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, 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