Cybersecurity is one of the most fluid and changing fields of the tech industry. Every year, new threats and challenges emerge, outpacing past records and expectations. In this respect 2016 was no different. But as...
As Artificial Intelligence evolves from myth and buzzword into a reality that permeates every aspect of our lives, much speculation is made over what the future challenges will be. Among them is the effect of...
DARPA's XAI initiative aims to shed light inside the black box of artificial intelligence algorithms. Project Manager Dave Gunning explains how the agency is working to create explainable AI tools that will build trust and reliability into AI models.
The team behind IBM's RoboRXN platform explains how AI, robotics, and the cloud can change the future of drug and chemicals research.
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.
Philips's Tina Manoharan on AI research in health care and the challenges of applying AI in real-world health applications.
Artificial intelligence provides a unique opportunity to give back the gift of time to doctors and patients.
In his book Augmented Mind, Alex Bates argues that the real opportunities of AI lie in augmenting humans, not replacing them.
Nenshad Bardoliwalla, chief product officer at DataRobot, discusses challenges machine learning in different sectors and how no-code platforms are helping democratize AI.
Harvard Medical University Professor Gabriel Kreiman discusses biological and computer vision and explains what separates current AI systems from the human visual cortex.