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Diffeo Event
AI <> Tradecraft Forum
Event Date: March 13, 2019
Hosted By: Diffeo's Second Annual AI Tradecraft Forum
Location: Arlington, VA
Hosted By: Diffeo's Second Annual AI Tradecraft Forum
Location: Arlington, VA
Thought Leader Presentations (All Day):
| Dr. Pat Biltgen | Author of Activity Based Intelligence |
| David J. Gauthier, Director, Commercial and Business Operations Group, NGA Source | “Reaching all the data for GEOINT” |
Patricia Guitard*, Senior OSINT Consultant, US INSCOM | “OSINT challenges, successes and the road ahead.” |
Hannah MacKenzie-Margulies, Product Manager, Basis Technology, Rosette Text Analytics | "Multi-lingual analytics for open source and dirty data." |
| Andrew E. Newton, Technical Director, J2, US CYBERCOM, | “To index or not to index? That is the data lake question.” |
| Robert Shelton, Jr., CTO, Microsoft Federal | “How AI and continuous monitoring affect force protection.” |
Dr. Ian Soboroff, Group Leader, Retrieval Group, Information Access Division | “TREC: measuring the effectiveness of information analytics.” |
Fred Waugh*, Program Manager, MIT Lincoln Labs | "Assessing AI Capabilities." |
*invited
Hands-On Workshops (Afternoon):
- Open Source Web Research: Hands-On Tradecraft and Tools
- Focusing on the countries of India and Russia, Diffeo’s analyst team will teach the latest PAI exploitation techniques to research foreign government interest in critical DoD supply chains and political leadership goals.Tools include: managed attribution with Authentic8/Toolbox, Recordedfuture, Basis multi-lingual analytics, and more.
- Machine Learning Tutorial: Python Vector Embeddings for Entity-Entity Relations
- Diffeo’s machine learning team will provide a hands-on tutorial based in an iPython notebook adapted from our colleague Sameer Singh’s tutorial on vector embeddings for entity-to-entity relations. This clever use of matrix factorization combines unstructured documents with relations from a structured knowledge base to create dense vectors that encode the semantic meaning of relationships.
Resources
Case Study
While data creation and accessibility has grown dramatically, our ability to consume and utilize that data has not kept up. Humans are limited by time and language skills; however, full automation is not an option as machines lack the intuition and broader understanding of research goals that a huma...
Resource
Interview with Geoffrey Milstein, VP Public Sector of Diffeo at 2017 GeoINT.
Di eo’s mission is to help people organize the world’s information by accelerating surprises. Interactive
machine learning helps intelligence analysts rapidly traverse and develop knowledge graphs. The uid
interaction between humans and machines enables users to quickly uncover relationships ...
Discover unknown unknowns in unstructured text by rapidly assembling networks of entities
with help from Di eo’s active learning algorithms for large-scale entity disambiguation. As you
take note of interesting relationships, the machine-in-the-loop learns which entities you are
studying and su...
Discover unknown unknowns in unstructured text by rapidly assembling networks of entities
with help from Di eo’s active learning algorithms for large-scale entity disambiguation. As you
take note of interesting relationships, the machine-in-the-loop learns which entities you are
studying and su...
Whitepaper
Even with the progress that has been made sorting and analyzing massive volumes of data, much
remains to be gained by infusing the sorting, discovery & analysis process with active machine
intelligence. Most agencies rely on text analytics and big data algorithms, and yet, those tools stop
short ...