# Ep 89: AI Research Legend’s Honest Assessment of Where We Are

Page: https://stenobird.com/podcast/unsupervised-learning-with-jacob-effron-6041643/ep-89-ai-research-legend-s-honest-assessment-of-where-we-are
Text version: https://stenobird.com/podcast/unsupervised-learning-with-jacob-effron-6041643/ep-89-ai-research-legend-s-honest-assessment-of-where-we-are.md
Podcast: [Unsupervised Learning with Jacob Effron](https://stenobird.com/podcast/unsupervised-learning-with-jacob-effron-6041643)
Published: 2026-06-03T12:50:11+00:00
Episode link: https://unsupervised-learning.simplecast.com/episodes/ep-89-ai-research-legends-honest-assessment-of-where-we-are-3Qm7Jv8G
Audio file: https://cdn.simplecast.com/media/audio/transcoded/b3414ac6-61c8-4752-8722-491e1457c3bf/2c08ad29-5b79-42c0-a40a-6c1af4327f2f/episodes/audio/group/98ba3d90-17b3-480f-8e27-649edf1f188e/group-item/7a6c6941-22de-4556-94af-f0300b36b071/128_default_tc.mp3?aid=rss_feed&feed=dOSE_bdP
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Duration seconds: 4413

## Resource

This episode with Lukasz Kaiser, co-author of the seminal "Attention Is All You Need" transformer paper and former researcher at both Google Brain and OpenAI, is a wide-ranging conversation about the fundamental limits of current AI architectures and whether transformers will continue to dominate or eventually give way to something new. Lukasz brings a rare dual perspective: deep belief in how far the current paradigm has taken us (he's an enthusiastic daily Codex user who's seen 10x productivity gains in his own research), while maintaining genuine intellectual humility about whether transformers can truly generalize the way humans do. The episode weaves together questions about data efficiency, the non-verifiable RL frontier, the coding agent revolution, the open vs. closed source gap, and what the next architectural leap might look like: all filtered through the lens of someone who helped build the foundation the entire field is standing on.

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## Transcript

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