By Raymond Chan
In the ever-evolving realm of artificial intelligence, the ability to seamlessly convert 2D images into dynamic 3D representations has unlocked a realm of new visual experiences and boundless creative possibilities. However, beneath the surface of this technological marvel lies a critical challenge – the lack of inherent “know-how” to determine the precise elements necessary for crafting a truly accurate 3D image.
Addressing this gap in AI proficiency opens up avenues for ground breaking advancements in industrial design processing. By augmenting existing AI frameworks with a new layer of intelligent guidance, we have the opportunity to revolutionize the way in which machines perceive and reconstruct the world around us.
Bridging the Skill Gaps in Design Industries
In the diverse landscape of design industries, each field presents its own unique set of challenges and requirements, demanding specialized skills and expertise. Consider the scenario of a shopping-mall architect making the transition to designing a casino: While both structures are buildings, they entail vastly different skill sets, from ambiance creation to spatial layout, catering to distinct user experiences.
Traditionally, such transitions necessitate human intervention to bridge the knowledge gap and adapt expertise to new contexts. However, the advent of AI offers a transformative solution, empowering machines to swiftly absorb and apply domain-specific insights. By infusing AI systems with a new layer of contextual understanding, we can facilitate the seamless transfer of skills and knowledge across diverse design disciplines.
This enhanced AI functionality acts as a bridge, enabling architects, designers, and creators to transcend the constraints of their traditional expertise. They can explore new realms of design with confidence and precision. Through this fusion of human creativity and AI intelligence, the boundaries between different design industries blur, fostering a collaborative ecosystem where innovation thrives and boundaries dissolve.
The Essential Layer: Simulation and the Real Physical World
To construct the foundational layer essential for enhancing AI capabilities in design industries, software engineers play a pivotal role in developing the intricate framework that merges simulation with physics engines. This integration is crucial for providing real-time feedback and ensuring a heightened sense of realism in terms of collisions, balance, and momentum within the AI-generated designs.
The marriage of simulation and physics engines within AI systems facilitates a dynamic environment where virtual creations behave authentically, mimicking the physical laws governing our world. This real-time simulation not only enhances the visual aesthetics of the designs but also ensures practical viability by adhering to fundamental principles of physics.
Software engineers work meticulously to intertwine data-driven modeling with physical simulation, creating a symbiotic relationship that empowers AI systems with high-level abstract control and the capacity for precise motion adjustments. Through this harmonious integration, AI designers can manipulate and refine designs with unparalleled accuracy, while maintaining the physical realism crucial for generating motions that resonate with real-world dynamics.
This innovative approach, if implemented correctly, not only streamlines the design process but also opens up a realm of possibilities for designers to explore and experiment with complex structures and interactions. It can be the new future for the industrial design business.
ABOUT RAYMOND CHAN
Raymond is a software engineer by profession with a track record in corporate innovation and entrepreneurship. He co-founded two prosperous startups, TGG Interactive and Global Gaming Group in Asia, where he served as director and CEO to lead the customer intelligence and electronic gaming businesses from 2007 to 2018. Earlier in his career, Raymond was a founding member of the business intelligence team at E*TRADE from Morgan Stanley and played a pivotal role in designing the TiVo customer intelligence system in Silicon Valley.
