From agents to world models: What San Francisco revealed about AI’s next phase

2026-06-18 · Source: Dataconomy · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Robotics & Autonomous Systems · Depth: Intermediate, medium

Summary

AI's next phase will not be defined by better answers alone. Instead, it will be characterized by systems that can act with context, perceive with depth, and model the world they are asked to change, moving beyond the chatbot interface. Discussions at HumanX in San Francisco highlighted this shift, with Jensen Huang describing a "third wave" of AI where systems move from answering questions to "doing things" and using other software. Srinivas Narayanan noted that coding is evolving from assistance to managing agents, a pattern expected to extend to other knowledge work. Fei-Fei Li emphasized the critical need for spatial intelligence and "world models" that understand geometry, physics, and dynamics to create 3D/4D environments for learning and simulation, exemplified by World Labs' Marble. This transition signifies AI moving closer to real-world work and environments, requiring action, tool use, and contextual understanding beyond just language processing.

Key takeaway

For AI Engineers and Directors of AI/ML designing next-generation systems, recognize that AI's frontier is shifting from language processing to action and world understanding. Prioritize developing agentic capabilities, integrating tool use, and building spatial intelligence into your solutions. This requires focusing on robust infrastructure, governance, and intuitive interfaces to manage agents effectively, moving beyond simple chatbot interactions.

Key insights

AI is transitioning from linguistic models to agentic systems that act, use tools, and comprehend physical and virtual environments.

Principles

• AI is software that uses software.
• Intelligence evolves with world awareness.
• Coding is a preview for agentic knowledge work.

In practice

• Create training environments for robots.
• Design experiences and support healthcare imaging.
• Power virtual worlds and model physical states.

Topics

• AI Agents
• World Models
• Spatial Intelligence
• Agentic AI
• Software Automation
• HumanX Conference

Best for: Research Scientist, Investor, CTO, AI Scientist, AI Engineer, Director of AI/ML

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Editorial summary, takeaway, and curation by AIssential. Original article published by Dataconomy.