Generative AI and Machine Learning for Film, TV, and Gaming
Vinith Misra is a machine learning scientist and software engineer at Roblox, an online platform for gaming, co-experience, and game creation that brings people together through play. Previously, he led the Artwork and Video Data Science team at Netflix, where they used multimodal (video/text/audio) machine learning to assist creators, and analytics to inform creative decisions. He has also worked as Research Staff at IBM Watson, after graduating from Stanford (PhD) and MIT (M. Eng). In a parallel world, he worked as a technical consultant for HBO on their show Silicon Valley, including “developing” the fictitious middle-out compression algorithm!
In this fireside chat, Vinith joins Hugo Bowne-Anderson, Outerbounds’ Head of Developer Relations, to talk about the intersection of AI, machine learning data, algorithms, human creativity, content, and strategy in the entertainment industry. They’ll discuss
industrial applications of machine learning, computer vision, and AI to creative workflows and what happens when machine learning engineers work with content creators, such as directors, editors, 3d artists, and game developers;
Multimodal GenAI systems, where they came from and where they’re going, with a view towards both linear content creation and experiential systems, such as gaming;
Under-reported technical challenges in the GenAI space, such as developing robust evaluation systems;
Moving from ML and GenAI POCs to production and what is actually working in industry.
And much more!