Perspectives on Research in Artificial Intelligence and Artificial General Intelligence Relevant to DoDJASON offers the following recommendations to DoD senior leadership [documented as goals in this StratML rendition]Artificial Intelligence (AI) is conventionally, if loosely, defined as intelligence exhibited by machines. Operationally, it can be defined as those areas of R&D practiced by computer scientists who identify with one or more of the following academic sub-disciplines: Computer Vision, Natural Language Processing (NLP), Robotics (including Human-Robot Interactions), Search and Planning, Multi-agent Systems, Social Media Analysis (including Crowdsourcing), and Knowledge Representation and Reasoning (KRR). The field of Machine Learning (ML) is a foundational basis for AI. While this is not a complete list, it captures the vast majority of AI researchers.JASON_3914abf6-2046-11e9-af5d-53fcd5e8efbcJASON is an independent group of elite scientists which advises the United States government on matters of science and technology, mostly of a sensitive nature. https://en.wikipedia.org/wiki/JASON_(advisory_group) The MITRE CorporationDepartment of Defense Research and Engineering EnterpriseThis JASON study was sponsored by DoD/OSD/ASD(R&E). AI technologies are of great importance to DoD missions. Defense systems and platforms with varying degrees of autonomy already exist. More importantly, AI is seen as the key enabling technology (along with human-computer interactions of various kinds) of a “Third Offset Strategy” that seeks for the U.S. a unique, asymmetric advantage over near-peer adversaries._3914adb8-2046-11e9-af5d-53fcd5e8efbcTo make recommendations to DoD for investment in AI_3914ae6c-2046-11e9-af5d-53fcd5e8efbcTracking & InvestmentTrack and invest in the most dynamic and rapidly advancing areas of AI_3914af0c-2046-11e9-af5d-53fcd5e8efbc1AI CadreDoD should both track (via a knowledgeable cadre) and invest in (via a 6.1 research portfolio) the most dynamic and rapidly advancing areas of AI, including, but by no means limited to DL._3914aff2-2046-11e9-af5d-53fcd5e8efbcAI EngineeringDevelop a discipline of AI engineering_3914b092-2046-11e9-af5d-53fcd5e8efbc2DoD should support the development of a discipline of AI engineering, accelerating the progress of the field through Shaw’s “craft” and (empirical) “commercial” stages.illitiesAdvance the “illities”_3914b128-2046-11e9-af5d-53fcd5e8efbc2.1A particular focus should be advancing the “illities” in support of DoD missions. [Editor's note: "The ilities are desired properties of systems, such as flexibility or. maintainability (usually but not always ending in “ility”) that often manifest themselves. after a system has been put to initial use." https://pdfs.semanticscholar.org/c472/ee5117ae6034a8653bb289630352ab86d6f8.pdf]Augmented IntelligenceFocus investment on human augmentation via AI_3914b1c8-2046-11e9-af5d-53fcd5e8efbc3DoD’s portfolio in AGI should be modest and recognize that it is not currently a rapidly advancing area of AI. The field of human augmentation via AI is much more promising and deserves significant DoD support.AGIInvest modestly in AGI_3914b268-2046-11e9-af5d-53fcd5e8efbc3.1Artificial General Intelligence (AGI) is a research area within AI, small as measured by numbers of researchers or total funding, that seeks to build machines that can successfully perform any task that a human might do. Where AI is oriented around specific tasks, AGI seeks general cognitive abilities. On account of this ambitious goal, AGI has high visibility, disproportionate to its size or present level of success, among futurists, science fiction writers, and the public.Data Curation & LabelingCurate and label mission-related data sets_3914b312-2046-11e9-af5d-53fcd5e8efbc4DoD should support the curation and labeling, for research, of its unique mission-related large data sets. Operational DataSave operational data for future research_3914b3d0-2046-11e9-af5d-53fcd5e8efbc4.1Wherever possible, operational data should be saved for future research use in support of AI for DoD-unique missions.ResourcesProvide resources for researchers_3914b47a-2046-11e9-af5d-53fcd5e8efbc5AI ResearchersDoD should create and provide centralized resources for its intramural and extramural researchers (MOSIS-like), including labeled data sets and access to large-scale GPU training platforms.Data SetsProvide labeled data sets_3914b75e-2046-11e9-af5d-53fcd5e8efbc5.1GPU Training PlatformsProvide access to GPU training platforms_3914b812-2046-11e9-af5d-53fcd5e8efbc5.2Embedded DevicesSurvey embedded devices for potential breakthrough applications of AI_3914b93e-2046-11e9-af5d-53fcd5e8efbc6DoD should survey the mission space of embedded devices for potential breakthrough applications of AI, and should consider investing in special-purpose accelerators to support AI inference in embedded devices for DoD missions if such applications are identified.Special-Purpose AcceleratorsInvest in special-purpose accelerators to support AI inference in embedded devices for DoD missions_3914b9f2-2046-11e9-af5d-53fcd5e8efbc6.12017-01-312019-01-24https://fas.org/irp/agency/dod/jason/ai-dod.pdfOwenAmburOwen.Ambur@verizon.net