Some self-driving cars can’t tell the difference between a person in the roadway and an image projected on the street. A team of researchers used projectors to trick semiautonomous vehicles into detecting people, road signs, and lane markings that didn’t exist.

In an online dating profile, the photo that highlights your physical beauty may not be the one that makes you look smart or honest — also important traits in a significant other. A new neural network helps pick the most appealing shots.

Female giant pandas are fertile for only 24 to 36 hours a year: Valentine’s Day on steroids. A new neural network alerts human keepers when a panda couple mates.

Robots are moving into a job that traditionally required the human touch.What’s new: A commercial warehouse that ships electrical supplies deployed AI-driven robotic arms from Covariant, a high-profile Silicon Valley robotics firm.

Can machine learning help address the scourge of opioid addiction? A public health researcher developed a neural network that spots sellers of opioids on social media, Recode reported.

End-to-end backpropagation and labeled data are the peanut butter and chocolate of deep learning. However, recent work suggests that neither is necessary to train effective neural networks to represent complex data.

Softmax commonly computes probabilities in a classifier’s output layer. But softmax isn’t always accurate in complex tasks — say, in a natural-language task, when the length of word vectors is much smaller than the number of words in the vocabulary.

Artificial intelligence was everywhere at the biggest, buzziest consumer-technology showcase in the U.S. AI ruled the convention floor at the annual Consumer Electronics Show in Las Vegas, as numerous media outlets proclaimed.

Computer vision has potential to spot cancer earlier and more accurately than human experts. A new system surpassed human accuracy in trials, but critics aren’t convinced.

Researchers aiming to increase accuracy in object detection generally enlarge the network, but that approach also boosts computational cost. A novel architecture sets a new state of the art in accuracy while cutting the compute cycles required.

How is it that many people learn to drive a car fairly safely in 20 hours of practice, while current imitation learning algorithms take hundreds of thousands of hours, and reinforcement learning algorithms take millions of hours? Clearly we’re missing something big.

Many people in the AI community focus on achieving flashy results, like building an agent that can win at Go or Jeopardy. This kind of work is impressive in terms of complexity.

The previous state-of-the-art image classifier was trained on the ImageNet dataset plus 3.5 billion supplemental images from a different database. A new method achieved higher accuracy with one-tenth as many supplemental examples — and they were unlabeled, to boot.

Sophisticated models trained on biased data can learn discriminatory patterns, which leads to skewed decisions. A new solution aims to prevent neural networks from making decisions based on common biases.

Image analysis guided by AI revealed a 2,000-year-old picture dug into the Peruvian desert. Researchers analyzing aerial imagery shot over Peru found a pattern that looks like a three-horned humanoid holding a staff.