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Secondpod
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Recent Episodes
July 7, 2026
Ramin Hassani I Co-Founder & CEO of Liquid AI
Ramin Hasani is the co-founder and CEO of Liquid AI, and he has done what almost no one in AI has: built a real alternative to the transformer, the architecture behind ChatGPT and nearly every model you touch. Liquid AI raised a $250M Series A led by AMD, and by his own account now sits around $4.5 billion. The core idea did not come from a bigger data center. It came from the 302-neuron brain of a 2mm worm. We also get into the part most founders never put on a slide. While the whole field was stripping complexity out of neural networks to make them scale, Ramin spent seven years adding it back in, chasing an equation about how two neurons talk that had sat unsolved since 1907. He cracked it on a chalkboard at MIT, one now headed to the MIT history museum. Ramin was born in Iran and left for Politecnico di Milano, then a PhD at TU Wien in Vienna, where modeling the brain of a worm became Liquid Neural Networks. From there: MIT, CSAIL, a 2022 Nature paper, and in March 2023 spinning the research into Liquid AI alongside Daniela Rus, Mathias Lechner, and Alexander Amini. Our News Letter : https://substack.com/@seondnewsletter Ramin Hassani Linkedin : https://www.linkedin.com/in/alikashani Ardalan Javadi : https://www.linkedin.com/in/ardalanjam1369/ Farzam Hejazi: https://www.linkedin.com/in/farzam-hejazi-5b608081/ 00:00:00 Introduction 00:03::24 Why Noise Is Actually a Resource for Computation 00:06:01 Where the Whole Worm Idea Came From 00:6:56 Why Ramin Chose the C. elegans Worm as the Basis of His Research 00:10:19 How Ramin Found His First Co Founder 00:18:08 The Equation Ramin and His Team Solved That Had Been Unsolved Since 1907 00:19:06 The First Mathematical Attempt in 1953 to Show Neuron Relationships 00:19:41 What Is the Problem With Differential Equation Based Machine Learning? 00:21:29 The Aha Moment Behind Liquid AI 00:22:16 The Birth of Liquid AI 00:22:46 How Sergey Levine Inspired the Name 00:24:09 How Liquid AI's Architecture Differs From Transformers 00:25:09 The Relationship Between Bias and Algorithm Scalability 00:28:05 Why Liquid Neural Networks Have an Efficiency Advantage at Scale 00:29:41 Do Scaling Laws Apply to Liquid Models? 00:31:26 Attention Is Not the Only Thing You Can Scale 00:34:08 How the Liquid Search System Works 00:34:53 Why Liquid AI Has the Lowest Memory Usage and Latency and Why It Is Hybrid 00:35:00 The Best Foundation Model for CPUs 00: 37:30 How to Close Enterprise Customers in the AI Era 00:38:29 What Vanguard Taught Ramin About Financial Strategy 00:41:58 125 Enterprises Are Now Using the Liquid AI Model 00:42:56 How to Design a Revenue Model for Enterprise in the AI Era00:43:19 How Shopify Uses Liquid AI 00:44:00 How Mercedes Uses Liquid AI With a 600 MB Model 00:45:51 The Quality of $1 of Liquid AI Revenue Compared to $1 of Anthropic 00:47:13 Why Liquid Is Going After Arm's Business Model 00:52:53 The Story Behind Another Iranian Founded AI DNA Startup That Raised $200M in Seed 00:55:47 The Story Behind Liquid AI's $290M Fundraise 00:59:30 How to Close a Seed Round 00:1:00:17 The Mastermind Behind the Fundraising 00:1:02:57 The Story Behind AMD Leading the Round 1:04:56 Why Revenue Matters So Much for Fundraising 1:05:22 Liquid AI Is Now at a $4.5 Billion Valuation 1:05:51 Ramin's Insight on Building a World Class Network 1:07:32 Ramin's Takeaways From Meeting Jamie Dimon 1:08:31 Jamie Dimon's Pitch for Liquid AI 1:08:51 How to Build an Effective Short Narrative for Your Pitch 1:10:31 Leading by Example 1:11:07 What Is the Best Definition of Intelligence? 1:14:32 Silicon Valley Is a Gossip Town 1:16:22 Why an Exponential View Matters and How Sam Altman Does It References: Check our News Letter : https://substack.com/@seondnewsletter?r=2v0lej&utm_campaign=profile&utm_medium=profile-page About Us : Linkedin : https://www.linkedin.com/company/secondpodcast/ Twitter : /thesecondpod Instagram : https://www.instagram.com/thesecond
June 28, 2026
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
June 4, 2026
Ali Kashani, Serve Robotics
Ali Kashani is the co-founder and CEO of Serve Robotics, and he has done what almost no one in Robotics has: put robots on real streets in dozens of cities and made people love them. He is the youngest Iranian-born CEO on the Nasdaq, the youngest CEO of any robotics company on the exchange, growing revenue around 600 percent year over year and scaling from 100 robots to thousands in a single year. We also get into the part most founders never put on a slide. Between spinning out of Uber and ringing the Nasdaq bell, Serve hit its last payroll ten times. Two of those times Ali made payroll out of his own mortgage. Ali was born in Iran and left at 17. He did his robotics PhD at the University of British Columbia on fusing LiDAR and cameras, started an energy hardware company that nearly died and then sold I co-hosted this one with a friend of the pod Brendan, Managing Director of AI and Partner at Human Agency. Our News Letter : https://substack.com/@seondnewsletter Ali Kashani Linkedin : https://www.linkedin.com/in/alikashani Ardalan Javadi : https://www.linkedin.com/in/ardalanjam1369/ 00:00:00 The youngest Iranian-born CEO on the Nasdaq 00:01:19 Why a public company beats a private one 00:02:47 The path to Serve: a robotics PhD and LiDAR 00:04:14 Fired, broke, and one step at a time 00:07:20 The dead company that came back 00:08:31 DARPA 2005 and the contrarian bet on LiDAR 00:12:45 Designing a robot people would forgive 00:16:04 Principle before perception 00:18:45 Building the ecosystem: NVIDIA, Magna, Uber 00:23:56 Dots versus lines, and "Exit Path" 00:26:24 Turning customer concentration into a feature 00:29:38 The real unit economics of a delivery 00:31:48 Picking cities and rolling out robots 00:33:17 The case for optimism on AI and jobs 00:37:49 Sidewalks versus streets 00:41:18 The IPO and the numbers ‘00:42:23 Ten last payrolls and the Kashani loan 00:46:10 Two days before Christmas: the call to Jensen 00:48:50 From bankruptcy lawyers to the bell in three months 00:49:11 The coming valley and the humanoid hype 00:50:50 Where the value is in physical AI 00:53:24 Why narrow robots beat humanoids, for now 00:55:00 Don't follow trends 00:57:44 Uncertainty is the job 01:00:59 Startups as entropy reduction engines 01:02:31 Touraj, Noosheen & Pejman 01:04:39 His hope for Iran References : https://investors.generac.com/news-releases/news-release-details/generac-announces-acquisition-neurio-technology-inc https://en.wikipedia.org/wiki/DARPA_Grand_Challenge https://bothsidesofthetable.com/invest-in-lines-not-dots-611f36491d73 https://www.therobotreport.com/four-ways-to-make-ai-products-that-people-will-love/ 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
37 total episodes available
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