EP12: Adversarial attacks and compression with Jack Morris

In this episode of the Information Bottleneck Podcast, we host Jack Morris, a PhD student at Cornell, to discuss adversarial examples (Jack created TextAttack (arxiv.org/abs/2005.05909), 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 - jxmo.io
TextAttack - arxiv.org/abs/2005.05909
How much do language models memorize? arxiv.org/abs/2505.24832
DeepSeek OCR - 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