Search Results for: defense

As we've done with our article on AI at the top 5 US defense contractors, this report discusses the artificial intelligence initiatives at the top four military defense contractors of Israel by revenue. Although Israel is a nation just 70 years old, it possesses one of the most modern militaries in the world.

Due to the popularity of our recent report on AI at the top 5 US defense contractors, we decided to broaden our scope of AI in the world's militaries. This report attempts to illuminate the current artificial intelligence projects at Europe’s largest private defense contractors.

wikiMany of the pivotal technologies utilized by the public today have their roots in military projects. The internet’s first successful message transfer was due to a U.S. Department of Defense-awarded contract in 1969 for the development of the “ARPANET project.” Global Positioning System (GPS) technology utilized in smartphones today was put in place and created in the 1970s for accurate military positioning, coordination, and tracking.

Episode Summary: This week, we're going to be talking about the defense sector. We interview Ryan Welsh, CEO of Kyndi, a company working on explainable AI. We focus specifically on the unique data challenges of the defense industry, as well as the general use case of AI in defense writ large. Many of the challenges that the defense sector has to deal with transfer to other spaces and sectors. Business leaders that deal with extremely disjointed text information, what is sometimes called "dark data," and information in various languages or different dialects, will be able to resonate with some of the unique challenges talked about in this episode, and maybe even gain some insights for how to handle them.

Event: A guest appearance at National Defense University

Date: October 24, 2018

Team Member: Daniel Faggella, Emerj CEO and Founder
What Happened
Through a variety of presentations for business and government personnel, I was put in touch with some of the leadership at the Defense Innovation Unit at the Department of Defense, which is essentially an arm of the Defense Advanced Research Projects Agency (DARPA). In talking to those folks, I was introduced to a professor at the National Defense University in Washington DC who was very interested in how to bake artificial intelligence use cases and understanding into their curriculum in order to help train military leaders on how to fruitfully leverage these technologies.

1 - Announcing SyntaxNet: The World’s Most Accurate Parser Goes Open Source

On Thursday, Google released SyntaxNet, its open-source neural network framework through TensorFlow that serves as a base building block for natural language understanding (NLU) systems. Parsing human languages has been historically challenging for computers, in big part due to the ambiguity of syntactic structures. The system's neural networks are successful in helping better train systems. In addition to a comprehensive set of code for training new SyntaxNet models on proprietary data, users also have access to 'Parsey McParseface', a machine learning-based parsing system trained to analyze English text. Parsey is the most accurate model of its kind to date, and will help further research involving automatic extraction of information, translation, and other capabilities of the NLU.

What does developing an AI strategy look like? Most executives openly embrace the technology and the automation possibilities within their organization. They may just need a bit of help getting started.

When Facebook bought Oculus in 2014 for over a billion dollars, it was an investment ahead of its time. For years virtual reality remained an interesting novelty and little more.

You don’t want the brand new shiny red sports car. 

Or that all-inclusive resort vacation to Hawaii.

As artificial intelligence makes its way into more industries and workflows, more and more non-technical team members will be charged with leading AI projects. The next wave of AI catalysts will be familiar with AI at a conceptual level (read: executive AI fluency), but will mostly be expert in bridging AI's capabilities to important business workflows and objectives.