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PODCAST

The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)

Sam Charrington

Machine learning and artificial intelligence are dramatically changing the way businesses operate and people live. The TWIML AI Podcast brings the top minds and ideas from the world of ML and AI to a broad and influential community of ML/AI researchers, data scientists, engineers and tech-savvy business and IT leaders. Hosted by Sam Charrington, a sought after industry analyst, speaker, commentator and thought leader. Technologies covered include machine learning, artificial intelligence, deep

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All Episodes

55:52

Building an AI Mathematician with Carina Hong - #754

The TWIML AI Podcast (formerly This Week in Machine... ·

2025/11/04

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 generation. We explore the core technical challenges, including the massive data gap between general-purpose code and formal math code, and the difficult

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52:23

High-Efficiency Diffusion Models for On-Device Image...

The TWIML AI Podcast (formerly This Week in Machine... ·

2025/10/28

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 process. Hung details his team's work on SwiftBrush and SwiftEdit, which enable high-quality text-to-image generation and editing in a single inference step. He

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72:36

Vibe Coding's Uncanny Valley with Alexandre Pesant -...

The TWIML AI Podcast (formerly This Week in Machine... ·

2025/10/22

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 explore the current capabilities and limitations of coding agents, the importance of context engineering, and the practices that separate successful vibe coders

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57:37

Dataflow Computing for AI Inference with Kunle...

The TWIML AI Podcast (formerly This Week in Machine... ·

2025/10/14

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 the dataflow graph of an AI model, moving beyond the traditional instruction-fetch paradigm of CPUs and GPUs. We explore how this architecture is

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57:23

Recurrence and Attention for Long-Context...

The TWIML AI Podcast (formerly This Week in Machine... ·

2025/10/07

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 weight-state FLOP ratio as a way of reasoning about the optimality of compute architectures, and we dig into the Power Retention architecture, which

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65:03

The Decentralized Future of Private AI with Illia...

The TWIML AI Podcast (formerly This Week in Machine... ·

2025/09/30

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 global payment challenges, and now applying those decentralized principles back to AI. We explore how Near AI is creating a decentralized cloud that

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63:39

Inside Nano Banana 🍌 and the Future of...

The TWIML AI Podcast (formerly This Week in Machine... ·

2025/09/23

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 multimodal agents that can use both visual and textual data for a variety of tasks. Oliver explains how Nano Banana can generate and iteratively edit

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58:26

Is It Time to Rethink LLM Pre-Training? with Aditi...

The TWIML AI Podcast (formerly This Week in Machine... ·

2025/09/16

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 examines why LLMs struggle with generating truly novel ideas. We dig into the "Roll the dice" approach, which encourages structured exploration by injecting

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65:11

Building an Immune System for AI Generated Software...

The TWIML AI Podcast (formerly This Week in Machine... ·

2025/09/09

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 support. We explore PlayerZero’s debugging and code verification platform, which uses code simulations to build a "memory bank" of past bugs and leverages

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71:48

Autoformalization and Verifiable Superintelligence...

The TWIML AI Podcast (formerly This Week in Machine... ·

2025/09/02

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 of translating mathematical concepts from their human-readable form into rigorously formal, machine-verifiable logic. We explore the critical distinction

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70:20

Multimodal AI Models on Apple Silicon with MLX with...

The TWIML AI Podcast (formerly This Week in Machine... ·

2025/08/26

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 Apple devices. We explore his workflow for adapting new models in MLX, the trade-offs between the GPU and Neural Engine, and how optimization methods like

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61:01

Genie 3: A New Frontier for World Models with Jack...

The TWIML AI Podcast (formerly This Week in Machine... ·

2025/08/19

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-resolution environments. Jack and Shlomi share their perspectives on what defines a world model, the model's architecture, and key technical challenges and

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61:11

Closing the Loop Between AI Training and Inference...

The TWIML AI Podcast (formerly This Week in Machine... ·

2025/08/12

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 the friction that often stalls deployment. We explore the strategic shift from treating models as commodities to viewing them as core product assets. Lin

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46:01

Context Engineering for Productive AI Agents with...

The TWIML AI Podcast (formerly This Week in Machine... ·

2025/07/29

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 limitations of agent protocols like MCPs and how developers can extend them to handle the required context and authority. The conversation challenges the

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73:02

Infrastructure Scaling and Compound AI Systems with...

The TWIML AI Podcast (formerly This Week in Machine... ·

2025/07/22

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 simultaneously faster, more accurate, and even cheaper than single-model approaches. Using examples like "laconic decoding," Jared explains the practical techniques

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73:02

Building Voice AI Agents That Don’t Suck with Kwindla...

The TWIML AI Podcast (formerly This Week in Machine... ·

2025/07/15

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 the complexities of multi-turn conversations. We explore why many production systems favor a modular, multi-model approach over the end-to-end models

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60:29

Distilling Transformers and Diffusion Models for...

The TWIML AI Podcast (formerly This Week in Machine... ·

2025/07/09

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 incorporates distilling large language models for structured scene understanding and safe planning motion in critical "long-tail" scenarios. We explore how DiMA

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56:13

Building the Internet of Agents with Vijoy Pandey - #737

The TWIML AI Podcast (formerly This Week in Machine... ·

2025/06/24

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, probabilistic, and noisy environment, a stark contrast to the deterministic APIs of the past. Vijoy introduces Cisco's vision for an "Internet of Agents," a

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59:31

LLMs for Equities Feature Forecasting at Two Sigma...

The TWIML AI Podcast (formerly This Week in Machine... ·

2025/06/17

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 trading and investment. We explore the firm's platform-centric approach to managing an extensive portfolio of features and models, the impact of multimodal LLMs

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56:45

Zero-Shot Auto-Labeling: The End of Annotation for...

The TWIML AI Podcast (formerly This Week in Machine... ·

2025/06/10

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 rivals human performance,” which demonstrates how zero-shot auto-labeling with foundation models can yield to significant cost and time savings compared to

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81 results

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