Difference between revisions of "Bio-inspired Computing"

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= Embodied Minds and Cognitive Agents =
 
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* [https://drmichaellevin.org/resources/ The Levin Lab and Dr. Michael Levin’s research]
discuss embodied minds, his research into limb regeneration and collective intelligence, cognitive light cones, and much more. Dr. Levin and the Levin Lab work at the intersection of biology, artificial life, bioengineering, synthetic morphology, and cognitive science.
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* [https://thoughtforms.life/about/ Forms of life, forms of mind | Dr. Michael Levin]
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* [https://news.uchicago.edu/how-bioelectricity-could-regrow-limbs-and-organs How bioelectricity could regrow limbs and organs, with Michael Levin (Ep. 112)] ... Biologist’s innovative research on how cells rebuild themselves could be the future of regenerative medicine
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Discuss embodied minds, his research into limb regeneration and collective intelligence, cognitive light cones, and much more. Dr. Levin and the Levin Lab work at the intersection of biology, artificial life, bioengineering, synthetic morphology, and cognitive science.
  
 
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Revision as of 19:49, 9 February 2024

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Bio-inspired Computing is a subset of metaphor-based metaheuristics

Bio-inspired AI or Nature-inspired AI is a branch of artificial intelligence that seeks to develop intelligent agents by mimicking the behavior of natural systems. This can include the behavior of animals, plants, or even entire ecosystems. Bio-inspired AI is a field of study that seeks to develop artificial intelligence (AI) systems by taking inspiration from biological systems. This can include the structure and function of biological organisms, as well as the principles of evolution and natural selection.

There are many different areas of bio-inspired AI, but some of the most common include:

  • Artificial neural networks: are inspired by the structure and function of the human brain. They are made up of interconnected nodes that can learn to recognize patterns and make decisions.
  • Genetic algorithms: are inspired by the process of natural selection. They use a technique called mutation to randomly change the parameters of an algorithm, and then select the best-performing algorithms to continue evolving.
  • Evolutionary computation: is a broad term that encompasses a variety of techniques inspired by evolution, such as genetic algorithms, genetic programming, and differential evolution.
  • Swarm intelligence: is inspired by the behavior of social insects, such as ants and bees. These insects are able to coordinate their actions to achieve complex tasks, such as building nests and foraging for food.
  • Biomimetics: is the field of engineering that seeks to design artificial systems that mimic the function of biological systems. This can include the development of artificial limbs, organs, and sensors.


The world of AI has a lot of things around it to thank for its existence in our technological landscape of today. Not only have humans spent decades of research perfecting the mathematical calculations to make these wonderfully complex learning algorithms work but during this time we have looked further than our own species as inspiration to make the next generation of intelligent presence on our planet. Mother Nature, and all that it encompasses, has it’s roots firmly planted in the workings of Artificial Intelligence — and it’s here to stay. 5 Ways mother nature inspires artificial intelligence | Luke James - Towards Data Science






Biological and Artificial Intelligence

Explores the evolution of human intelligence and its implications for AI. The book identifies the five major breakthroughs in the history of the brain that gave rise to our cognitive abilities. They are:

  • The emergence of neurons**. About a billion years ago, the first cells with specialized functions for communication and computation appeared, forming the basis of nervous systems.
  • The development of the cortex**. About 500 million years ago, the first vertebrates evolved a thin layer of tissue around their brains, called the cortex, that enabled complex sensory processing and motor control.
  • The expansion of the cortex**. About 200 million years ago, the cortex of mammals began to grow larger and more folded, creating more surface area and connections for higher cognitive functions such as memory, learning, and planning.
  • The specialization of the cortex**. About 100 million years ago, the cortex of primates became more differentiated into distinct regions, each with specialized roles for vision, language, social cognition, and other abilities.
  • The integration of the cortex**. About 2 million years ago, the cortex of hominins (our ancestors) developed a dense network of long-range connections, called the default mode network, that enabled self-awareness, creativity, and mental simulation.



Embodied Minds and Cognitive Agents

Discuss embodied minds, his research into limb regeneration and collective intelligence, cognitive light cones, and much more. Dr. Levin and the Levin Lab work at the intersection of biology, artificial life, bioengineering, synthetic morphology, and cognitive science.