Cobots with Conversation, Cognition and PerceptiOn

But in practice, current models rely on brute-force training approaches using billions of labelled examples, while the datasets and computing resources available to academic and industrial researchers are typically much smaller.
Compared to artificial neural networks, real brains learn much more efficiently. We thus take inspiration from the cognitive science idea of a Global Workspace (GW) to build a novel class of AI systems.
The GW, a unique model of multimodal grounding (encompassing perception, action and semantic representations), can promote advances in perceptual models and support both top-down interactions (from language and semantics to perception and action) of interest to linguists and bottom-up interactions (from active perception and navigation to semantic abstractions) of interest to roboticists
The high-risk/high-gain hypothesis is that the modalities complement one another synergistically, such that the whole system is much more efficient than the sum of its parts, not just for multimodal tasks but also when evaluated in the initial domains (vision, NLP, robotics).
Building frugal perceptual and cognitive models that can support language grounding and embodiment and provide semantic representations to robotic agents is expected to have important beneficial consequences for ANITI’s industrial partners (e.g. Airbus, Linagora).