Science, Space and Technology News 2023
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“In recent years, AI-based generative models have yielded numerous eye-popping results, from photorealistic images to lucid streams of text. Remarkably, some of the most powerful generative models are grounded in time-tested concepts from physics, such as symmetries and thermodynamics. PFGM++ takes a century-old idea from fundamental physics — that there might be extra dimensions of space-time — and turns it into a powerful and robust tool to generate synthetic but realistic datasets.
Looking ahead, they aim to refine certain aspects of the model, particularly in systematic ways to identify the “sweet spot” value of D tailored for specific data, architectures, and tasks by analyzing the behavior of estimation errors of neural networks. They also plan to apply the PFGM++ to the modern large-scale text-to-image/text-to-video generation.“Diffusion models have become a critical driving force behind the revolution in generative AI,” says Yang Song, research scientist at OpenAI.
“They even outperform the popular diffusion models, which currently dominate the literature. This makes them a very powerful generative modeling tool, and I envision their application in diverse areas, ranging from digital content creation to generative drug discovery. More generally, I believe that the exploration of further physics-inspired generative modeling frameworks holds great promise for the future and that Poisson Flow Generative Models are only the beginning.
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