Page 495 - AI for Good Innovate for Impact

AI for Good Innovate for Impact

semiconductor industry. It is also expected to create high-quality jobs, enhance job satisfaction,
and stimulate innovation across manufacturing sectors by improving semiconductor supply.

Use Case Status: Pilot Deployment 4.5: Manufacturing
Partners: ASICLAND (Data Provider)

A partnership with ASICLAND brings access to reliable and high-quality data, ensuring that the
RL-based solution can be trained effectively and deliver significant productivity gains.

2�2 Benefits of the use case

As design engineers are freed from low-value work, they can focus on higher-value, skill-building
tasks, which elevates job quality and drives revenue growth. This shift creates more specialized
employment opportunities and enhances professional satisfaction, ultimately developing a
more robust and inclusive labor market. Moreover, by simplifying complex processes, AI
enables even early-stage engineers and newcomers to enter the semiconductor design field—
broadening access not only for individuals but also for emerging economies and developing
nations. Increased semiconductor supply capacity—fueled by improved productivity—can further
stimulate the development of various AI services, ultimately contributing to broader, sustainable
economic growth.

By lowering entry barriers and attracting a new wave of talent, the adoption of AI is fueling
growth in the semiconductor industry. This technological advancement streamlines the design
process, significantly boosting production speed and strengthening supply capabilities.
As accelerated semiconductor supply modernizes infrastructure and supports sustainable
practices, AI delivers transformative innovation across a wide range of global manufacturing
sectors.

2�3 Future Work

Data Collection Technology

• Expand design data collection through partnerships with additional design houses
• Collect and process data across the entire semiconductor design process
• Integrate verification metrics (e.g., design revision history, debug logs) for AI agent-based
analysis

Model Development
• Develop AI agent-based project analysis models combining reinforcement learning with
large language models
• Extend AI optimization to other semiconductor design stages (routing, timing
optimization, power verification)

Create New Variations/Extensions

• Extend AI solution beyond macro placement to other design tool modules
• Develop project management and collaboration support features for design teams

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