Friday, 18 October 2019

Artificial intelligence needs the speed of light

The Physics department of UniTrento is working on all-optical devices for machine learning. The work is part of the Pelm project, whose objectives include the development of a cancer monitor

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A non-invasive cancer monitor capable of monitoring the evolution of cancer tissues and therefore to provide information on the progress of the disease and the efficacy of the treatment.

That is one of the devices that will be developed within Pelm, the research project coordinated by the University of Trento that received almost 1 million euro funding over a period of three years by the Ministry of Education, universities and research as a Research project of national relevance (Prin).

Coordinated by Lorenzo Pavesi of the Nanoscience laboratory of the Department of Physics of the University of Trento, the project uses light to build innovative all-optical platforms for artificial intelligence.

Machine learning processes, with which machines recognize images, understand human voice and carry out other basic tasks, have relied so far on microelectronic circuits and microprocessors stored on devices. These circuits are not efficient enough for artificial intelligence applications, use too much energy and this limits their use.

The purpose of Pelm is to modify the notion of circuit to create energy-efficient, fast and non-invasive devices.

The press release contains comments by professor Lorenzo Pavesi, coordinator of Pelm.

The project
Pelm stands for “Photonic Extreme Learning Machine: from neuromorphic computing to universal optical interpolant, strain gauge sensor and cancer morphodynamic monitor".
The project was launched on 10 and 11 October at Polo Ferrari in Povo with a meeting of researchers from the University of Trento (Department of Physics, Nanolab), which is the national coordinator, La Sapienza University in Rome, Scuola Normale Superiore in Pisa, Università Cattolica del Sacro Cuore in Rome, and Cnr-Ino in Naples.
The kickoff meeting provided the teams with the opportunity to talk about the project, its objectives and working methodology to achieve the desired results.