News

Teaching Machines How to Spell Will Help Catch Terrorists – Defense One

07 April 2014

The Boston Marathon bomber Tamerlan Tsarnaev could have been caught before his attack if only his name had been properly matched to a terrorist watch list.

In a Defense One byline, Basis Technology VP of Engineering David Murgatroyd outlines how more robust software can match names with spelling variations as well as tackle other information processing problems faced by security agencies.

While the system that failed to identify Tsarnaev is classified, we can learn from public examples about how they work. Murgatroyd takes the example of IBM’s Watson on Jeopardy. Despite an overall impressive performance, Watson answered “Toronto” to a question in the category “U.S. Cities.” Using 200 million pages of content via 90 powerful servers, Watson stumbled not on compiling a list of potential answers, but on removing one answer that most humans would instantly know to be false.

This might seem like a minor example, but as Murgatroyd writes “when we move beyond game shows to stopping terrorists, curious errors can have fatal consequences.”

Read the full article in Defense One.

autopsy

世界で最も多く利用されている簡単操作のオープンソース・デジタルフォレンジックツール

Learn More
cyber-triage

実用的、自動的、エージェントレスなエンドポイントレスポンス

Learn More
rosette

Natural language understanding for enterprise applications

Do even more with Rosette

Relationship Extraction · Sentiment Analysis

Categorization

Learn More
autopsy

The premier open source platform for forensic investigators and tool developers

Learn More
cyber-triage

Practical, automated, agentless endpoint response

Learn More
konasearch

Salesforce search that works

Learn More