Best Grokking Podcasts (2026)

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Intelligent Robots in 2026: Are We There Yet? with Nikita Rudin - #760 1:06:37

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1d ago1:06:37

1:06:37

Today, we're joined by Nikita Rudin, co-founder and CEO of Flexion Robotics to discuss the gap between current robotic capabilities and what’s required to deploy fully autonomous robots in the real world. Nikita explains how reinforcement learning and simulation have driven rapid progress in robot locomotion—and why locomotion is still far from “so…

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Zombi Bitches "Time to Quench Their Thirst." The Si-Monsta is Back 2:38:24

9d ago2:38:24

2:38:24

Today we check in with my good buddy Si. We ended up having a great conversation about robots, politics, religion, accountability, managing our anger, honing our instincts, and the idea that there is a natural order to the world, and much more. If you'd like to support my family and I create more content visit us at Patreon. patreon.com/dogbo Suppo…

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Rethinking Pre-Training for Agentic AI with Aakanksha Chowdhery - #759 52:54

23d ago52:54

52:54

Today, we're joined by Aakanksha Chowdhery, member of technical staff at Reflection, to explore the fundamental shifts required to build true agentic AI. While the industry has largely focused on post-training techniques to improve reasoning, Aakanksha draws on her experience leading pre-training efforts for Google’s PaLM and early Gemini models to…

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Why Vision Language Models Ignore What They See with Munawar Hayat - #758 57:40

1M ago57:40

57:40

In this episode, we’re joined by Munawar Hayat, researcher at Qualcomm AI Research, to discuss a series of papers presented at NeurIPS 2025 focusing on multimodal and generative AI. We dive into the persistent challenge of object hallucination in Vision-Language Models (VLMs), why models often discard visual information in favor of pre-trained lang…

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Scaling Agentic Inference Across Heterogeneous Compute with Zain Asgar - #757 48:44

1M ago48:44

48:44

In this episode, Zain Asgar, co-founder and CEO of Gimlet Labs, joins us to discuss the heterogeneous AI inference across diverse hardware. Zain argues that the current industry standard of running all AI workloads on high-end GPUs is unsustainable for agents, which consume significantly more tokens than traditional LLM applications. We explore Gim…

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Proactive Agents for the Web with Devi Parikh - #756 56:04

2M ago56:04

56:04

Today, we're joined by Devi Parikh, co-founder and co-CEO of Yutori, to discuss browser use models and a future where we interact with the web through proactive, autonomous agents. We explore the technical challenges of creating reliable web agents, the advantages of visually-grounded models that operate on screenshots rather than the browser’s mor…

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AI Orchestration for Smart Cities and the Enterprise with Robin Braun and Luke Norris - #755 54:46

2M ago54:46

54:46

Today, we're joined by Robin Braun, VP of AI business development for hybrid cloud at HPE, and Luke Norris, co-founder and CEO of Kamiwaza, to discuss how AI systems can be used to automate complex workflows and unlock value from legacy enterprise data. Robin and Luke detail high-impact use cases from HPE and Kamiwaza’s collaboration on an “Agentic…

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Building an AI Mathematician with Carina Hong - #754 55:52

2M ago55:52

55:52

In this episode, Carina Hong, founder and CEO of Axiom, joins us to discuss her work building an "AI Mathematician." Carina explains why this is a pivotal moment for AI in mathematics, citing a convergence of three key areas: the advanced reasoning capabilities of modern LLMs, the rise of formal proof languages like Lean, and breakthroughs in code …

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High-Efficiency Diffusion Models for On-Device Image Generation and Editing with Hung Bui - #753 52:23

2M ago52:23

52:23

In this episode, Hung Bui, Technology Vice President at Qualcomm, joins us to explore the latest high-efficiency techniques for running generative AI, particularly diffusion models, on-device. We dive deep into the technical challenges of deploying these models, which are powerful but computationally expensive due to their iterative sampling proces…

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Vibe Coding's Uncanny Valley with Alexandre Pesant - #752 1:12:36

3M ago1:12:36

1:12:36

Today, we're joined by Alexandre Pesant, AI lead at Lovable, who joins us to discuss the evolution and practice of vibe coding. Alex shares his take on how AI is enabling a shift in software development from typing characters to expressing intent, creating a new layer of abstraction similar to how high-level code compiles to machine code. We explor…

