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Oliver Wang

Principal Scientist at Google DeepMind focusing on image and multimodal models; discussed the architecture and capabilities behind Nano Banana (Gemini 2.5 Image).

Top 3 podcasts with Oliver Wang

Ranked by the Snipd community
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371 snips
Oct 28, 2025 • 54min

Google DeepMind Developers: How Nano Banana Was Made

Oliver Wang, Principal Scientist at Google DeepMind, and Nicole Brichtova, Group Product Manager, dive into the viral sensation, Nano Banana. They discuss the innovative merging of image and multimodal models, the surprising early reactions during testing, and how this technology can enhance both professional productivity and creative expression. The duo also explores the balance between user interfaces, character consistency, and the future impact of AI on artistic learning and collaboration, while addressing artist concerns and emerging applications.
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221 snips
Sep 17, 2025 • 41min

Ep 75: Nano Banana’s Oliver Wang and Nicole Brichtova - Behind the Breakthrough as Gemini Tops the Charts

Nicole Brichtova and Oliver Wang, innovative Google researchers, delve into the groundbreaking AI image model, Nano Banana. They discuss its superior character consistency and notable user engagement, revealing how it enhances creative workflows. The duo explores the convergence of image and video generation, the challenges of personalization, and the actual limitations of current AI expectations. They also highlight the need for intuitive design in user interfaces and share insights on future developments in AI for visual media.
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174 snips
Sep 23, 2025 • 1h 4min

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

Oliver Wang, a Principal Scientist at Google DeepMind, shares insights on the transformative capabilities of the Gemini 2.5 Flash Image, codenamed 'Nano Banana.' He explores the evolution from specialized image generators to integrated multimodal agents, highlighting how Nano Banana generates and edits images while preserving consistency. Oliver discusses the balance between aesthetics and accuracy, unexpected creative applications, and the future of AI models that could ‘think’ in images. He also warns about the risks associated with training on synthetic data.

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