Genie: Generative Interactive Environments with Ashley Edwards - #696

Genie: Generative Interactive Environments with Ashley Edwards - #696

Today, we're joined by Ashley Edwards, a member of technical staff at Runway, to discuss Genie: Generative Interactive Environments, a system for creating ‘playable’ video environments for training deep reinforcement learning (RL) agents at scale in a completely unsupervised manner. We explore the motivations behind Genie, the challenges of data acquisition for RL, and Genie’s capability to learn world models from videos without explicit action data, enabling seamless interaction and frame prediction. Ashley walks us through Genie’s core components—the latent action model, video tokenizer, and dynamics model—and explains how these elements collaborate to predict future frames in video sequences. We discuss the model architecture, training strategies, benchmarks used, as well as the application of spatiotemporal transformers and the MaskGIT techniques used for efficient token prediction and representation. Finally, we touched on Genie’s practical implications, its comparison to other video generation models like “Sora,” and potential future directions in video generation and diffusion models. The complete show notes for this episode can be found at https://twimlai.com/go/696.

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Building the Internet of Agents with Vijoy Pandey - #737

Building the Internet of Agents with Vijoy Pandey - #737

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 colla...

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

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

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 i...

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

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

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 platf...

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

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

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 fro...

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Google I/O 2025 Special Edition - #733

Google I/O 2025 Special Edition - #733

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...

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

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

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-...

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

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

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. Mah...

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How OpenAI Builds AI Agents That Think and Act with Josh Tobin - #730

How OpenAI Builds AI Agents That Think and Act with Josh Tobin - #730

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 comprehensi...

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