Greg Ellis, GM of Application Security at Digital.ai, delves into the evolving landscape of machine learning security.
GoPractice CEO and founder Oleg Yakubenkov discusses how he created a unique product management simulator course.
IBM Watson's CTO describes the opportunities, prospects and challenges that lie ahead for artificial intelligence–powered chatbots
Nenshad Bardoliwalla, chief product officer at DataRobot, discusses challenges machine learning in different sectors and how no-code platforms are helping democratize AI.
Researchers at the University of Maryland discuss why security must be part of the machine learning research process.
Deep learning and neural networks are becoming increasingly accurate at performing complicated tasks. But are they robust as well. Researchers at MIT-IBM Watson AI Lab have developed methods to evaluate the robustness of neural networks against adversarial examples.
The team behind IBM's RoboRXN platform explains how AI, robotics, and the cloud can change the future of drug and chemicals research.
Cerebras Systems CEO Andrew Feldman explains the impact of open-source large language models (LLM) on the broader AI community.
Neuroscientist Daeyeol Lee discusses different modes of reinforcement learning in humans and animals, AI and natural intelligence, and future directions of research.
Unfortunately, it is fair to say that the vulnerabilities of Internet of Things (IoT) are preceding its innovations and utilities. From the hacking of the Ukraine power grid, to last year’s DDoS attack against the...