Towards truly human-level intelligence in artificial applications

Abstract

Despite the fact that there are now a large number of successful bio-inspired applications in use in science and technology, we are still quite far removed from creating applications that display human-like intelligence. Putting together successful bio-inspired applications remains something of a black art; this is due to a lack of fundamental understanding of brain function. The causes for these problems were analysed in a ’Roadmap for Neuro-IT’ and were deemed to be sufficiently pressing to motivate one of five ’Grand Challenges’ in Neuro-IT: the ’Constructed Brain’. The challenge argued that one of the main bottlenecks to progress is that data taking and modelling in the neurosciences are being fractured across many research groups and communities; it makes proposals for addressing the issue. Similar observations, raised in two OECD workgroup papers have led to the formation of the International Neuroinformatics Coordinating Facility. As a consequence we can conclude that there is now a much higher awareness of the problems and that in the neurosciences the situation has improved dramatically. I will review recent initiatives to facilitate data management, modelling and simulation in the neurosciences. One problem remains unaddressed, however. The project-based funding of the brain sciences sets an upper limit to the complexity of brain models. Since the brain is truly complex, any individual project will fall short of capturing the brain’s complexity. The creation of a central infrastructure for the brain sciences is inescapable, but is unlikely to be realised soon. I will outline suggestions to handle the current situation.