AI Medical Compendium Journal:
Trends in cognitive sciences

Showing 21 to 30 of 47 articles

Realizing the promise of AI: a new calling for cognitive science.

Trends in cognitive sciences
Rapid progress in artificial intelligence (AI) places a new spotlight on a long-standing question: how can we best develop AI to maximize its benefits to humanity? Answering this question in a satisfying and timely way represents an exciting challeng...

The signature-testing approach to mapping biological and artificial intelligences.

Trends in cognitive sciences
Making inferences from behaviour to cognition is problematic due to a many-to-one mapping problem, in which any one behaviour can be generated by multiple possible cognitive processes. Attempts to cross this inferential gap when comparing human intel...

Next-generation deep learning based on simulators and synthetic data.

Trends in cognitive sciences
Deep learning (DL) is being successfully applied across multiple domains, yet these models learn in a most artificial way: they require large quantities of labeled data to grasp even simple concepts. Thus, the main bottleneck is often access to super...

Dual coding of knowledge in the human brain.

Trends in cognitive sciences
How does the human brain code knowledge about the world? While disciplines such as artificial intelligence represent world knowledge based on human language, neurocognitive models of knowledge have been dominated by sensory embodiment, in which knowl...

Generative adversarial networks unlock new methods for cognitive science.

Trends in cognitive sciences
Generative adversarial networks (GANs) enable computers to learn complex data distributions and sample from these distributions. When applied to the visual domain, this allows artificial, yet photorealistic images to be synthesized. Their success at ...

Epistemic Autonomy: Self-supervised Learning in the Mammalian Hippocampus.

Trends in cognitive sciences
Biological cognition is based on the ability to autonomously acquire knowledge, or epistemic autonomy. Such self-supervision is largely absent in artificial neural networks (ANN) because they depend on externally set learning criteria. Yet training A...

Mind Meets Machine: Towards a Cognitive Science of Human-Machine Interactions.

Trends in cognitive sciences
As robots advance from the pages and screens of science fiction into our homes, hospitals, and schools, they are poised to take on increasingly social roles. Consequently, the need to understand the mechanisms supporting human-machine interactions is...

Embracing Change: Continual Learning in Deep Neural Networks.

Trends in cognitive sciences
Artificial intelligence research has seen enormous progress over the past few decades, but it predominantly relies on fixed datasets and stationary environments. Continual learning is an increasingly relevant area of study that asks how artificial sy...

Artificial Intelligence and the Common Sense of Animals.

Trends in cognitive sciences
The problem of common sense remains a major obstacle to progress in artificial intelligence. Here, we argue that common sense in humans is founded on a set of basic capacities that are possessed by many other animals, capacities pertaining to the und...

Understanding Human Intelligence through Human Limitations.

Trends in cognitive sciences
Recent progress in artificial intelligence provides the opportunity to ask the question of what is unique about human intelligence, but with a new comparison class. I argue that we can understand human intelligence, and the ways in which it may diffe...