Approaching the Point of Breakthrough for Embodied Artificial Intelligence, Akin to ChatGPT?
In the world of artificial intelligence (AI), a significant shift is underway. Embodied AI, a cutting-edge technology, is revolutionising the field of robotics, bringing us closer to a future where humanoid robots can adapt and improve their behaviour over time, much like humans do.
Embodied AI allows these robots to perform tasks in a more human-like and intuitive manner. By integrating robotics with machine learning, these systems can perceive, act, and collaborate with their surroundings. This technology leverages advanced technologies such as sensors, motors, machine learning, and natural language processing.
The timeline of AI development traces back to the 1950s and 60s, where rule-based systems focused on abstract reasoning. Fast forward to the 1980s, and the articulation of Moravec's Paradox by roboticist Hans Moravec, Marvin Minsky, and Rodney Brooks, emphasised the difficulty of sensorimotor tasks for AI systems. Moravec's Paradox states that AI systems excel in tasks requiring abstract reasoning but underperform in tasks requiring real-world interactions.
However, advancements in embodied AI are bridging this gap. Robots may soon blend AI cognition with physical interaction, thanks to these advancements. Companies like Figure, which raised $675 million, are enhancing their humanoid robot system Helix by integrating advanced perception, inference, and control capabilities via next-generation GPU infrastructure and large-scale multimodal data collection. This approach targets robots understanding and acting in complex, dynamic environments.
Moreover, the merger of MBody AI with Check-Cap focuses on embodied AI for autonomous workforce solutions, reflecting significant market growth potential. Advances in language-model-driven robotics, such as Nvidia’s Isaac GROOT N1 and DeepMind’s RT-2, exemplify the cutting edge in fusing large language models with embodied control.
The 2010s saw neural networks power breakthroughs in perception, such as facial recognition and AlphaGo's success in Go. This decade, ChatGPT and similar models achieved advanced natural language processing, showcasing the potential of cognitive AI. By 2022, ChatGPT started showcasing advanced cognitive skills, contrasting with the struggles in robotics.
Spatial Intelligence and Embodied AI might enable robots to gain human-like dexterity and adaptability for dynamic, real-world applications. Skills like perception and motor control have been honed over millions of years in humans and animals. These skills are deeply ingrained and unconscious in us, and as embodied AI continues to evolve, we may see robots embodying these skills too.
The future of robotics, powered by embodied AI, is promising. As we continue to make strides in this field, we are bringing us closer to a "ChatGPT moment" for robotics, where AI systems can understand and act in complex, dynamic environments, much like humans do.
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