In this episode of the Information Bottleneck Podcast, we host Jack Morris, a PhD student at Cornell, to discuss adversarial examples (Jack created TextAttack, the first software package for LLM jailbreaking), the Platonic representation hypothesis, the implications of inversion techniques, and the role of compression in language models.
Links:
Jack's Website - https://jxmo.io/
TextAttack - https://arxiv.org/abs/2005.05909
How much do language models memorize? https://arxiv.org/abs/2505.24832
DeepSeek OCR - https://www.arxiv.org/abs/2510.18234
Chapters:
00:00 Introduction and AI News Highlights
04:53 The Importance of Fine-Tuning Models
10:01 Challenges in Open Source AI Models
14:34 The Future of Model Scaling and Sparsity
19:39 Exploring Model Routing and User Experience
24:34 Jack's Research: Text Attack and Adversarial Examples
29:33 The Platonic Representation Hypothesis
34:23 Implications of Inversion and Security in AI
39:20 The Role of Compression in Language Models
44:10 Future Directions in AI Research and Personalization
