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Last year, AI-made videos looked like nightmarish acid trips with little attachment to reality. Today, the highest-quality content is much closer to depicting the way our world actually looks and functions. The improvements in text-to-video AI applications have been fuelled by lots more data and computing processing power. Some developers, notably OpenAI and Runway AI, are determined to make the quality even better.
The spaghetti video is not a bad benchmark for progress. Compare Mr. Mina’s 2023 video with the one below, made in late June with. One approach to video generation involves teaching a model to predict what the next frame in a sequence will look like. That same ability can help a robot arm understand how to grab and move objects, or help autonomous vehicles anticipate how cars and pedestrians will move a few seconds into the future.
Such datasets have not always been easy to come by, and they can be expensive and time-consuming to compile. Academic institutions and AI labs have nevertheless assembled large publicly available video datasets for research purposes,Google DeepMind released multiple versions of a dataset called Kinetics that consists of links to hundreds of thousands of YouTube videos of humans performing various tasks.
Even though Mr. Bain took down WebVid, other versions still exist. “Loads of people cloned it,” he said.Generative AI companies, meanwhile, typically no longer disclose how and where they obtain data to train their models, as both competition and legal uncertainty have mounted.
Aud-Headline Video Dataset Model Data Company Runway Models Videos Getty Images Tsinghua University Mcgill University
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