Among the highlights is “Meta Video Seal”, an open-source tool designed for video watermarking, which builds upon last year’s widely-used “Meta Audio Seal” for sound watermarking. This technology helps identify the source of digital content, ensuring its authenticity – sounds pretty practical to me.
What’s more interesting, though, is Meta’s foundational model that could make mobile gaming pretty exciting.
The standout release is called “Meta Motivo”, a foundation model for controlling virtual embodied agents, such as humanoid figures in simulations or games. Unlike conventional AI methods that rely on highly curated data or are tailored for specific tasks, Meta Motivo uses a groundbreaking approach called unsupervised reinforcement learning. This technique allows the AI to learn a wide range of tasks – such as imitating human motion, achieving specific poses, or optimizing reward-based actions – without requiring additional training.
What sets Meta Motivo apart is its ability to interpret movements, rewards, and states using a shared framework, enabling the agent to behave more like a human. For instance, the model can adjust to unexpected changes like altered gravity or environmental disturbances, showcasing robust adaptability even in scenarios it wasn’t specifically trained for.While these tools are primarily designed for researchers and developers, Meta Motivo has the potential to benefit smartphone users and everyday technology consumers. AI agents with human-like behavior could lead to more realistic non-player characters (NPCs) in mobile games.Enhanced AI memory and social intelligence may result in virtual assistants and chatbots that are smarter, more responsive, and better suited to individual needs. I truly hope so. Because right now, they are not that smart.