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Jared Leon with Instigate Clothing 2:15:01

3M ago2:15:01

2:15:01

Today my buddy (and birthday twin) Jared stops by to talk shop. Jared started his own clothing line in high school selling clothes to his peers, now 23 he keeps pressing on. He dropped by today with a fresh logo design that in my opinion rips. Stick around to hear about the creative process of design and the message behind the Instigate name. We al…

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Dataflow Computing for AI Inference with Kunle Olukotun - #751 57:37

3M ago57:37

57:37

In this episode, we're joined by Kunle Olukotun, professor of electrical engineering and computer science at Stanford University and co-founder and chief technologist at Sambanova Systems, to discuss reconfigurable dataflow architectures for AI inference. Kunle explains the core idea of building computers that are dynamically configured to match th…

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Recurrence and Attention for Long-Context Transformers with Jacob Buckman - #750 57:23

3M ago57:23

57:23

Today, we're joined by Jacob Buckman, co-founder and CEO of Manifest AI to discuss achieving long context in transformers. We discuss the bottlenecks of scaling context length and recent techniques to overcome them, including windowed attention, grouped query attention, and latent space attention. We explore the idea of weight-state balance and the…

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The Decentralized Future of Private AI with Illia Polosukhin - #749 1:05:03

3M ago1:05:03

1:05:03

In this episode, Illia Polosukhin, a co-author of the seminal "Attention Is All You Need" paper and co-founder of Near AI, joins us to discuss his vision for building private, decentralized, and user-owned AI. Illia shares his unique journey from developing the Transformer architecture at Google to building the NEAR Protocol blockchain to solve glo…

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Inside Nano Banana 🍌 and the Future of Vision-Language Models with Oliver Wang - #748 1:03:39

4M ago1:03:39

1:03:39

Today, we’re joined by Oliver Wang, principal scientist at Google DeepMind and tech lead for Gemini 2.5 Flash Image—better known by its code name, “Nano Banana.” We dive into the development and capabilities of this newly released frontier vision-language model, beginning with the broader shift from specialized image generators to general-purpose m…

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Is It Time to Rethink LLM Pre-Training? with Aditi Raghunathan - #747 58:26

4M ago58:26

58:26

Today, we're joined by Aditi Raghunathan, assistant professor at Carnegie Mellon University, to discuss the limitations of LLMs and how we can build more adaptable and creative models. We dig into her ICML 2025 Outstanding Paper Award winner, “Roll the dice & look before you leap: Going beyond the creative limits of next-token prediction,” which ex…

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Building an Immune System for AI Generated Software with Animesh Koratana - #746 1:05:11

4M ago1:05:11

1:05:11

Today, we're joined by Animesh Koratana, founder and CEO of PlayerZero to discuss his team’s approach to making agentic and AI-assisted coding tools production-ready at scale. Animesh explains how rapid advances in AI-assisted coding have created an “asymmetry” where the speed of code output outpaces the maturity of processes for maintenance and su…

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Cyclopes Pops and Cultural Ops 1:27:06

4M ago1:27:06

1:27:06

Today Dad, fresh out of eye surgery, joins me along with Matthew (my older brother) who is in town for the holidays. We talked about our personal lives, the current cultural affairs, the future of AI and Chat GPT and what it could mean for the arts moving forward, and the darker parts of technology. Podcast Notes: We recorded this back in December …

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Autoformalization and Verifiable Superintelligence with Christian Szegedy - #745 1:11:48

4M ago1:11:48

1:11:48

In this episode, Christian Szegedy, Chief Scientist at Morph Labs, joins us to discuss how the application of formal mathematics and reasoning enables the creation of more robust and safer AI systems. A pioneer behind concepts like the Inception architecture and adversarial examples, Christian now focuses on autoformalization—the AI-driven process …

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The Pat-riarchy is Back 59:56

4M ago59:56

59:56

It's my old man's 70th birthday! Today we goofed around and chopped it up about our personal lives such as Dad being a pastor, what it was like growing up playing basketball with Dad as my coach, I reflect on my time in LA, some words of wisdom from father per usual, and much more.. If you'd like to support my family and I create more content visit…

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Multimodal AI Models on Apple Silicon with MLX with Prince Canuma - #744 1:10:20

