Young AI Researcher Disrupting the Entire Industry - Ali Behrouz

Ali Behrouz is an AI researcher and the author of two of the most talked about papers in machine learning right now, Titans and Nested Learning. He is a PhD student at Cornell University and a researcher at Google, and his work takes direct aim at one of the field's biggest questions: what comes after the transformer. His paper Nested Learning, which Google's Jeff Dean called a possible paradigm shift, rethinks the whole deep learning stack. In this conversation we get into the back story behind Titans and Nested Learning, how Ali thinks about transformers and where they fall short, the idea that all of deep learning is really associative memory, and his newer work on giving models a kind of "sleep" phase to consolidate what they learn. One of the most insightful conversations we have had on where AI is heading. Ali was named as the best AI researcher in 2025 by Second Group: Second Prize Awards 2025, Celebrating the Best Iranian AI Scientists, Roboticist, CEOs & Startups Ali Behrouz : Ali BehrouzGitHubhttps://abehrouz.github.io Ardalan Javadi: https://www.linkedin.com/in/ardalanjam1369/ Farzam Hejazi: https://www.linkedin.com/in/farzam-hejazi-5b608081/ Subscribe to our Newsletter : https://substack.com/@seondnewsletter   00:00 Introduction  03:26 What is Intelligence?  05:51 Academic Journey 11:57 From Blockchain to Brain Networks 17:21 The Allure of Computational Social Science 21:02 The Genesis of TITAN 24:39 Human Memory Systems vs. AI Caching 32:36 The Disconnect: Solving Anterograde Amnesia in LLMs 41:40 Mechanics of TITAN 47:37 The Viral Aftermath: Dealing with Hype and Haters 52:09 Why Transformers Dominate & The Rebranding Epidemic 57:24 Scaling Laws and the Limitations of Pure Compression 64:05 Anthropic vs. OpenAI 66:06 Architectural Frontiers: Loop Transformers & Mixture of Depths 69:01 Moving Beyond TITAN 77:51 Nested Learning: Emulating Brain Frequencies 81:44 Memory Distillation and AI Sleep Cycles 83:24 Career Advice: Scientific Progress as "Old Ideas + New Noise"   References https://www.seltzer.com/margo/ https://en.wikipedia.org/wiki/Large-scale_brain_network https://www.geeksforgeeks.org/machine-learning/introduction-to-recurrent-neural-network/ https://en.wikipedia.org/wiki/Mamba_(deep_learning_architecture)   About Us :  Linkedin : https://www.linkedin.com/company/secondpodcast/ Twitter : /thesecondpod    Instagram : https://www.instagram.com/thesecondpod/ #Secondpod #Second_Pod #پادکست ـ دوم #secondpod #پادکست