Everything you need to know about symbolic artificial intelligence, the branch of AI that dominated for five decades.
To create better artificial intelligence hardware, researchers have been drawing inspiration from the brain. The result is neuromorphic chips, which have grown in popularity in the past years.
Huge salaries and bonuses at tech firms are luring AI scientists away from universities. How will this artificial intelligence brain drain affect the AI industry?
Everything you need to know about artificial neural networks (ANN), the state-of-the-art of artificial intelligence that help computers solve tasks that are impossible with classic AI approaches.
This beginner’s guide to enterprise applications will tell you what they are, why they’re beneficial, and how businesses can use them in 2019.
As artificial intelligence becomes more ubiquitous in consumer applications, it must better understand human emotions. That’s where emotion AI comes in.
Training a deep learning model requires vast amounts of training data and compute resources. With transfer learning, developers can cut both on training examples and CPU costs.
From game-playing bots to robotic hands that dexterously handle objects, reinforcement learning creates AI models that requires little training data.
The fourth industrial revolution is well underway — and it's thanks to a confluence of technologies we wrote off as science fiction just a few short years ago.
In tandem with advances in artificial intelligence, there’s growing interest in establishing ethical guidelines and standards to weigh the robustness and trustworthiness of the AI algorithms that are helping or replacing humans in making important and critical decisions.