5M ago1:10:20

1:10:20

Today, we're joined by Prince Canuma, an ML engineer and open-source developer focused on optimizing AI inference on Apple Silicon devices. Prince shares his journey to becoming one of the most prolific contributors to Apple’s MLX ecosystem, having published over 1,000 models and libraries that make open, multimodal AI accessible and performant on …

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Genie 3: A New Frontier for World Models with Jack Parker-Holder and Shlomi Fruchter - #743 1:01:01

5M ago1:01:01

1:01:01

Today, we're joined by Jack Parker-Holder and Shlomi Fruchter, researchers at Google DeepMind, to discuss the recent release of Genie 3, a model capable of generating “playable” virtual worlds. We dig into the evolution of the Genie project and review the current model’s scaled-up capabilities, including creating real-time, interactive, and high-re…

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Closing the Loop Between AI Training and Inference with Lin Qiao - #742 1:01:11

5M ago1:01:11

1:01:11

In this episode, we're joined by Lin Qiao, CEO and co-founder of Fireworks AI. Drawing on key lessons from her time building PyTorch, Lin shares her perspective on the modern generative AI development lifecycle. She explains why aligning training and inference systems is essential for creating a seamless, fast-moving production pipeline, preventing…

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Context Engineering for Productive AI Agents with Filip Kozera - #741 46:01

5M ago46:01

46:01

In this episode, Filip Kozera, founder and CEO of Wordware, explains his approach to building agentic workflows where natural language serves as the new programming interface. Filip breaks down the architecture of these "background agents," explaining how they use a reflection loop and tool-calling to execute complex tasks. He discusses the current…

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Infrastructure Scaling and Compound AI Systems with Jared Quincy Davis - #740 1:13:02

6M ago1:13:02

1:13:02

In this episode, Jared Quincy Davis, founder and CEO at Foundry, introduces the concept of "compound AI systems," which allows users to create powerful, efficient applications by composing multiple, often diverse, AI models and services. We discuss how these "networks of networks" can push the Pareto frontier, delivering results that are simultaneo…

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Building Voice AI Agents That Don’t Suck with Kwindla Kramer - #739 1:13:02

6M ago1:13:02

1:13:02

In this episode, Kwindla Kramer, co-founder and CEO of Daily and creator of the open source Pipecat framework, joins us to discuss the architecture and challenges of building real-time, production-ready conversational voice AI. Kwin breaks down the full stack for voice agents—from the models and APIs to the critical orchestration layer that manages…

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Distilling Transformers and Diffusion Models for Robust Edge Use Cases with Fatih Porikli - #738 1:00:29

6M ago1:00:29

1:00:29

Today, we're joined by Fatih Porikli, senior director of technology at Qualcomm AI Research for an in-depth look at several of Qualcomm's accepted papers and demos featured at this year’s CVPR conference. We start with “DiMA: Distilling Multi-modal Large Language Models for Autonomous Driving,” an end-to-end autonomous driving system that incorpora…

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Building the Internet of Agents with Vijoy Pandey - #737 56:13

7M ago56:13

56:13

Today, we're joined by Vijoy Pandey, SVP and general manager at Outshift by Cisco to discuss a foundational challenge for the enterprise: how do we make specialized agents from different vendors collaborate effectively? As companies like Salesforce, Workday, and Microsoft all develop their own agentic systems, integrating them creates a complex, pr…

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LLMs for Equities Feature Forecasting at Two Sigma with Ben Wellington - #736 59:31

7M ago59:31

59:31

Today, we're joined by Ben Wellington, deputy head of feature forecasting at Two Sigma. We dig into the team’s end-to-end approach to leveraging AI in equities feature forecasting, covering how they identify and create features, collect and quantify historical data, and build predictive models to forecast market behavior and asset prices for tradin…

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2-Champion (aka Uncle Zane) Sticks Around for Round Two 2:23:31

7M ago2:23:31

2:23:31

Big daddy "2-Champion" (aka Uncle Zane) sticks around after my birthday so we could shoot the shit and go round two podding. We ended up talking about the validity of "history", being famous for the wrong reasons, and what war is, why it goes on, and "how it effects the mind of the man fighting it" - Zane We also had a special surprise guest join u…

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Zero-Shot Auto-Labeling: The End of Annotation for Computer Vision with Jason Corso - #735 56:45

