Introduction of Pervasive AI Driven Bioinformetrics for SaaS Applications

What is a new way of user identification? Do people still need passwords or fingerprints to access their accounts?

In this presentation at the Glorium Technologies virtual summit, Patrick Nunally, a Chief Technology Officer at Blockchain Exchange Network (BEN), tells about a new approach to creating a “life print” of a user’s activity.

Each person’s behavior is a set of repeating patterns that allow AI to identify them quickly. Machine learning in bioinformatics uses the data like the voice, walking gait, and places the person attends.

“We don’t need users to identify themselves. We just need them to be themselves”.

Topic – Introduction of Pervasive AI Driven Bioinformetrics for SaaS Applications

• Mobile 3.0 requires native uninterrupted user identification
• Bioinformetrics fuse sensor streams into a single native biometric
• How does Bioinformetrics work?
• Bioinformetrics development and testing status
• Bioinformetrics changes security dynamics

About speaker

Dr. Nunally is an internationally recognized innovator that has been pioneering AL/ML technologies for over 30 years. As the head of signal processing for General Dynamics he co-founded the cognitive processing center with Hopfield and Mead. His career has largely focused on the application of core AI/ML technologies to wireless, internet of things, cryptographic security, and network systems applications. With over 120 granted patents, Dr. Nunally has been consistently successful in creating/launching industry changing systems and service and his accomplishments have led to recognition by the Institute of Electrical and Electronics Engineers’ Eta Kappa Nu, The National Academy of Television Arts & Sciences, and he has been twice recognized nationally as the IEEE Eta Kappa Nu’s most outstanding engineer of the year and was awarded a Technical Emmy 2009 for his Arbitron Portable People Meter.

You can get the full recording of the virtual summit «Boosting SaaS products with new technologies. Big Data. Data Science. Artificial Intelligence. Machine Learning» here.