That's the principle underpinning "lazy robotics," a field of study championed by René van de Molengraft, a professor at Eindhoven University of Technology in the Netherlands. He believes that teaching all kinds of robots to be "lazier" with their data could help pave the way for machines that are better at interacting with things in their real-world environments, including humans. Essentially, the more efficient a robot can be with information, the better. Van de Molengraft's lazy robotics is just one approach researchers and robotics companies are now taking as they train their robots to complete actions successfully, flexibly, and in the most efficient manner possible. Teaching them to be smarter when they sift through the data they gather and then de-prioritize anything that's safe to overlook will help make them safer and more reliable--a long-standing goal of the robotics community.

The fear that robots are taking over the world might not be that far-fetched. While artificial intelligence is praised for its responsiveness to expansive amounts of information, AI seems to be absorbing biases, too. An experiment published in June demonstrated that robots trained with artificial intelligence exhibited racism and sexism in their decision-making. While sorting through billion of images, robots in this experiment routinely categorized Black men as "criminals." Similarly, the label "homemaker" was given to women more regularly than it was given to men.

Most autonomous vehicle manufacturers incorporate high-end 3D LiDARs, along with additional sensors, into their vehicles so that they are provided with enough data to fully understand their surroundings and operate safely. Yet in April 2019, Elon Musk famously told attendees at Tesla's Autonomy Day that LiDAR is a "fool's errand"--and that anyone relying on it is "doomed," referring to Tesla's preference for vision-based perception. The LiDAR / vision debate continues to this day. But since that time there has been a steadily increasing emphasis on cameras and computer vision in the autonomous vehicle market. Vision-based Navigation for AMRs Recently, the same debate has emerged in the mobile robot market where traditional 2D LiDARs have been the prevailing navigation sensor for decades. Some AMR manufacturers, including Canvas Technology (acquired by Amazon), Gideon Brothers, and Seegrid, have already developed AMRs with varying degrees of vision-based navigation.

Natural language processing (NLP) has taken great strides recently--but how much does AI understand of what it reads? Less than we thought, according to researchers at USC's Department of Computer Science. In a recent paper Assistant Professor Xiang Ren and Ph.D. student Yuchen Lin found that despite advances, AI still doesn't have the common sense needed to generate plausible sentences. "Current machine text-generation models can write an article that may be convincing to many humans, but they're basically mimicking what they have seen in the training phase," said Lin. "Our goal in this paper is to study the problem of whether current state-of-the-art text-generation models can write sentences to describe natural scenarios in our everyday lives." Specifically, Ren and Lin tested the models' ability to reason and showed there is a large gap between current text generation models and human performance.

Robots often get a bad rap. "There's an impression that they're much more capable than they really are," says Catie Cuan. Whether it's a fear that "robots are coming for my job" or "robots are coming to kill me," Cuan believes those ideas are largely driven by how robots are portrayed in fiction and storytelling. Cuan is actively working to change how the public perceives robots. But what does that have to do with dance?

Sensor research could open doors to an array of interesting applications.

How do you get machines to perform better? Tell them they could croak at any minute. In a new paper from the University of Southern California, scientists say that "in a dynamic and unpredictable world, an intelligent agent should hold its own meta-goal of self-preservation." Lead researcher Antonio Damasio is a luminary in the field of intelligence and the brain. In his profile at the Edge Foundation, they say Damasio "has made seminal contributions to the understanding of brain processes underlying emotions, feelings, decision-making and consciousness."

Way back in 1942, futurists like Isaac Asimov were already giving thought to the risks of emerging technologies, especially autonomous ones. It was during that year that Asimov wrote a short story entitled "Runaround" in which he unveiled the three laws of robotics. The key theme for these laws was that a robot could not through action or inaction allow harm to come to humans. Over the years both philosophers and writers have examined these laws in myriad ways showing the loopholes in the language and the challenges that can arise in edge cases. Regardless, the principles seem like the sort of thing we'd want if robots walked among us.

When our chief executive, Arthur Sadoun, announced that we were going to stash one year's awards cash to fund Marcel's creation, many a jaw dropped. But while we all wait with bated breath for Marcel's first whispers, the project is already a success. We're on a journey to see how AI can grapple with the complexities of a multinational organisation, where the ultimate product is human creativity. We know we can leverage our creative resources better, it's just way too complex and nuanced to perform through more mechanistic, cruder tools. On day one, we were already learning.

They're going to take your job and destroy your life – and there's nothing you can do about it. That's the hype: we are facing a dystopian future in which human labour is about to be rendered obsolete. The announcement last week that a robot had been granted Saudi Arabian citizenship – a gimmick, admittedly – was nevertheless reported as yet another step in the direction of our much-anticipated demise. I am a tech evangelist. I like to say I went into politics for exactly the same reason I went into engineering, two decades earlier: to make the world work better, for everyone.