7M ago56:45

56:45

Today, we're joined by Jason Corso, co-founder of Voxel51 and professor at the University of Michigan, to explore automated labeling in computer vision. Jason introduces FiftyOne, an open-source platform for visualizing datasets, analyzing models, and improving data quality. We focus on Voxel51’s recent research report, “Zero-shot auto-labeling riv…

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The Boys Get Together for My 40th Birthday 1:43:03

7M ago1:43:03

1:43:03

Today my brother Matthew and my two closet friends, Marc and Zane, came over for my 40th birthday. We ended up talking about our government, geopolitics, demons, and the truth about good and evil. If you'd like to support my family and I create more content visit us at Patreon. patreon.com/dogbo Support the show…

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Grokking, Generalization Collapse, and the Dynamics of Training Deep Neural Networks with Charles Martin - #734 1:25:21

7M ago1:25:21

1:25:21

Today, we're joined by Charles Martin, founder of Calculation Consulting, to discuss Weight Watcher, an open-source tool for analyzing and improving Deep Neural Networks (DNNs) based on principles from theoretical physics. We explore the foundations of the Heavy-Tailed Self-Regularization (HTSR) theory that underpins it, which combines random matri…

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Google I/O 2025 Special Edition - #733 26:21

8M ago26:21

26:21

Today, I’m excited to share a special crossover edition of the podcast recorded live from Google I/O 2025! In this episode, I join Shawn Wang aka Swyx from the Latent Space Podcast, to interview Logan Kilpatrick and Shrestha Basu Mallick, PMs at Google DeepMind working on AI Studio and the Gemini API, along with Kwindla Kramer, CEO of Daily and cre…

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RAG Risks: Why Retrieval-Augmented LLMs are Not Safer with Sebastian Gehrmann - #732 57:09

8M ago57:09

57:09

Today, we're joined by Sebastian Gehrmann, head of responsible AI in the Office of the CTO at Bloomberg, to discuss AI safety in retrieval-augmented generation (RAG) systems and generative AI in high-stakes domains like financial services. We explore how RAG, contrary to some expectations, can inadvertently degrade model safety. We cover examples o…

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From Prompts to Policies: How RL Builds Better AI Agents with Mahesh Sathiamoorthy - #731 1:01:25

8M ago1:01:25

1:01:25

Today, we're joined by Mahesh Sathiamoorthy, co-founder and CEO of Bespoke Labs, to discuss how reinforcement learning (RL) is reshaping the way we build custom agents on top of foundation models. Mahesh highlights the crucial role of data curation, evaluation, and error analysis in model performance, and explains why RL offers a more robust altern…

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Si and Two Guys (and a cup) 1:54:57

8M ago1:54:57

1:54:57

Today I have my buddies Si and Slug onto to shoot the shit and talk about whatever. We ended up talking about vintage clothing and running a small business, bipartisanship and the Trump and Kamala election results, Slug's alien encounter while hiking, and what we think about aliens and demons, and more. If you'd like to support my family and I crea…

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How OpenAI Builds AI Agents That Think and Act with Josh Tobin - #730 1:07:27

8M ago1:07:27

1:07:27

Today, we're joined by Josh Tobin, member of technical staff at OpenAI, to discuss the company’s approach to building AI agents. We cover OpenAI's three agentic offerings—Deep Research for comprehensive web research, Operator for website navigation, and Codex CLI for local code execution. We explore OpenAI’s shift from simple LLM workflows to reaso…

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CTIBench: Evaluating LLMs in Cyber Threat Intelligence with Nidhi Rastogi - #729 56:18

8M ago56:18

56:18

Today, we're joined by Nidhi Rastogi, assistant professor at Rochester Institute of Technology to discuss Cyber Threat Intelligence (CTI), focusing on her recent project CTIBench—a benchmark for evaluating LLMs on real-world CTI tasks. Nidhi explains the evolution of AI in cybersecurity, from rule-based systems to LLMs that accelerate analysis by p…

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Generative Benchmarking with Kelly Hong - #728 54:17

9M ago54:17

54:17

In this episode, Kelly Hong, a researcher at Chroma, joins us to discuss "Generative Benchmarking," a novel approach to evaluating retrieval systems, like RAG applications, using synthetic data. Kelly explains how traditional benchmarks like MTEB fail to represent real-world query patterns and how embedding models that perform well on public benchm…

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Exploring the Biology of LLMs with Circuit Tracing with Emmanuel Ameisen - #727 1:34:06

