A New Approach To AI Models
During last month’s NeurIPS 2025 conference, YC’s Ankit Gupta sat down with Karan Goel, founder and CEO of Cartesia, to explain why today’s AI architectures may be fundamentally limited. They discuss why transformers behave more like retrieval systems than learning systems, how state space models enable compression and abstraction, and why multimodal intelligence may require a whole new approach. The conversation also covers why Cartesia chose AI voice as a wedge product, and how research-driven companies can balance deep technical bets with real-world product discipline.
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Chapters (18)
0:11
Introducing Cartesia
0:26
From Architecture Research to Startup
1:20
What “Architecture Research” Really Means
2:18
Why Transformers Hit a Ceiling
3:33
State Space Models Explained
4:21
Intelligence as Compression
5:47
Retrieval vs. Abstraction
6:41
Hybrid Architectures and the Future
7:13
Why Cartesia Chose Voice AI
8:25
What Multimodality Actually Means
9:20
Audio as a Recipe for Other Modalities
10:09
Tokens, Representations, and Learning Signals
11:37
Learning Representations End-to-End
12:29
Building for the “Average Human”
13:54
Research vs. Product Reality
15:18
One Vision, Ruthlessly Executed
16:28
Product as a Truth Serum for Research
17:25
Startup Gravity Applies to Research Too
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