Generative design is an AI-driven design exploration process where engineers input design goals, parameters like performance requirements, materials, manufacturing methods, and cost constraints into software. The software then explores all possible permutations and generates optimized design alternatives that meet the specified criteria.[1][2] It tests and learns from each iteration to arrive at high-performing solutions, eliminating the need for an initial human-designed model.[3][4]

The key aspects of generative design are:

## Automated Design Exploration
The software automatically generates hundreds or thousands of design options optimized for the given goals and constraints, rapidly exploring solutions that human designers may never conceive.[1][4]

## AI and Machine Learning
Generative design leverages artificial intelligence and machine learning algorithms to iteratively improve designs, learning from each iteration what works and what doesn't.[1][3]

## Cloud Computing
It draws on cloud computing data to inform and refine the generated designs.[3]

## Biomimicry
Generative design can mimic how nature designs efficient systems and structures through the concept of biomimicry.[3]

The key benefits include simultaneous design exploration, accelerated timelines, material and cost savings, automation, agility, and reduced reliance on expert knowledge.[4][5] It enables engineers to focus on high-level problem-solving while AI handles the design details.[4]

Sources
[1] Generative Design - NexGenSolutions https://nexgensolutions.com/solutions/generative-design/
[2] Generative Design - KETIV https://ketiv.com/solutions/generative-design/
[3] What is Generative Design? Ultimate Guide | TechTarget https://www.techtarget.com/whatis/definition/generative-design
[4] Generative Design 101 - Formlabs https://formlabs.com/blog/generative-design/
[5] 10 ways you can use generative design to improve your business https://blog.hexagonmi.com/10-ways-you-can-use-generative-design-to-improve-your-business/