New Dimensions By Raymond Chan
The pace of artificial intelligence has entered a new era, propelled by revolutionary advancements by DeepMind’s AlphaFold 3 (a Google company), which has dramatically accelerated progress in the fundamental science of protein folding.
AlphaFold 3’s ability to accurately predict the 3D structure of proteins based on their amino acid sequences has sent shockwaves through the biological sciences. By solving a grand challenge that has puzzled researchers for decades, this breakthrough has catalyzed unprecedented gains in fields like drug discovery, materials science, and renewable energy — all by unlocking faster pathways to innovation.
Harnessing the power of generative AI represents a pivotal moment in the history of innovation. By empowering us to ideate, experiment, and bring new ideas to life faster than ever before, these technologies have the potential to propel us into an era of unprecedented advancement and transformation.
The Next Frontier: Physics-rule-based Intelligence
On top of science development, the advent of generative AI has also undoubtedly revolutionized creative industries, exemplified by the viral success of tools like Sora, which can generate movie scripts from simple prompts. These systems still face significant limitations. At their core, these models are fundamentally based on statistical patterns extracted from massive datasets — a
technique that, while powerful, fails to fully capture the underlying physical realities that govern our world.
The movies and visual content produced by current generative AI tend to rely on learned stylistic techniques and narrative structures, rather than a deeper understanding of the physical laws and
constraints that shape authentic human experiences. This “statistics-based intelligence” can generate compelling, but often unrealistic, outputs that lack the grounding in physics-based causality that audiences increasingly demand.
The next frontier in generative AI for industries like film, gaming, and robotics will be the development of “Physics Intelligence” — systems that can not only ideate and compose, but also simulate, and render content that adheres to the fundamental principles of the physical universe. By incorporating a deeper comprehension of dynamics, materials, and the physical parameters that govern our reality, these advanced AI models will be able to produce hyper-realistic, scientifically grounded content and experiences.
This shift towards physics-intelligence represents a significant business opportunity, as industries hungry for innovative, lifelike digital content and autonomous systems will eagerly adopt these transformative technologies. Overcoming the limitations of current generative AI approaches will be crucial for unlocking the full potential of these tools to accelerate innovation across a wide range of sectors.
Preserving the Human Touch
As the capabilities of Generative AI continue to advance, it’s crucial that the development of these technologies aligns with the long-term wellbeing and agency of the human race. Rather than seeking to replace human creators and decision-makers, the true promise of generative AI lies in its ability to augment and empower our innate creativity, and problem-solving abilities. The future should not be one where AI systems autonomously generate all of our games, movies, and innovations, but rather where these technologies serve as powerful design assistants and collaborators that enhance the human touch.
Designers, producers, and other creative professionals should be equipped with generative AI tools that allow them to ideate, prototype and refine their visions more efficiently, not to replace the human element. By developing AI systems that can seamlessly integrate with human control on workflows and decision-making processes, we can ensure that the products of our collective innovation remain grounded in the unique perspectives, emotions, and values that only humans can provide.
This delicate balance between human and machine intelligence is where the true transformative potential of generative AI lies. As we continue to push the boundaries of what these technologies can achieve, the focus must remain on cultivating AI as a tool for empowerment, rather than one of replacement. Only then can we harness the full power of generative AI to accelerate innovation in a way that preserves the essence of the human experience and safeguards our collective creative agency. This is the future we must strive to build.
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.
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.
*** This exclusive feature interview was originally published in July 2024 edition of Casino Life Magazine Issue 168 ***
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