Find below EMERGE’s news articles, press releases, digests of scientific publications, as well as other outreach materials.

Shared awareness could lead to greener, more ethical, and useful smart machines

Shared awareness could lead to greener, more ethical, and useful smart machines

Calendar31 July 2024

The EMERGE project proposes a collaborative shared awareness as a more reliable, energy-efficient, and ethically tractable framework for the coordination between artificial systems and humans than an artificial general intelligence. Read our Press Release!

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Publication: Shared Awareness Across Domain-Specific Artificial Intelligence: An Alternative to Domain-General Intelligence and Artificial Consciousness

Publication: Shared Awareness Across Domain-Specific Artificial Intelligence: An Alternative to Domain-General Intelligence and Artificial Consciousness

Calendar17 July 2024

In this work, EMERGE partners add their voice to a few ones which propose that investing in specialized AI systems tailored to specific tasks can be overall more effective than developing general intelligence.

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Publication: Continual pre-training mitigates forgetting in language and vision

Publication: Continual pre-training mitigates forgetting in language and vision

Calendar01 July 2024

In this work, EMERGE partners from the University of Pisa investigate the characteristics of the Continual Pre-Training scenario, where a model is continually pre-trained on a stream of incoming data and only later fine-tuned to different downstream tasks.

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Workshop on Structural Priors as Inductive Biases for Learning Robot Dynamics

Workshop on Structural Priors as Inductive Biases for Learning Robot Dynamics

Calendar03 June 2024

EMERGE partners from TUDelft are organising the “Workshop on Structural Priors as Inductive Biases for Learning Robot Dynamics” during the 20th RSS Conference, to be held in Delft, Netherlands, on July 15th, 2024.

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6th International Workshop on eXplainable Knowledge Discovery in Data Mining

6th International Workshop on eXplainable Knowledge Discovery in Data Mining

Calendar31 May 2024

EMERGE partners from UNIPI are organising the workshop during the next European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD 2024), to be held in Vilnius, Lithuania, on September 13th, 2024.

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Publication: Edge of Stability Echo State Network

Publication: Edge of Stability Echo State Network

Calendar29 May 2024

In this work, EMERGE partners from the University of Pisa introduce a new ESN architecture called the Edge of Stability ESN to bring together the fading memory property and the ability to retain as much memory as possible.

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Publication: Hedonic valence at the core of consciousness: A review of “A philosophy for the science of animal consciousness” by Walter Veit

Publication: Hedonic valence at the core of consciousness: A review of “A philosophy for the science of animal consciousness” by Walter Veit

Calendar23 May 2024

In this work, EMERGE partners from the Ludwig Maximilian University of Munich, discuss the main original contributions of Walter Veit’s “A Philosophy for the Science of Animal Consciousness”.

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Publication: Co-perceiving: Bringing the social into perception

Publication: Co-perceiving: Bringing the social into perception

Calendar06 May 2024

Humans and other animals possess the remarkable ability to discern which objects and spaces are perceived by others and which remain private to themselves. In this comprehensive review, EMERGE partners from the Ludwig Maximilian University of Munich advocate for a broader and more mechanistic understanding of this phenomenon, termed co-perception.

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Publication: Quasi-Metacognitive Machines: Why We Don’t Need Morally Trustworthy AI and Communicating Reliability is Enough

Publication: Quasi-Metacognitive Machines: Why We Don’t Need Morally Trustworthy AI and Communicating Reliability is Enough

Calendar03 May 2024

In this work, EMERGE partners from the Ludwig Maximilian University of Munich argue that developing morally trustworthy AI is not only unethical, as it promotes trust in an entity that cannot be trustworthy, but it is also unnecessary for optimal calibration.

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