TPUs

Building Generative Image & Video models at Scale - Sander Dieleman, Google DeepMind

Apr 21, 2026 · 40:46

Sander Dieleman, a research scientist at Google DeepMind, explains the behind-the-scenes process of building generative image and video models at scale, focusing on diffusion models. He emphasizes that data curation is often underrated and more impactful than model tweaking. Dieleman details how latent diffusion models use learned autoencoders to compress pixels into smaller representations, enabling training on high-resolution video. He describes diffusion as 'spectral autoregression' that generates images coarse-to-fine, and notes that guidance—amplifying the difference between conditional and unconditional predictions—massively improves sample quality at the cost of diversity. On sampling, he contrasts deterministic and stochastic approaches, and covers distillation techniques like consistency models that reduce steps. Dieleman also discusses control signals beyond text, such as camera motion in video generation, and the importance of post-training for conditioning.

A year of Gemini progress + what comes next — Logan Kilpatrick, Google DeepMind

Jul 10, 2025 · 11:58

Logan Kilpatrick, head of product for Google AI Studio at DeepMind, announces the final update to Gemini 2.5 Pro, which achieves state-of-the-art results on Aider and HLE benchmarks. He details Google's 50x increase in AI inference over the past year, driven by merging research and product teams into DeepMind. The episode outlines Gemini's evolution toward a universal assistant that unifies Google products, with upcoming features including proactivity, native audio and video capabilities (Veo), and smaller models. Kilpatrick also previews developer-focused updates: a SOTA embeddings model, a deep research API, and Veo 3 and Imagine 4 in the API, alongside repositioning AI Studio as a dedicated developer platform.