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The rise of intelligent matter
Open accessAbstract
Artificial intelligence (AI) is accelerating the development of unconventional computing paradigms inspired by the abilities and energy efficiency of the brain. The human brain excels especially in computationally intensive cognitive tasks, such as pattern recognition and classification. A long-term goal is de-centralized neuromorphic computing, relying on a network of distributed cores to mimic the massive parallelism of the brain, thus rigorously following a nature-inspired approach for information processing. Through the gradual transformation of interconnected computing blocks into continuous computing tissue, the development of advanced forms of matter exhibiting basic features of intelligence can be envisioned, able to learn and process information in a delocalized manner. Such intelligent matter would interact with the environment by receiving and responding to external stimuli, while internally adapting its structure to enable the distribution and storage (as memory) of information. We review progress towards implementations of intelligent matter using molecular systems, soft materials or solid-state materials, with respect to applications in soft robotics, the development of adaptive artificial skins and distributed neuromorphic computing.
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“Therefore, there is a rising interest in energy-efficient hardware primarily optimized for artificial intelligence [29].”
From Brain-inspired computing systems: a systematic literature review (2024) · cites this paper as [29]
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“Efforts to program abiotic polymer networks with biomimetic behavior have seen some success 20–23 , but purely chemical approaches typically require large input signals and multiple orthogonal chemistries, limiting their programmability to relatively simple operations 24–26 .”
Tomography of memory engrams in self-organizing nanowire connectomes
Milano, G., Cultrera, A., Boarino, L., Callegaro, L., & Ricciardi, C. (2023) · Nature Communications · doi:10.1038/s41467-023-40939-x · Cited by 25
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Physical Networks Become What They Learn.
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Programming metastable transition sequences in digital mechanical materials
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A Reconfigurable Piezoelectric Actuator With Asymmetric Rhomboid Drive Module
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Stimuli-Triggered Dynamic Transformations in Supramolecular Polymers
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Magnetic field–driven particle assembly and jamming for bistable memory and response plasticity
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Polyelectrolyte/Surfactant Mixtures: A Pathway to Smart Foams
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Sensor-actuator integration for intelligent devices
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Electrospun biomedical nanofibers and their future as intelligent biomaterials
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Homogeneous Memristors with Tunable Decay Dynamics for Self-Adaptive Reservoir Computing
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Mechanical Computing with Transmissive Snapping of Kirigami Shells
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Active pattern formation emergent from single-species nonreciprocity
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Probing Fast Transformation of Magnetic Colloidal Microswarms in Complex Fluids
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Noisy pursuit and pattern formation of self-steering active particles
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A photo-mechanically inactive tough gel exhibits multimodal, light-guided underwater navigation
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Metadata
- Authors
- Kaspar, C., Ravoo, B. J., van der Wiel, W. G., Wegner, S. V., & Pernice, W. H. P.
- Affiliations
- University of Münster (DE)
- Corresponding author
- Pernice, W. H. P.
- Venue
- Nature
- Published
- 2021-06-16
- Volume
- 594
- Issue
- 7863
- Pages
- 345-355
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- OpenAlex
- W3169707058
- Cited by
- 526
- References
- 0
- Citations by year
- 2026: 70 · 2025: 136 · 2024: 112 · 2023: 106 · 2022: 75 · 2021: 27
- FWCI
- 5.06
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Nature (publishedVersion)
- PubMed (publishedVersion)
- University of Twente Research Information (publishedVersion, other-oa)
- RePEc: Research Papers in Economics (submittedVersion)
- University of Twente Research Information (submittedVersion, other-oa)
- Funders
- European Commission (101017237, HORIZON2020)
- Deutsche Forschungsgemeinschaft (SFB 1459, 433682494)
- Volkswagen Foundation (A126874)
- Topics
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Advanced Memory and Neural Computing
- Physical Sciences › Engineering › Mechanical Engineering › Advanced Materials and Mechanics
- Physical Sciences › Computer Science › Artificial Intelligence › Neural Networks and Reservoir Computing
- Keywords
- neuromorphic computing, decentralized computing, molecular systems, soft materials, solid-state materials, soft robotics, distributed memory, pattern recognition
- MeSH terms
- Artificial Intelligence, Colloids, Environment, Enzymes, Equipment Design, Homeostasis, Humans, Physical Stimulation, Robotics, Skin, Artificial, Biomimetics, Biomimetic Materials
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