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Machine Learning for Navy Applications...Machine Learning for Navy Applications NDIA Fall Defense...
Transcript of Machine Learning for Navy Applications...Machine Learning for Navy Applications NDIA Fall Defense...
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Machine Learning for Navy Applications
NDIA Fall Defense and Industry Forum 24 October 2017
Dr. Katie Rainey SPAWAR Systems Center Pacific
[email protected] Distribution A: Unlimited Distribution
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Machine learning is critical to SPAWAR’s strategic vision
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http://www.public.navy.mil/spawar/News/Pages/StrategicVision.aspx
“[The] era of precision and observation is giving way to an era of competition for decision. The sensors are now omnipresent, the positioning information is embedded, so now the competition is to orienting, finding a way through that information, and making a decision.” CNO Admiral Richardson, Naval War College, June 2017
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Machine Learning at SSC Pacific
Data Analytics
Bio-Inspired Systems
Computer Vision Autonomous Systems
Cyber Autonomy
Supervisory Autonomy
Machine Learning Center of Excellence
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What makes machine learning hard for the Navy?
1. Data 2. Computing Environment 3. Trust
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Navy data is noisy, sparse, and unstructured
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Chinese aircraft carrier in South China Sea. DigitalGlobe
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Navy data is noisy, sparse, and unstructured
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Vehicles in desert environment. DVIDS
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Navy data is noisy, sparse, and unstructured
12/1/2009
Easier Hard
Fisher’s Iris dataset. Wikipedia Service outage heat map.
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What makes machine learning hard for the Navy?
1. Data 2. Computing Environment 3. Trust
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The Navy has challenging computing environments
▼ Disconnected, Intermittent, and Limited (DIL) environments ▼ Legacy systems ▼ Data silos ▼ Multiple classification domains ▼ Unique human-machine interface requirements
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DVIDS
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What makes machine learning hard for the Navy?
1. Data 2. Computing Environment 3. Trust
12/1/2009 10 Distribution A: Unlimited Distribution
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Trust in the system is at least as important as the system itself
▼ Human-in-the-Loop vs Human-on-the-Loop ▼ Consequences when system is wrong ▼ Understandable failure ▼ Ethics of automation
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When exploring machine learning for Navy applications...
▼ Use representative data ▼ Consider the system’s capabilities and limitations ▼ Remember the user
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Workshop on Naval Applications of Machine Learning 2018
▼ 13-15 February, 2018, San Diego, California Tentatively: two days S&T focused, one day operationally focused Short technical talks and poster sessions Dr. Guna Seetharaman (ST, NRL) scheduled as keynote speaker Panel discussions on collaboration efforts / other topics Potential for classified sessions / meetings
▼ Open to government, industry, academia ▼ Now accepting abstracts until Nov. 12, 2017
Email [email protected] for more info
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THANK YOU
Dr. Katie Rainey SPAWAR Systems Center Pacific [email protected]
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