Figure 2 - uploaded by Stefan Heinrich
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1: A map of the human brain (dominant-left hemisphere) with regions involved in language processing. For orientation the map is coloured: the cortex' temporal lobe in green, frontal lobe in red, parietal lobe in blue, and occipital lobe in light grey as well as cerebellum and medulla in dark grey. Highlighted regions are the Primary Auditory Cortex (A1), Superior Temporal Gyrus (STG) (including anterior and posterior parts), Superior Temporal Sulcus (STS), Middle Temporal Gyrus (MTG) (including anterior and posterior parts), Inferior Temporal Sulcus (ITS), Inferior Frontal Gyrus (IFG) (including anterior and posterior parts), PreMotor Cortex (PMC), and Primary Motor Cortex (M1).
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The human brain is one of the most complex dynamic systems that enables us to communicate (and externalise) information by natural language. Our languages go far beyond single sounds for expressing intentions - in fact, human children already join discourse by the age of three. It is remarkable that in these first years they show a tremendous capab...
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Citations
... We argue that these conditions inherently enable the development of distributed representations of knowledge. For example, in our research, we found that architectural mechanisms, like different timings in the information processing in the cortex, foster compositionality that in turn enables both the development of more complex body actions and the development of language competence from primitives (Heinrich 2016). These kinds of distributed representations are coherent with the cognitive science on embodied cognition. ...
We comment on ways in which Lake et al. advance our understanding of the machinery of intelligence and offer suggestions. The first set concerns animal-level versus human-level intelligence. The second concerns the urgent need to address ethical issues when evaluating the state of artificial intelligence.
... We argue that these conditions inherently enable the development of distributed representations of knowledge. For example, in our research, we found that architectural mechanisms, like different timings in the information processing in the cortex, foster compositionality that in turn enables both the development of more complex body actions and the development of language competence from primitives (Heinrich 2016). These kinds of distributed representations are coherent with the cognitive science on embodied cognition. ...
The argument by Lake et al. to create more human-like robots is, first, implausible and, second, undesirable. It seems implausible to me that a robot might have friends, fall in love, read Foucault, prefer Scotch to Bourbon, and so on. It seems undesirable because we already have 7 billion people on earth and don't really need more.
... We argue that these conditions inherently enable the development of distributed representations of knowledge. For example, in our research, we found that architectural mechanisms, like different timings in the information processing in the cortex, foster compositionality that in turn enables both the development of more complex body actions and the development of language competence from primitives (Heinrich 2016). These kinds of distributed representations are coherent with the cognitive science on embodied cognition. ...
Lake et al. underrate both the promise and the limitations of contemporary deep learning techniques. The promise lies in combining those techniques with broad multisensory training as experienced by infants and children. The limitations lie in the need for such systems to possess functional subsystems that generate, monitor and switch goals and strategies in the absence of human intervention.
... NAO from Aldebaran is one of the most commonly used small humanoid robots in developmental and multimodal research, e.g. [17], [8]. NAO features a large number of sensors and degrees of freedom for its size of ca. ...
Interdisciplinary research, drawing from robotics, artificial intelligence, neuroscience, psychology, and cognitive science, is a cornerstone to advance the state-of-the-art in multimodal human-robot interaction and neuro-cognitive mod-eling. Research on neuro-cognitive models benefits from the embodiment of these models into physical, humanoid agents that possess complex, human-like sensorimotor capabilities for multimodal interaction with the real world. For this purpose, we develop and introduce NICO (Neuro-Inspired COmpanion), a humanoid developmental robot that fills a gap between necessary sensing and interaction capabilities and flexible design. This combination makes it a novel neuro-cognitive research platform for embodied sensorimotor computational and cognitive models in the context of multimodal interaction as shown in our results.
Lake et al. point out that grounding learning in general principles of embodied perception and social cognition is the next step in advancing artificial intelligent machines. We suggest it is necessary to go further and consider lifelong learning, which includes developmental learning, focused on embodiment as applied in developmental robotics and neurorobotics, and crossmodal learning that facilitates integrating multiple senses.
