Gen AI tools and their underlying models offer capabilities that take steps toward synthetic production methods
Unthinkable as it might seem, it’s a future that could begin to emerge with generative artificial intelligence. Gen AI tools and their underlying models are beginning to offer capabilities that take steps toward the possibility of synthetic production that would allow for replacing certain physical production methods.
To create a NeRF, a neural network is trained on a simple recorded video from any camera or just a partial set of 2D images, meaning they don’t need to show all perspectives, sides or angles of the object or scene. The network is then able to generate a high-fidelity 3D representation of an object or scene by inferring unseen viewpoints, even those not captured in training data provided to the model.
Typically, the imagery displayed in these volumes requires VFX artists to produce a realistic 3D model of the scene environment in. But now, NeRFs may be a dramatically easier, cheaper way to create these 3D scenes, as a small team of photographers can simply go to a scene location and capture video or images of the environment to render as a NeRF.
For example, Soul Machines trains large language model and speech systems on hundreds of hours of interviews to replicate how an individual would respond in conversation, including in what they say and how they say it. As a result, avatars can be rendered to speak any language available in a large language model.
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