The Whole Brain Architecture Initiative (WBAI) aims to foster research into architectural approaches to general intelligence. They have held a series of events – the Hackathons – that encourage and support the development of new models which provide working solutions to questions about the possible architecture of general intelligence in the brain.
You can read about previous hackathons here.
The 5th Hackathon will focus on the topic of working memory (WM). Unlike previous years, a longer period of remote/at-home R&D – known as the “modelathon” – will be used to develop models in depth prior to the main event. WBAI has announced that theoretical models of working memory for the specified task should be submitted by the due-date for prizes including cash!
The nature of the tasks will be “delayed sample matching”. This means that models must use WM to remember observed objects, and then recognize new instances of them. The new instances may be transformed in appearance, change colour, or be occluded by other objects. Distraction objects may also be employed in some task variants. Full details of the experimental conditions will be provided shortly.
We encourage AI/ML researchers with an interest in working memory and neural approaches to reinforcement-learning to apply via the link above.
Project AGI will be collaborating with WBAI on the definition of the hackathon tasks and to provide “stub” modules that contestants can use as a starting point. Used together, the stubs will be sufficient to solve the easiest tasks, allowing contestants to rapidly develop more sophisticated modules for specific capabilities.