World Models vs. Multimodal LLMs: Charting the Future of AI Agents
Analysis
Exciting advancements in AI agents are emerging! This discussion explores whether powerful multimodal LLMs, enhanced with tools, can achieve the same level of robustness as world models that learn the dynamics of the world. This debate sparks innovative thought around the future of AI.
Key Takeaways
- •The article discusses the potential of both multimodal LLMs and world models, such as JEPA/V-JEPA, for building robust AI agents.
- •A key question is whether multimodal LLMs, enhanced with post-training and tool use, can match the capabilities of world models in tasks requiring long-term planning and physical interaction.
- •The author seeks concrete benchmarks to compare the performance of these two approaches to AI agent development.
Reference / Citation
View Original"My question: what concrete criteria or benchmarks would allow us to choose between: (1) a multimodal LLM + post-training + tool-use will eventually cover the essentials vs (2) a non-generative world model architecture is needed to take a leap (prediction, constraints, physical interaction)"
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r/deeplearningJan 23, 2026 15:50
* Cited for critical analysis under Article 32.