Bio-AI: Mutually Beneficial Partnership

Nature and AI could benefit from each other. On the one hand, nature is a great source of inspiration for AI. On the other hand, AI could help us with natural resource management. Riddle In the article, you will find 9 riddles. Guessing them will allow you to get access to an amazing resource that will help you to get inspiration from nature. You will need to get one letter from each guess (an animal or a plant) and combine them, so that you get a link to the aforementioned resource. Search it with the terms like “artificial intelligence”, and you will find really cool ideas on how AI systems could be inspired by nature. Nature as an inspiration for AI Whenever you have a problem, ask nature first. Biomimicry is innovation inspired by nature. And it's a new way of inventing by looking to the natural world for inspiration. And asking, before we design anything, what would nature do here? (Janine Benyus) Riddle #1 Total number of letters: 8 The one you need to choose: 1st General design Well, first of all, AI itself was inspired by nature. It mimics human cognitive skills. Just like the human brain, AI-based technologies need energy to perform their chores. Modern AI technologies are often used to solve complex problems. For their algorithms to function, they require vast amounts of computing power that can be provided by large data centers. And these centers require a lot of energy that is not always readily available in remote and hostile areas and becomes increasingly expensive. Natural intelligence, in contrast, is extremely efficient in terms of energy usage. That is where biomimicry comes into play. Energy saving strategies inspired by a nervous system could be integrated into AI systems design. The power requirements of a brain is about 20 W. The brain has a number of features at different levels that allow it to maintain high performance and be energy efficient [1]. For example, at the coding level, neuronal networks may reduce neural activity while reacting to environmental changes by shifting the timing of spikes instead of increasing their number, thus saving energy [2]. At a macroscopic level, minimizing the wiring and packing it in a three-dimensional space helps to save energy as well [3]. These principles can be used in AI systems to minimize energy consumption. They could be integrated into neuromorphic architectures (computing hardware platforms that mimic the brain’s characteristics). Aside from the brain, power saving strategies can be also inspired by non-neural solutions. For example, there are distributed computing systems inspired by social insects. In these systems, each unit has very low energy consumption, and their interactions allow to solve complex problems (swarm intelligence) [4]. We could also think about the (resPonsiveness, heteROgeneity, decenTralization, rEdundancy, and CooperaTION) and apply its principles, when it comes to general design for AI systems. It ensures adaptability of a strategy, which helps the system using it to survive and evolve. PROTECTION framework Riddle #2 Total number of letters: 5 The one you need to choose: 4th Frameworks There are some frameworks inspired by nature. For example, let’s take a look at Organic. In this case, each component of the framework and related concepts are represented as cell components or chemicals (so that we get sort of metaphors). The whole Cell represents an application. The Server is represented as a membrane, and plasma has the rest of components (Router, Render, and CSS represented as organelles). The latter communicate via chemicals and react on them (page (emitted by the router), request (emitted by the server), and css (emitted by the CSS)). Finally, DNA is sort of configuration for the components of the Cell [6, 7]. Riddle #3 Total number of letters: 8 The one you need to choose: 1th Riddle #4 Here you need to solve a maze and choose the animal that touches the path. The letter that you need to choose: 4th Algorithms There are a lot of algorithms used in computing inspired by nature like an ant colony optimization algorithm, bees algorithm, flower pollination algorithm, bat algorithm, artificial neural networks and a lot of others. Riddle #5 Here you need to find an animal on a hidden image. Total number of letters: 3 The one you need to choose: 2nd https://js1k.com/2017-magic/demo/2842?embedable=true The ant colony optimization algorithm is inspired by the behavior of ants which try to find the most beneficial sources of food and communicate this information to the rest of the colony with the help of the pheromones. This algorithm mimics their behavior and helps to find the best solution to different problems using artificial 'ants' [8]. The bees algorithm is similar to the aforementioned algorithm, but mimics the foraging behavior of honey bees. Artificial neural networks mimic biological neural systems to solve different AI problems. Riddle #6 Total number of letters: 10 The one you need to choose: 3rd The potential of AI for natural resource management Now, let’s discuss how AI could help with the management of the Earth’s resources. AI solutions could help to assess and monitor nature, aid in decision-making and threat prediction [9]. Let’s take a look at some examples. Rainforest Connection provides an acoustic monitoring system / RFCx Guardians (basically, a group of smartphones powered by solar energy and placed high up in the trees) that in combination with AI can help to detect illegal logging and poaching. This system then sends real-time messages to rangers to take actions. Also, this system can be used by biologists / ecologists to monitor biodiversity [10]. Riddle #7 Total number of letters: 4 The one you need to choose: 2nd Global Forest Watch provides a number of tools using AI to monitor the world’s forests and protect them [11]. Also, Generative AI may aid in developing of different innovations (including nature-inspired ones) that might help with the intelligent management of natural resources [12]. Riddle #8 Total number of letters: 6 The one you need to choose: 4th Conclusion What nature has to teach is more than we have ever imagined (John Lanie) Developing different AI systems may help us to better understand natural intelligence and what makes us human. In its turn, this will allow to develop even more intelligent AI systems. The future of AI is Natural. Riddle #9 Total number of letters: 10 The one you need to choose: 7th The headline image was composed by me with the help of the , , , and images. wreath key chest world map Other images sourced from Pixabay. The divider was created by me with the help of the world map image. Riddles sourced from . Logiclike web-site Reference Krichmar JL, Severa W, Khan MS, Olds JL. Making BREAD: Biomimetic Strategies for Artificial Intelligence Now and in the Future. Front Neurosci. 2019 Jun 27;13:666. doi: 10.3389/fnins.2019.00666. PMID: 31316340; PMCID: PMC6610536. Malyshev A, Tchumatchenko T, Volgushev S, Volgushev M. Energy-efficient encoding by shifting spikes in neocortical neurons. Eur J Neurosci. 2013 Oct;38(8):3181-8. doi: 10.1111/ejn.12338. Epub 2013 Aug 14. PMID: 23941643; PMCID: PMC3810016. Laughlin SB, Sejnowski TJ. Communication in neuronal networks. Science. 2003 Sep 26;301(5641):1870-4. doi: 10.1126/science.1089662. PMID: 14512617; PMCID: PMC2930149. Rubenstein M, Cornejo A, Nagpal R. Robotics. Programmable self-assembly in a thousand-robot swarm. Science. 2014 Aug 15;345(6198):795-9. doi: 10.1126/science.1254295. Epub 2014 Aug 14. PMID: 25124435. Rzeszutko, Elzbieta & Mazurczyk, Wojciech. (2014). Insights from Nature for Cybersecurity. Health security. 13. 10.1089/hs.2014.0087. node-organic Organic Development Ant colony optimization algorithm Exploring the potential of Artificial Intelligence for nature conservation Rainforest Connection Global Forest Watch Bio-Inspired AI: When Generative AI and Biomimicry Overlap