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Neuromorphic Cognitive Learning Systems: The Future of Artificial Intelligence?

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Abstract

In this position paper, I outline the caveats of the current artificial intelligence (AI) field driven by deep learning (DL) and large data volumes. Although AI/DL has demonstrated huge potential and attracted huge investments globally, it encounters big problems – it not only need to collect huge datasets and spend enormous time and resources to be trained on them, but also the trained system cannot deal effectively with any never encountered before (novel) data. From a human perspective, any current AI/DL system is completely unintelligent. It is only able to represent information but have no awareness of what this information means. I propose as an alternative the Neuromorphic Cognitive Learning Systems (NCLS), intimate imitations of animal and human brains, able to address the AI/DL limitations and achieve true artificial general intelligence. Similar to human and animal brains NCLS are unparalleled in their ability to rapidly, and on their own, adapt and learn from changing and unexpected environmental contingencies with very limited resources. I describe how NCLS driven AI inspired by human/animal brains can pave the way to new computing technologies with the potential to revolutionize the industry, economy and society. It is my strong belief that NCLS investigations will have major impact to real-time autonomous systems to achieve human-like intelligence capabilities.

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Data Availability

No datasets were generated or analysed during the current study.

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Funding

This work was supported by the EU HORIZON 2020 Project ULTRACEPT under Grant 778062.

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Authors and Affiliations

  1. Lincoln Group of Excellence for Neuromorphic Cognitive Learning Systems, College of Health and Science, University of Lincoln, Lincoln, UK

    Vassilis Cutsuridis

  2. School of Computer Science, University of Lincoln, Lincoln, LN6 7TS, UK

    Vassilis Cutsuridis

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  1. Vassilis Cutsuridis
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V.C. wrote the manuscript.

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Correspondence to Vassilis Cutsuridis.

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The authors declare no competing interests.

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Cutsuridis, V. Neuromorphic Cognitive Learning Systems: The Future of Artificial Intelligence?. Cogn Comput (2024). https://doi.org/10.1007/s12559-024-10308-x

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