| dc.contributor.author | Donati, E | |
| dc.contributor.author | Payvand, M | |
| dc.contributor.author | Indiveri, G | |
| dc.contributor.author | Debacker, P | |
| dc.contributor.author | Furber, Steve | |
| dc.contributor.author | Sandamirskaya, Yulia | |
| dc.contributor.author | Schmuker, Michael | |
| dc.contributor.author | Bartolozzi, Chiara | |
| dc.contributor.author | Spiga, Sabina | |
| dc.contributor.author | Bortolotti, Paolo | |
| dc.contributor.author | Mizrahi, A | |
| dc.date.accessioned | 2020-06-19T00:08:39Z | |
| dc.date.available | 2020-06-19T00:08:39Z | |
| dc.date.issued | 2020-06 | |
| dc.identifier.citation | Donati , E , Payvand , M , Indiveri , G , Debacker , P , Furber , S , Sandamirskaya , Y , Schmuker , M , Bartolozzi , C , Spiga , S , Bortolotti , P & Mizrahi , A 2020 , ' Neuromorphic technology in Europe : Brain-inspired technologies are advancing apace across Europe and are poised to help accelerate the AI revolution ' , The Innovation Platform , no. 2 , pp. 140–143 . < https://www.innovationnewsnetwork.com/publication/the-innovation-platform-issue-02/ > | |
| dc.identifier.issn | 2634-0208 | |
| dc.identifier.uri | http://hdl.handle.net/2299/22882 | |
| dc.description | © 2020 The Author. | |
| dc.description.abstract | By taking loose inspiration from the brain, artificial neural network algorithms have made tremendous progress in artificial intelligence. However, to unlock significant gains in terms of novel real-world capabilities, performance and efficiency, a more ambitious step needs to be taken: to develop a new technology that emulates neural computation directly at the hardware level. The NEUROTECH network presents its vision of these ‘neuromorphic’ technologies and their innovative potential in Europe. | en |
| dc.format.extent | 4 | |
| dc.format.extent | 220726 | |
| dc.language.iso | eng | |
| dc.relation.ispartof | The Innovation Platform | |
| dc.title | Neuromorphic technology in Europe : Brain-inspired technologies are advancing apace across Europe and are poised to help accelerate the AI revolution | en |
| dc.contributor.institution | Centre of Data Innovation Research | |
| dc.contributor.institution | School of Physics, Engineering & Computer Science | |
| dc.contributor.institution | Department of Computer Science | |
| dc.contributor.institution | Biocomputation Research Group | |
| dc.description.status | Non peer reviewed | |
| dc.identifier.url | https://www.innovationnewsnetwork.com/publication/the-innovation-platform-issue-02/ | |
| rioxxterms.type | Journal Article/Review | |
| herts.preservation.rarelyaccessed | true | |
