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Leveraging insights from neuroscience to build adaptive artificial intelligence
1École Polytechnique Fédérale de Lausanne (EPFL), Brain Mind Institute, Geneva, Switzerland. mackenzie.mathis@epfl.ch.
Nature Neuroscience
|December 30, 2025
Summary
Biological intelligence offers a blueprint for creating adaptive artificial intelligence (AI). By studying how animals learn and adapt, researchers aim to build AI systems capable of online learning and rapid environmental adaptation.
Area of Science:
- Neuroscience
- Artificial Intelligence
- Cognitive Science
Background:
- Biological intelligence demonstrates inherent adaptability through continuous action adjustment based on environmental feedback.
- Developing artificial intelligence (AI) with similar adaptive capabilities remains a significant challenge in the field.
- Recent neuroscience research highlights how animals learn and adapt world models, providing inspiration for AI development.
Purpose of the Study:
- To define and explore the concept of 'adaptive intelligence' by integrating insights from biological systems into AI.
- To review the fundamental behavioral and neural mechanisms underlying adaptive biological intelligence.
- To examine the parallels between biological adaptation and current advancements in artificial intelligence.
Main Methods:
- Reviewing behavioral and neural studies on animal learning and adaptation.
- Analyzing current progress and limitations in artificial intelligence.
- Exploring brain-inspired computational approaches for adaptive algorithms.
Main Results:
- Biological intelligence provides a foundation for understanding online learning, generalization, and rapid adaptation in AI.
- Neuroscience offers valuable insights into how agents can learn and update their internal models of the environment.
- Progress in AI shows promise in developing agents that can adapt to dynamic conditions, though challenges remain.
Conclusions:
- Harnessing principles of biological intelligence is crucial for advancing AI towards true adaptive capabilities.
- Future AI development should focus on brain-inspired methods to achieve online learning and environmental responsiveness.
- The integration of neuroscience and AI research paves the way for more robust and adaptable artificial intelligence systems.
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