Attempts to create a system that acts and makes decisions like humans are developing in the field of AI. This topic is vast and controversial. New approaches to AI spring from the idea that intelligence emerges as much from cells, bodies, and societies as it does from evolution, development and learning.  

Traditionally, AI has been concerned with reproducing the abilities of human brains; newer approaches take inspiration from a wide range of biological structures capable of autonomous self-organization. These new approaches include evolutionary computation and evolutionary electronics, artificial neural networks, immune systems, bio-robotics, and swarm intelligence—to mention only a few. 

IIT Kanpur’s artificial muscle 

 Earlier this year, IIT Kanpur developed a bio-inspired artificial muscle for next-generation space robots and adaptive robotic prostheses for bio-medical applications in the country. It can also be used in smart buildings, automobiles and the aviation industry.  

The technology comprises fast and efficient actuators, whose purpose is to generate mechanical output, such as force and displacement, by transforming electrical energy. The researchers said that shape memory alloy-based actuators are a class of smart materials that can restore their shape after exposure to high temperatures.  

The IIT Kanpur research can further encourage researchers in the domain of biomechatronics to develop adaptive robotic prostheses for bio-medical applications in the country. In addition, the technology is also beneficial in the development of patient rooms with low maintenance and quieter operation. 

MIT research 

 Juncal Arbelaiz Mugica, a researcher at MIT, finds inspiration in the biological intelligence of invertebrates such as octopus and jellyfish. The ultimate goal is to design novel control strategies for flexible “soft” robots that could be used in tight or delicate surroundings, such as a surgical tool or for search-and-rescue missions. 

 In the biological world, the “controller” is usually associated with the brain and central nervous system. It commands the body muscles for movements. Jellyfish and a few other soft organisms lack a centralized nerve center or brain. Inspired by this observation, she is working toward a theory where soft-robotic systems could be controlled using decentralized sensory information sharing. 

 According to Arbelaiz, when sensing and actuation are distributed in the body of the robot and onboard computational capabilities are limited, it might be difficult to implement centralized intelligence. Therefore, they need decentralized schemes that, despite sharing sensory information only locally, guarantee the desired global behavior. 

Neuroevolution of Artificial General Intelligence 

 Researchers from Oslo Metropolitan University and the Norwegian University of Science and Technology developed a framework recently. It was known as the Neuroevolution of Artificial General Intelligence (NAGI). Neuroevolution is a sub-field of AI which utilizes evolutionary algorithms to generate ANN. This framework uses the biologically-realistic models of neutrons for performing computations. 

 The concept of AGI is still science fiction, and once the researchers accomplish to gain the full potential of this technology where there will be numerous advantages in the modern world one can ever think of. With the advent of this technology, there will be fewer human labors and reduced issues like violence and corruption.