Intelligence Analytics Summit 2020 will focus on covering; large scale data collection and validation, real time actionable intelligence exchange and creating a cross-services and cross-allies unified language as well as looking at the latest technologies supporting Intelligence Analytics including Artificial Intelligence and Deep Learning Systems.
Join us for the opportunity to develop and challenge what you know, discuss the burning topics in the intelligence community and take an active part in delivering solutions and generating cooperation opportunities.
Innovation can and does occur in Bill Hewlett’s garage, but ultimately you need a production-strength ISO 9001 factory. This is also true for high performance data analysis projects. R and python are great tools for research and for science projects -- in the best sense of the word. Innovative approaches to get new analytic outcomes are crucial to address the challenge of sense-making in a complex data world.
But, once the lab project is proven to be a valuable analysis method, we must make it performant, manageable, and make it scale to work with data volumes that are meaningful for the mission, not just with experimental sample data sets. In this talk we will learn how SAP, the world’s largest Enterprise Software company, approaches the problem of managing the execution of innovative machine learning and artificial intelligence algorithms to solve hard analytical problems. We will discuss how to empower the data science team at your organization to innovate with tools they are comfortable and familiar with, yet deliver their innovation to the mission in a way that is powerful and secure.
Presentation by Bob Palmer, VP Software Solutions, SAP: NS2, National Security
Presentation by Doug Ellis, VP Global Solution Architects, Altair
Exploring alternative analytical methods that can help to circumvent the limitations posed by encryption of data
Presentation by Frederic Lemieux, Professor of the Practice and Faculty Director of the MPS in Applied Intelligence, Georgetown University
The U.S. Intelligence Community (IC), both the so-called “alphabet agencies” such as the CIA, FBI, and NSA, as well as the various intelligence components of the Department of Defense are constantly seeking to know the enemy. Whether it is to gain a strategic advantage in war, defend the homeland against foreign threats, or preventing terrorism, the IC uses every tool at its disposal to know and defeat the enemy.
The IC has numerous disciplines, collection methods, and tools that cumulatively collect immense amounts of raw data that it uses to piece together the enemy and their intentions. Yet there is a flaw in the system - not one due to improper practice or ignorance, but an inherent limitation in any organization. At its core, any intelligence organization is made up of and relies on people to analyze the raw data, and convert it into actionable data. This limitation is an inherent bottleneck - the amount of raw data to be analyzed is vastly disproportionate to the available manpower. This reliance on Small Data, only that which has already been analyzed by a human, limits our potential to know our adversaries.
Further, even the most studious of analysts is still imperfect. Whether you consider the effects of fatigue and being overworked, or the effects of inherent cognitive bias, or even simply overlooking crucial data, the answer remains the same. Humans simply cannot accurately analyze information on the scale increasingly needed to effectively contend with the adversaries the U.S. now faces.
It is no surprise, then, that the U.S. and its adversaries and peers around the world are increasingly looking to technological solutions to bridge this gap. In particular, there is a worldwide push to increase the use of Big Data and Artificial Intelligence (AI) for military and national security applications, especially in intelligence analysis. DOWNLOAD this in-depth report to learn more about:
In line with the guidance provided by CDC, WHO and the Federal Government we have taken the decision to postpone the Intelligence Analytics Summit that was due to take place April 7-9, 2020. As the health and safety of our attendees, speakers, sponsors and staff are our primary concern...Please keep reading