ERC Advanced Grant · 2020
Autonomous Linguistic Emergence in neural Networks
Deep neural networks (DNNs) are specialized computational models lacking a standard interface. If a complex task requires different DNNs, an ad-hoc connection must be laboriously designed. Inspired by human language, ALiEN wants to replace such ad-hoc interfaces with generic communication protocols optimized for ease of learning by DNNs that might have different architectures and functions. ALiEN “languages” are not hand-crafted: they emerge by training DNNs to share information through communication, offering the scalability and robustness to noise that is an asset of learned systems. A first set of experiments will study, in tightly controlled settings, the impact of input, training…
From the public funding record at EU CORDIS. Describes the funded project, not the reviews below.