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Brain-inspired Computing
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1Quantum Revolution& Advanced AI2HumanAugmentation3Eco-Regeneration& Geo-Engineering4Science& Diplomacy1.11.21.31.42.12.22.32.43.13.23.33.43.54.14.24.34.44.5HIGHEST ANTICIPATIONPOTENTIALAdvancedArtificial IntelligenceQuantumTechnologiesBrain-inspiredComputingBiologicalComputingCognitiveEnhancementHuman Applications of Genetic EngineeringRadical HealthExtensionConsciousnessAugmentation DecarbonisationWorldSimulationFuture FoodSystemsSpaceResourcesOceanStewardshipComplex Systems forSocial EnhancementScience-basedDiplomacyInnovationsin EducationSustainableEconomicsCollaborativeScience Diplomacy
1Quantum Revolution& Advanced AI2HumanAugmentation3Eco-Regeneration& Geo-Engineering4Science& Diplomacy1.11.21.31.42.12.22.32.43.13.23.33.43.54.14.24.34.44.5HIGHEST ANTICIPATIONPOTENTIALAdvancedArtificial IntelligenceQuantumTechnologiesBrain-inspiredComputingBiologicalComputingCognitiveEnhancementHuman Applications of Genetic EngineeringRadical HealthExtensionConsciousnessAugmentation DecarbonisationWorldSimulationFuture FoodSystemsSpaceResourcesOceanStewardshipComplex Systems forSocial EnhancementScience-basedDiplomacyInnovationsin EducationSustainableEconomicsCollaborativeScience Diplomacy

Emerging Topic:

1.3Brain-inspired Computing

Associated Sub-Fields

The most powerful, flexible and efficient “computer” that we know of is the one we all carry in our heads: the human brain. Research in the field of brain-inspired, or neuromorphic, computing seeks to develop machines that will ultimately display the same capabilities, often by emulating the brain's elements, structures and processes.

Brains perform low-energy, high-speed operations using rules, memory and transfer of knowledge across domains, in order to enable organisms to function, survive and thrive. Neural systems have to process interactions with the environment and with other living organisms, either in real-time or in imagined encounters that anticipate gains and losses. To do so, they process a potentially confusing array of information from multiple sources — sound, touch, vision, memory and so on — and apply remarkably flexible algorithms to plan, make decisions, and act on them through movements or communications.

The fundamental principles of information processing and storage in the brain are far from understood. It is clear that the brain operates in a very different way from the stored-program computer, which makes mimicking the brain conceptually difficult. However, various biologically plausible networks of artificial neurons are being built, and their properties explored. If any of these can inspire a route to brain-like information processing, the technological applications will range from robotics and intelligent systems in mobile phones to breakthrough treatments for diseases of the brain and new accelerators of scientific discovery.

Selection of GESDA best reads and key reports

Perhaps the most recent roadmap for the field is the multi-institution “2021 Roadmap on Neuromorphic Computing and Engineering”1.

“Large scale neuromorphic computing systems” (https://iopscience.iop.org/article/10.1088/1741-2560/13/5/051001/meta) offers a brief history of neuromorphic engineering and an analysis of the principal current large-scale projects.2

“A Survey of Neuromorphic Computing and Neural Networks in Hardware” (https://arxiv.org/pdf/1705.06963.pdf) is a 2017 review by IEEE members that digests research in progress and highlights the important gaps in achievement that will need to be addressed.3

“The building blocks of a brain-inspired computer” (https://aip.scitation.org/doi/full/10.1063/1.5129306) focusses on the central primitives of a brain-inspired computer.4

Drawing inspiration from the brain to inform the design of computing systems involves synthesising expertise from many fields. This convergence is the driving force behind the need for anticipation in this area as the transformational impact of such a cross-cutting discipline is hard to predict. Breakthroughs are also likely to have highly pervasive effects, with neural networks in particular having potential uses cases in a wide range of areas. Tempering this though, is the fact that respondents predict this field is less than a decade away from maturity. That means many of these technologies are already upon us, reducing the need for anticipation.

GESDA Best Reads and Key Resources