EARLY AI ADOPTERS

Google: Gmail has used machine learning techniques to filter emails since its launch 18 years ago. Today, there are applications of machine learning in almost all of its services, especially through deep learning, which allows algorithms to do more independent adjustments and self-regulation as they train and evolve.

“Before we were in a world where the more data you had, the more problems you had. Now with deep learning, the more data the better. Elie Bursztein, head of anti-abuse research team at Google

IBM/Watson: The team at IBM has increasingly leaned on its Watson cognitive learning platform for “knowledge consolidation” tasks and threat detection based on machine learning.

“A lot of work that’s happening in a security operation center today is routine or repetitive, so what if we can automate some of that using machine learning?” – Koos Lodewijkx, vice president and chief technology officer of security operations and response at IBM Security.

Juniper Networks: The networking community hungers for disruptive ideas to address the unsustainable economics of present-day networks. Juniper sees the answer to this problem taking shape as a production-ready, economically feasible Self-Driving Network™.

“The world is ready for autonomous networks. Advances in artificial intelligence, machine learning, and intent-driven networking have brought us to the threshold at which automation gives way to autonomy.” Kevin Hutchins, Sr. VP of strategy and product management.

Balbix BreachControl (now called Balbix Security Cloud) platform uses AI-powered observations and analysis to deliver continuous and real-time risk predictions, risk-based vulnerability management and proactive control of breaches. The platform helps make cybersecurity teams more efficient and more effective at the many jobs they must do to maintain a strong security posture – everything from keeping systems patched to preventing ransomware.