Sep 25, 2026

Runway’s Bet Beyond Video: World Models, Robotics, and the Neural OS — Anastasis Germanidis

Anastasis Germanidis, co-founder of Runway, discusses the company's journey from early generative creative tools to frontier video models, emphasizing their pivot towards general-purpose world simulation. He details the evolution of Gen-1, Gen-2, and Gen-3 (scaling 10x after Sora's release), highlighting the importance of controllability and the inevitability of real-time generation. The conversation delves into cutting-edge applications like Interface World Models (a fully neural operating system) and World Models for Robotics, where third-person video data and robust simulation are key to training intelligent agents.

Sep 17, 2026

How Real-Time AI Video Is Changing How Creators Work

fal's H3 Max significantly accelerates generative video, achieving real-time capabilities and substantial cost reductions through advanced model post-training and system optimizations. The discussion covers its technical "secret sauce," the emergence of continuous, controllable video experiences like H3 Max Director, and fal's strategic shift to focus on granular controllability and quality for professional Hollywood workflows, including precise camera, lighting, and motion controls.

Aug 30, 2026

SOTA Generative Media Panel — Dumitru Erhan, Shane Gu & Nicole Brichtova, Google DeepMind

This detailed discussion with Google AI researchers highlights the latest generative video models (NanoBanana 2 Lite, Gemini Omni Flash APIs) and their applications, including video editing, education, and localization. The conversation critically examines whether language is an adequate intermediate representation for AI, especially for sensory experiences like audio and taste, where human vocabulary is limited. It exposes the unreliability of human preferences in evaluating AI-generated content, citing the "Instagram filter effect" and "wedding ring" reward hacking as examples. The researchers emphasize the importance of high-quality, real-world data and the critical role of forward-deployed engineers in bridging the gap between cutting-edge research and practical applications.

Jun 16, 2026

You Might Not Need 50 Diffusion Steps — Ziv Ilan, Nvidia

Ziv Ilan from NVIDIA details how latency in video diffusion models can be drastically reduced to achieve real-time generation. He presents a layered approach combining dynamic quantization for memory and speed, chunk-based caching to skip redundant denoising computations, and, most critically, step distillation—training models to achieve high-quality output in significantly fewer steps. These techniques, packaged in the open-source FastGen repository, offer additive performance gains, enabling real-time video on a single Blackwell B200 GPU.

Apr 23, 2026

Why Most Robot Demos Are Fake

Changan Chen, co-founder of Rhoda AI, discusses their vision-first approach to building foundation models for robotics. The conversation covers their unique training pipeline, the distinction between policy and world models, and the path to deploying data-efficient, reliable robots in real-world industrial settings.

Apr 21, 2026

Building Generative Image & Video models at Scale - Sander Dieleman (Veo and Nano Banana)

Sander Dieleman from Google DeepMind provides a behind-the-scenes look at the key components of training large-scale diffusion models for audio-visual data. The talk covers the entire pipeline, from the critical role of data curation and latent representations to the mechanics of diffusion, network architectures, sampling with guidance, and advanced control signals.