Video as a Universal Interface for AI Reasoning with Sherry Yang - #676
Analysis
This article summarizes an interview with Sherry Yang, a senior research scientist at Google DeepMind, discussing her research on using video as a universal interface for AI reasoning. The core idea is to leverage generative video models in a similar way to how language models are used, treating video as a unified representation of information. Yang's work explores how video generation models can be used for real-world tasks like planning, acting as agents, and simulating environments. The article highlights UniSim, an interactive demo of her work, showcasing her vision for interacting with AI-generated environments. The analogy to language models is a key takeaway.
Key Takeaways
- •Generative video models can be used for real-world decision-making, similar to language models.
- •Video is presented as a unified representation of information, analogous to natural language.
- •The research explores using video generation models for planning, acting as agents, and environment simulation.
“Sherry draws the analogy between natural language as a unified representation of information and text prediction as a common task interface and demonstrates how video as a medium and generative video as a task exhibit similar properties.”