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Can an AI understand the visual world without the need for humans to pre-label millions of images? Meta believes it can, and its new model, V-JEPA 2 (Video Joint Embedding Predictive Architecture), is its most advanced answer. This model represents a significant evolution in the field of self-supervised learning for computer vision, better mimicking the

For the last decade, the epicenter of artificial intelligence has been in Silicon Valley. Names like OpenAI, Google or Anthropic have set the pace for global innovation. However, in recent years, a new force has emerged quickly and determinedly: China. What once seemed like a secondary role has now transformed into head-on competition, with Chinese

Thanks to the advancement of artificial intelligence, computer vision is undergoing a silent but profound revolution: self-supervised learning. At the forefront of this movement is DINOv3, the latest Meta AI model that is redefining how machines learn to “see” the world without the need for human labels. Discover how DINOv3 achieves this feat and why

Imagine that you are writing an email in Gmail and you don’t know how to start, or that you are faced with an endless spreadsheet in Google Sheets. Now think about having an invisible assistant that solves those tasks in seconds. That assistant already exists and is called Gemini, Google’s artificial intelligence that lives inside