9M ago1:34:06

1:34:06

In this episode, Emmanuel Ameisen, a research engineer at Anthropic, returns to discuss two recent papers: "Circuit Tracing: Revealing Language Model Computational Graphs" and "On the Biology of a Large Language Model." Emmanuel explains how his team developed mechanistic interpretability methods to understand the internal workings of Claude by rep…

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Treyton Wilhite (AKA Slug, Slug-A-Lug, or AtticSlug) World Traveler, Musician, Small Business Owner 1:36:17

9M ago1:36:17

1:36:17

Today I have on my buddy Slug to ask him about his travels around the world. Slug and I work together. I can say first hand he is one of he chillest, most hard working people I've ever meet. Slug runs his own business selling vintage and is a musician. Today we talk about his travels in Viet Nam on motorcycle, playing at a music festival in India, …

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Teaching LLMs to Self-Reflect with Reinforcement Learning with Maohao Shen - #726 51:45

9M ago51:45

51:45

Today, we're joined by Maohao Shen, PhD student at MIT to discuss his paper, “Satori: Reinforcement Learning with Chain-of-Action-Thought Enhances LLM Reasoning via Autoregressive Search.” We dig into how Satori leverages reinforcement learning to improve language model reasoning—enabling model self-reflection, self-correction, and exploration of a…

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Waymo's Foundation Model for Autonomous Driving with Drago Anguelov - #725 1:09:07

9M ago1:09:07

1:09:07

Today, we're joined by Drago Anguelov, head of AI foundations at Waymo, for a deep dive into the role of foundation models in autonomous driving. Drago shares how Waymo is leveraging large-scale machine learning, including vision-language models and generative AI techniques to improve perception, planning, and simulation for its self-driving vehicl…

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Dynamic Token Merging for Efficient Byte-level Language Models with Julie Kallini - #724 50:32

10M ago50:32

50:32

Today, we're joined by Julie Kallini, PhD student at Stanford University to discuss her recent papers, “MrT5: Dynamic Token Merging for Efficient Byte-level Language Models” and “Mission: Impossible Language Models.” For the MrT5 paper, we explore the importance and failings of tokenization in large language models—including inefficient compression…

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Scaling Up Test-Time Compute with Latent Reasoning with Jonas Geiping - #723 58:38

10M ago58:38

58:38

Today, we're joined by Jonas Geiping, research group leader at Ellis Institute and the Max Planck Institute for Intelligent Systems to discuss his recent paper, “Scaling up Test-Time Compute with Latent Reasoning: A Recurrent Depth Approach.” This paper proposes a novel language model architecture which uses recurrent depth to enable “thinking in l…

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Imagine while Reasoning in Space: Multimodal Visualization-of-Thought with Chengzu Li - #722 42:11

10M ago42:11

42:11

Today, we're joined by Chengzu Li, PhD student at the University of Cambridge to discuss his recent paper, “Imagine while Reasoning in Space: Multimodal Visualization-of-Thought.” We explore the motivations behind MVoT, its connection to prior work like TopViewRS, and its relation to cognitive science principles such as dual coding theory. We dig i…

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Inside s1: An o1-Style Reasoning Model That Cost Under $50 to Train with Niklas Muennighoff - #721 49:29

10M ago49:29

49:29

Today, we're joined by Niklas Muennighoff, a PhD student at Stanford University, to discuss his paper, “S1: Simple Test-Time Scaling.” We explore the motivations behind S1, as well as how it compares to OpenAI's O1 and DeepSeek's R1 models. We dig into the different approaches to test-time scaling, including parallel and sequential scaling, as well…

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Sammy Comes Back for Another Session 1:27:06

10M ago1:27:06

1:27:06

Today Sam (my wife) comes on to talk about our life and plans for the future. We always enjoy using these sessions to check in with each other and go over how things going in our lives, especially because with our two little ones these podcasts seem like the one of the only time we have to get into it with out any distractions. Behold our couples t…

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Accelerating AI Training and Inference with AWS Trainium2 with Ron Diamant - #720 1:07:05

11M ago1:07:05

1:07:05

Today, we're joined by Ron Diamant, chief architect for Trainium at Amazon Web Services, to discuss hardware acceleration for generative AI and the design and role of the recently released Trainium2 chip. We explore the architectural differences between Trainium and GPUs, highlighting its systolic array-based compute design, and how it balances per…