June 7, 2024, 4:43 a.m. | Edward Hughes, Michael Dennis, Jack Parker-Holder, Feryal Behbahani, Aditi Mavalankar, Yuge Shi, Tom Schaul, Tim Rocktaschel

cs.LG updates on arXiv.org arxiv.org

arXiv:2406.04268v1 Announce Type: new
Abstract: In recent years there has been a tremendous surge in the general capabilities of AI systems, mainly fuelled by training foundation models on internetscale data. Nevertheless, the creation of openended, ever self-improving AI remains elusive. In this position paper, we argue that the ingredients are now in place to achieve openendedness in AI systems with respect to a human observer. Furthermore, we claim that such open-endedness is an essential property of any artificial superhuman intelligence …

abstract ai systems artificial arxiv capabilities cs.ai cs.lg data ever foundation general improving intelligence open-endedness paper superhuman systems training type

Senior Data Engineer

@ Displate | Warsaw

Principal Architect

@ eSimplicity | Silver Spring, MD, US

Embedded Software Engineer

@ Carrier | CAN03: Carrier-Charlotte, NC 9701 Old Statesville Road, Charlotte, NC, 28269 USA

(USA) Software Engineer III

@ Roswell Park Comprehensive Cancer Center | (USA) CA SUNNYVALE Home Office SUNNYVALE III - 840 W CALIFORNIA

Experienced Manufacturing and Automation Engineer

@ Boeing | DEU - Munich, Germany

Software Engineering-Sr Engineer (Java 17, Python, Microservices, Spring Boot, REST)

@ FICO | Bengaluru, India