highlights

Listen to the best highlights from the podcasts you love and dive into the full episode

Save any
moment

Hear something you like? Tap your headphones to save it with AI-generated key takeaways

Share
& Export

Send highlights to Twitter, WhatsApp or export them to Notion, Readwise & more