Project description
Deep neural network communication inspired by human language
Deep neural networks (DNNs) are machine learning algorithms that aim to mimic the information processing of the brain. DNNs constitute a promising solution for introducing AI in our daily lives, from self-driving cars to smartphones and games. The EU-funded ALiEN project proposes to improve the DNN interface and develop a universal language that can be easily implemented across different applications. The project is inspired by human language and aims to replace existing interfaces with generic communication protocols. Researchers will set up a training environment for DNN interaction that will help improve existing DNNs and address complexities associated with real-life applications.
Objective
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 community size and communication channel on the expressiveness and ease of acquisition of emergent protocols. The emergence of general protocols will be encouraged by a training environment characterized by varied inputs and interaction among numerous DNNs. The best emerged protocols will also be taught in a supervised way to new DNNs, with the final aim of establishing a “universal” DNN language. Next, I will explore how emergent protocols can help interfacing out-of-the box, state-of-the-art DNNs, only requiring the addition of light input and output layers to existing pre-trained models. Finally, a simplified home automation use case will demonstrate the usefulness of emergent protocols in a scenario that features some of the complexities to be expected in real-life applications. The project will also thoroughly analyze the emerging protocols, with the concurrent aims of i) identifying and favoring features that make them more expressive and easier to learn; ii) enhancing interpretability; and iii) gathering scientific insights into communication emergence in a non-human “species”.
All in all, ALiEN will take a first bold step towards enabling autonomous DNN interaction, and thus genuinely adaptive AI systems.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
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Keywords
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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H2020-EU.1.1. - EXCELLENT SCIENCE - European Research Council (ERC)
MAIN PROGRAMME
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Topic(s)
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
ERC-ADG - Advanced Grant
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Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) ERC-2020-ADG
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Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.
08002 Barcelona
Spain
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.