Scientists at Harvard have copied their large, insect-inspired robot HAMR (Harvard Ambulatory Microrobot) into a smaller form factor. The new robot, HAMR-JR, is the size of a penny, measuring 2.25 centimetres across. The robot is capable of quick movement, able to travel 14 times the length of his body in a single second, which makes it one of the smallest and fastest robots currently made, according to Harvard. While it might be the size of a penny, it is significantly lighter, weighing only 0.3 grams. The ability to keep the familiar design, but change the scale of the robot, means that it can be used in a variety of purposes, including surgeries or large-scale industry because of its ability to carry heavy payloads. The method of miniaturising the robot was surprisingly straightforward: researchers simply shrunk the 2D sheet design of the robot, as well as its circulatory, to a more minute scale.

Jack Weast, vice president of autonomous vehicle standards at Intel Corp's Mobileye, in an interview on Friday said the auto industry was assembling a vast list of likely road scenarios and human behavior that every driverless car should be able to navigate safely. Government agencies and insurance companies are part of that process, Weast said.

Now, one firm wants to take things even further. It is developing machine-learning software to measure how quickly employees complete different tasks and suggest ways to speed them up. The tool also gives each person a productivity score, which managers can use to identify those employees who are most worth retaining--and those who are not. How you feel about this will depend on how you view the covenant between employer and employee. Is it okay to be spied on by people because they pay you?

The IIHS studied over 5,000 crashes with detailed causes that were collected by the National Highway Traffic Safety Administration, separating out those caused by "sensing and perceiving" errors such as driver distraction, impaired visibility or failing to spot hazards until it was too late. Researchers also separated crashes caused by human "incapacitation" including drivers impaired by alcohol or drugs, those who fell asleep or drivers with medical problems. Self-driving vehicles can prevent those, the study found.

A four-legged robot that inspects concrete can walk through underground sewage tunnels and detect when they need repairing. Hendrik Kolvenbach at the Swiss Federal Institute of Technology (ETH Zurich) in Switzerland and his colleagues have developed a robot that scratches one of its legs against concrete to determine the condition it is in. The robot is waterproof and it can wade through water and climb over obstacles. Because many modern sewage systems were built decades ago, constant underground monitoring is needed to prevent major leaks.

Nils J. Nilsson, a computer scientist who helped develop the first general-purpose robot and was a co-inventor of algorithms that made it possible for the machine to move about efficiently and perform simple tasks, died on Sunday at his home in Medford, Ore. His death was confirmed by his wife, Grace Abbott. Dr. Nilsson was a member of a small group of computer scientists and electrical engineers at the Stanford Research Institute (now known as SRI International) who pioneered technologies that have proliferated in modern life, whether in navigation software used in more than a billion smartphones or in such speech-control systems as Siri. The researchers had been recruited by Charles Rosen, a physicist at the institute, who had raised Pentagon funding in 1966 to design a robot that would be used as a platform for doing research in artificial intelligence. Although the project was intended to create a general-purpose mobile "automaton" and be a test bed for A.I. programs, Mr. Rosen had secured the funding by selling the idea to the Pentagon that the machine would be a mobile sentry for a military base.

As a teenager in Maryland in the 1950s, Mary Allen Wilkes had no plans to become a software pioneer -- she dreamed of being a litigator. One day in junior high in 1950, though, her geography teacher surprised her with a comment: "Mary Allen, when you grow up, you should be a computer programmer!" Wilkes had no idea what a programmer was; she wasn't even sure what a computer was. The first digital computers had been built barely a decade earlier at universities and in government labs. By the time she was graduating from Wellesley College in 1959, she knew her legal ambitions were out of reach. Her mentors all told her the same thing: Don't even bother applying to law school. "They said: 'Don't do it.

In archaeology, there are few watershed moments, when a technological breakthrough changes everything. But the invention of radiocarbon dating in the 1940s brought one such revolution, by providing a consistent, worldwide system for placing archaeological material in chronological order. A more-recent transformative innovation is the airborne application of a remote-sensing technique called light detection and ranging (lidar) to create a model (also known as a digital-elevation model) of the bare-surface terrain that is hidden by trees in forested areas1. Lidar is changing archaeological study of the ancient Maya in Mexico and Central America. It is increasing the speed and scale of discovery, and reshaping our understanding of the antiquity of monumental-scale landscape alteration.

As the recently released GPT-3 and several recent studies demonstrate, racial bias, as well as bias based on gender, occupation, and religion, can be found in popular NLP language models. But a team of AI researchers wants the NLP bias research community to more closely examine and explore relationships between language, power, and social hierarchies like racism in their work. Published last week, the work, which includes analysis of 146 NLP bias research papers, also concludes that the research field generally lacks clear descriptions of bias and fails to explain how, why, and to whom that bias is harmful. "Although these papers have laid vital groundwork by illustrating some of the ways that NLP systems can be harmful, the majority of them fail to engage critically with what constitutes'bias' in the first place," the paper reads. "We argue that such work should examine the relationships between language and social hierarchies; we call on researchers and practitioners conducting such work to articulate their conceptualizations of'bias' in order to enable conversations about what kinds of system behaviors are harmful, in what ways, to whom, and why; and we recommend deeper engagements between technologists and communities affected by NLP systems."

More funding for Argo AI, shared costs between Ford and VW. Ford, Volkswagen and Argo AI made it official on Tuesday. VW has made an investment in the self-driving technology company, which charts a course for shared development costs for any autonomous vehicle technologies to come. It's unclear how deep VW reached into its wallet, but a previous report pegged a coming investment at $1.7 billion. At the time, Argo AI was reportedly valued at $4 billion, which would put VW's investment at nearly 50% of its value.