AI Bibliography
AI Bibliography |
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Kott, A., Choi, K., Forch, B., Franaszczuk, P., Karna, S., & Lee, S., et al.. (2018). Potential science and technology game changers for the ground warfare of 2050: Selected projections made in 2017. US Army Research Laboratory. |
| Resource type: Book BibTeX citation key: Kott2018 View all bibliographic details  |
Categories: Artificial Intelligence, Biological Science, Complexity Science, Computer Science, Data Sciences, Decision Theory, Engineering, General, Geopolitical, Military Science Subcategories: 5G, Big data, Chaos theory, China, Cloud computing, Cognitive Electronic Warfare, Command and control, Cyber, Decision making, Military research, Quantum computing, Systems theory, United States Creators: Choi, Forch, Franaszczuk, Karna, Kott, Lee, Mait, others, Reynolds, Sadler, Swami Publisher: US Army Research Laboratory Collection: |
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| Abstract |
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This report, written by the members of the Strategic Projections Committee of the US Army Research Laboratory ARL, is a think piece. Its intent is to offer the Army community the thoughts of ARL scientific and technology professional level scientists on the likely breakthroughs in science and technology that may occur between now and 2050 and have the potential to be game changers for ground warfare in 2050 and beyond. This report will be followed by more reports of such nature, possibly on an annual basis. The subsequent reports might offer different projections or update those already discussed. In effect, it is a living document that is not intended to offer arguments or recommendations for programmatic investments or priorities. It touches on the following topics artificial cells algorithms that will enable creation of seeing skins for high resolution, 3-D imaging IR sensors that would be dramatically smaller, cheaper, and more sensitive and multifunctional than what is available today ways to measure, distribute, and exploit quantum entanglement self-healing, self-protecting, and other such networks brain-to-brain and brain-to-artificial-intelligence interfaces integration of neuroscience and conventional computing and Complexity Science that will enable new methods to anticipate and mitigate failures.
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