Allen and Ravid sit down and talk about Parameter Efficient Fine Tuning (PeFT) along with the latest updated in AI/ML news.

Allen and Ravid discuss a topic near and dear to their hearts, LLM Sampling!

In this episode of the Information Bottleneck Podcast, Ravid Shwartz-Ziv and Alan Rausch discuss the latest developments in AI, focusing on the controversial release of GPT-5 and its implications for users. They explore the future of large language models and the importance of sampling techniques in AI.

Chapters

00:00 Introduction to the Information Bottleneck Podcast

01:42 The GPT-5 Debacle: Expectations vs. Reality

05:48 Shifting Paradigms in AI Research

09:46 The Future of Large Language Models

12:56 OpenAI's New Model: A Mixed Bag

17:55 Corporate Dynamics in AI: Mergers and Acquisitions

21:39 The GPU Monopoly: Challenges and Opportunities

25:31 Deep Dive into Samplers in AI

35:38 Innovations in Sampling Techniques

42:31 Dynamic Sampling Methods and Their Implications

51:50 Learning Samplers: A New Frontier

59:51 Recent Papers and Their Impact on AI Research