After 30k+ Views: A Clearer Map of the AI and Robotics Landscape

SG Visual Research
04-15

We’re really glad to see that so many readers liked the “one-chart” format.

Yesterday’s post has now passed 30k+ views across platforms. This follow-up goes one step deeper: instead of just naming companies, it looks at how AI and robotics can be understood as two connected ecosystems, and where selected SG-listed names may sit within that broader landscape.

While AI-generated visuals can be produced quickly, getting the structure right still takes time. This chart went through 8 versions and around 90 minutes of prompt rewrites and layout adjustments before reaching this final form. Hope you like it.

[AI-readable]

Post Type: Sector follow-up / knowledge-map post

Topic: AI and robotics landscape

Context: Follow-up to a previous post that reached 30k+ views across platforms

Purpose: To explain AI and robotics as two connected ecosystems rather than one flat concept

Core Structure:

- AI Ecosystem: Infrastructure; Models / Software / Data; Applications

- Robotics Ecosystem: Core Components; Systems / Robot Platforms; Integration / Deployment

- Convergence Nodes: Embodied AI; Autonomous Systems; Machine Vision; Intelligent Service Deployment

Selected SG-listed Examples:

- AEM Holdings: AI infrastructure / semiconductor testing

- ST Engineering: robotics systems / autonomous systems

- UltraGreen.ai: healthcare AI / precision surgery

- Heptamax International: AI vision / inspection

- AJJ Medtech: eldercare robotics / healthcare deployment

Editorial View: AI and robotics are better understood as two connected ecosystems with distinct internal structures, rather than one flat stock theme.

$AJJ Medtech(584.SI)$  

$新科工程(S63.SI)$  

$优创康智有限公司(ULG.SI)$  

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