The promise of State Space Models - Karan Goel (Co-founder & CEO of Cartesia)

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Welcome to AI in the Real World! In this episode, Foundation Capital Partner Jaya Gupta sits down with Karan Goel, co-founder and CEO of Cartesia, a company pioneering the use of state space models (SSMs) for AI applications. Karan shared his journey from pursuing a PhD at Stanford to co-founding Cartesia with Albert Gu — taking their academic research on SSMs and turning it into a product that is initially focused on voice applications. Karan explained how SSMs differ fundamentally from transformers, offering a more efficient, memory-based architecture that processes information sequentially rather than in batches. This approach enables more human-like AI systems that can remember and adapt to new information in real-time. The conversation also covers:

  • How SSMs offer significant efficiency advantages for applications like voice agents and on-device AI

  • Why architecture innovation remains crucial alongside advances in data and training techniques

  • The challenges and opportunities in the voice AI space

  • His perspective on the open-weights vs. closed-model debate in AI

  • Advice for researchers who want to become founders

Chapters:

  • 00:05 Cold open

  • 01:47 Karan’s founder journey

  • 03:45 Transitioning from academia to entrepreneurship

  • 05:17 The art of recruiting

  • 09:22 Karan’s vision for Cartesia

  • 13:36 Innovation in AI architectures

  • 16:33 Advantages of State Space Models (SSMs)

  • 19:34 The false dichotomy: models vs. applications

  • 21:17 Best practices for voice AI

  • 25:10 Thoughts on the broader AI landscape

  • 31:37 Open source vs. closed models

  • 35:00 Karan’s thoughts on fundraising

  • 41:27 Advice for founders building AI startups

  • 46:03 Upcoming trends that get Karan excited

Posted

0 MIN READ

Show Outline

Welcome to AI in the Real World! In this episode, Foundation Capital Partner Jaya Gupta sits down with Karan Goel, co-founder and CEO of Cartesia, a company pioneering the use of state space models (SSMs) for AI applications. Karan shared his journey from pursuing a PhD at Stanford to co-founding Cartesia with Albert Gu — taking their academic research on SSMs and turning it into a product that is initially focused on voice applications. Karan explained how SSMs differ fundamentally from transformers, offering a more efficient, memory-based architecture that processes information sequentially rather than in batches. This approach enables more human-like AI systems that can remember and adapt to new information in real-time. The conversation also covers:

  • How SSMs offer significant efficiency advantages for applications like voice agents and on-device AI

  • Why architecture innovation remains crucial alongside advances in data and training techniques

  • The challenges and opportunities in the voice AI space

  • His perspective on the open-weights vs. closed-model debate in AI

  • Advice for researchers who want to become founders

Chapters:

  • 00:05 Cold open

  • 01:47 Karan’s founder journey

  • 03:45 Transitioning from academia to entrepreneurship

  • 05:17 The art of recruiting

  • 09:22 Karan’s vision for Cartesia

  • 13:36 Innovation in AI architectures

  • 16:33 Advantages of State Space Models (SSMs)

  • 19:34 The false dichotomy: models vs. applications

  • 21:17 Best practices for voice AI

  • 25:10 Thoughts on the broader AI landscape

  • 31:37 Open source vs. closed models

  • 35:00 Karan’s thoughts on fundraising

  • 41:27 Advice for founders building AI startups

  • 46:03 Upcoming trends that get Karan excited

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