| dc.contributor.author | Zewe, Adam | |
| dc.date.accessioned | 2023-12-18T18:43:36Z | |
| dc.date.available | 2023-12-18T18:43:36Z | |
| dc.date.issued | 2023-12-05 | |
| dc.identifier.uri | https://hdl.handle.net/1721.1/153196 | |
| dc.description.abstract | Researchers from MIT and ETH Zurich have developed a new, data-driven machine-learning technique that could be applied to many complex logistical challenges, such as package routing, vaccine distribution, and power grid management. | en_US |
| dc.language.iso | en_US | en_US |
| dc.publisher | MIT News | en_US |
| dc.rights | Attribution-NoDerivs 3.0 United States | * |
| dc.rights | Attribution-NoDerivs 3.0 United States | * |
| dc.rights.uri | http://creativecommons.org/licenses/by-nd/3.0/us/ | * |
| dc.subject | Artificial Intelligence | en_US |
| dc.title | AI Accelerates Problem-solving in Complex Scenarios | en_US |
| dc.type | Article | en_US |
