Understanding Neural Networks as a Foundation
The development of artificial intelligence that emulates the human brain starts with a deep understanding of the neural networks in the brain. Ultimately, algorithms are to be designed with cognitive abilities equivalent to or larger than humans, which can interpret the image and extract information from it just like a human would do. These involve drawing analogies in terms of the learning mechanisms between the two, the biological and the artificial neural networks, with a greater scope for the problem-solving abilities and flexibility of AI in a more humanly cognitive manner.
Indeed, studies show that using AI to digitally mimic neural functions is also furthering our understanding of the brain, creating a synergetic effect in the development of biology and technology.
The Emergence of a Functional Map
New but very symbiotic territory is emerging in the intersection of the life sciences and technology.
The ambitious idea started as an initiative: to build an artificial version of the human brain, complete down to its labyrinthine web of neurons and connections. The achievement of this replica, though definitely an outlying goal at the present time, would have been evolving into a valuable exchange of knowledge. These digital systems, created in the modern era, are slowly improving our knowledge of the workings and processes of our minds with the aid of novel simulations and models.
Insights from the Visual System
The sensory processes were complex in their depth, for example, vision. The visual system was one of the multiple cognitive tasks humans performed swiftly and on an ongoing basis, from distinguishing colors and establishing the localization of objects to extraction of relevant information from a complex view of scenes. In this way, the interface between artificial and natural vision systems would focus on very demanding computations while, at the same time, opening the salient abilities of one another. A history of problems with artificial vision systems again underscores the challenge in mimicking the biological vision system but suggests that current progress is pointing toward parity.
Learning from the Animal Mind
Studies of the connectome—for example, mapping neural connections in a brain—have been very rewarding in animal research. The base for understanding the behavioral mechanisms and decision-making process for them by means of mapping has been achieved through the simple neural architecture of simple organisms. When it comes to neurological research, one can only think of even more complex animals in which advanced imaging and some novel microscopy methods would help understand in detail the neural activity at a cellular level. The research of the neural and glial cells brings a view of extensive support networks that facilitate the course of cognitive processes. One example of that ongoing dialogue between artificial intelligence and neuroscience is lighting up some of the dark spaces not only in the complex structure and function of the brain but in the integrated approaches bringing about some illumination. These continuing, reciprocal influences by the two will synergize our digital toolset and their understanding of biological systems, promising a bright future where both technology and biology are integrated.
