AI etc.

Inside the FactMiners' Brain - Rainman Meet Sherlock

NOTE: In case you missed it, here is a link to a screencast of Kenny Bastani's webinar about using the Neo4j graph database in text classification and related Deep Learning applications. It's a fascinating introduction to some original work Kenny is doing that leverages the strengths of a property graph, in this case Neo4j, to do some Deep Learning text-mining and document classification.

Karma to Take a LOD off FactMiners

Collage of photos of Karma is an amazing Open Source "multilingual" ontology-aware cross-model smart-mapper

Karma is an amazing Open Source "multilingual" ontology-aware cross-model smart-mapper providing "Rosetta Stone"-like powers to users coping with the ever-shifting publication of Linked Open Data (LOD). Karma is the evolving brilliant work from the incredible minds of the researcher-makers of the Information Sciences Institute at the University of Southern California. Karma will likely handle this critical component of the technology stack that implements the FactMiners social-game ecosystem.

A Quick Trip to the Stanford Vision Lab

Fei-Fei Li is the director of the Computer and Human Vision Lab within the legendary Stanford Artificial Intelligence Laboratory. While her research interests and breakthrough contributions to the field are wide-ranging, I want to focus briefly on a 2009 study she and her colleagues did at Princeton, before Dr. Li's selection to head the prestigious Stanford Vision Lab.

Finding the 'CV' in 'STEM' at the British Library Image Collection

Computer Vision, or using its popular acronym 'CV', is a domain of scientific knowledge and practice within the domain of Artificial Intelligence which is part of the broad domain of Computer Science. CV is a particularly challenging field that has strong connections into each of the Science, Technology, Engineering, and Math 'branches' of the STEM fields of education.

Introducing the 'Seeing Eye Child' Robot Adoption Agency

The 'Seeing Eye Child' Robot Adoption Agency is similar to the 'Tamagotchi' or 'digital pet' gaming phenomena that hit in the mid-1990's and is still going strong. The difference here is that we harness our little cognitive learning machines – AKA FactMiners game players – to 'adopt' a robot (AKA a machine-learning program with some form of vision – image intake and analysis – capability) and help it to learn to see and understand its world. As an adoptive 'Seeing Eye Child', players take on the roles of coach and referee for training sessions where adopted robots learn to see what's in the British Library images.

A FactMiners' Fact Cloud for the British Library Image Collection

I was thrilled to read the announcement this week in the British Library Digital Scholarship blog about the Library's uploading to the Flickr Commons of over 1 million Public Domain images scanned from 17th, 18th, and 19th century books in the Library's physical collections. The Flickr image collection makes the individual images easily available for public use.

Subscribe to RSS - AI etc.