Researchers at the University of Nevada have developed an autonomous robot, designed to inspect bridges and detect any structural damage before it can cause potential injury.
The four-wheeled robot bridge inspector, called Seekur, uses a variety of tools to carry out its important task. These include ground-penetrating radar for looking beneath the surface of a bridge for underlying instabilities, sensors designed to search for possible corrosion of steel or cement, and a camera which analyzes cracks in the bridge’s surface.
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A machine learning algorithm then analyzes all of this information and uses it to generate a color-coded map, which is passed on to (human) engineers to make them aware of weak spots. Impressively, this vital analysis work can be carried out in real time.
“The robot takes the same amount of time to physically scan the bridge as a human inspector but it processes the data in minutes instead of hours,” lead researcher Spencer Gibb told New Scientist.
Already, the robot has been tested on road bridges in Nevada, New Hampshire, Maine, and Montana. In all cases, it was reportedly faster and more accurate than human inspectors.
As with other areas where machine learning has been used for prediction, the ambition is that using AI to help assess the stability of bridges could cut down on human error. While human bridge inspectors perform a valuable job, they are capable of missing details. For example, in 2007 a bridge over the Mississippi river in Minnesota collapsed due to defects in steel plates which had been missed by safety inspectors. Thirteen people tragically lost their lives in the collapse.
There is no guarantee that a robot would not also make errors, of course, but it would be easier to ensure that they have carried out full examinations. Furthermore, due to the shortage of human inspectors, the presence of Seekur robots would hopefully result in more regular check-ups for the thousands of bridges around the United States.
Digital Trends contacted Spencer Gibb, but he was unable to provide more details about the potential rollout of the bridge-checking bots at this time.
San Francisco startup Dimensional advertised for people to walk robot dogs through city streets. The New York Times reported that the job could include carrying a roughly 33-pound robot back to the office if it overheated. A lift home is an awkward requirement for a labor-saving machine.
Keeping the hardware running is only one challenge. Anthropic's robotics tests found that language models mostly failed when controlling joints directly, but did better when directing trained controllers. Giving an AI agent a body doesn't teach it to handle ordinary household objects.
Soon, a mattress protector may be more than a bed cover. Australian medtech company Sleeptite and researchers at RMIT University have received a US patent for FlexiSense, a smart bedding technology that tracks body position and posture to help caregivers identify when older residents may be at risk of falling.
The technology is being developed for Sleeptite’s in-bed monitoring system, REMi, and was recently on display at The MedTech Conference in Boston. A peer-reviewed study in Flexible and Printed Electronics says the sensors can also be made at scale without sacrificing performance or durability.
AI companies spend enormous amounts of time convincing us their technology is safe and secure. But what happens when those same companies become targets of increasingly sophisticated AI-powered attacks? Anthropic, the company behind Claude, is now facing that question. According to a Washington Post report, cybersecurity startup Cathedral discovered vulnerabilities that let its researchers access sensitive information in Anthropic's internal systems.
The researchers used AI agents to identify potential entry points in less than 12 hours. Interestingly, they didn't need to crack Claude itself. Instead, they exploited weaknesses in third-party business applications that Anthropic uses for everyday operations. Anthropic's security testing program disclosed the findings, which allows outside researchers to identify and report vulnerabilities.