Alex Momot, Founder and CEO of REMME, shares insights on the opportunities and challenges of IoT and which direction the industry should take.
If you’ve been following technology news, you’ve probably heard of end-to-end encryption. It’s the technology that makes sure the data you send—whether it’s a file, an email, or...
Cerebras Systems CEO Andrew Feldman explains the impact of open-source large language models (LLM) on the broader AI community.
Boston University's Kate Saenko discusses explainable AI and interpreting decisions made by deep learning algorithms and neural networks.
Harvard Medical University Professor Gabriel Kreiman discusses biological and computer vision and explains what separates current AI systems from the human visual cortex.
Greg Ellis, GM of Application Security at Digital.ai, delves into the evolving landscape of machine learning security.
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.
Researchers at the University of Maryland discuss why security must be part of the machine learning research process.
Late payments and invoice management are big challenges. Read about how payment platform Accru is addressing these challenges.
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.