Driving in winter conditions can be slow and hazardous, even for skilled drivers. The self-driving cars in development today are generally designed and tested on city streets, with curbs and lane markings and GPS maps to rely on. But what happens when you live in a country like Finland, where roads covered with several inches of snow are a fact of life every year?
Researchers at the VTT Technical Research Centre are tackling that problem head-on with Martti, an autonomous vehicle specifically programmed to safely navigate public roads blanketed in snow. Built on a Volkswagen Touareg, it’s equipped with a variety of antennas, sensors, cameras, and laser scanners.
The vehicle set a speed record for traveling in snowy conditions, according to a press release from the RobotCar Crew. “It probably also made a new world record in fully automated driving, making 40 km/h [25 mph] in a snowfall on snow-covered terrain without lane markings,” said project manager Matti Kutila. It could have gone faster, he added, if it weren’t for the speed limiter on the vehicle.
The testing and training sessions took place on the Aurora E8 intelligent road in Muonio with Martti and his “spouse” Marilyn. She’s equipped with a different array of sensors, and the two cars communicate continuously. “Martti has been designed for demanding weather conditions and Marilyn shines as the queen of urban areas,” said Kutila.
Most autonomous vehicles rely on Lidar, or Light Detection and Ranging, which doesn’t work very well in snowy or whiteout conditions. Kutila told Bloomberg that Mattti is designed to work even “when turbulent snow degrades 3D-sensor performance.” The car’s systems include radar and three forward-facing lasers.
VTT is hardly the first self-driving company to experiment with snowy conditions, but it certainly has a head start on their competition, as Waymo and Yandex just began their adverse weather tests a couple months ago.
The team is planning to upgrade the optical components and increase the resolution of the radar. Early next year, Martti will also be able to communicate with existing transport infrastructure via communication modules.
Even with all the high-tech additions, Kutila says it’s not always the smoothest ride. “It’s a prototype and not as comfortable as driving manually,” he admits. “However, when the car starts doing decisions himself, it feels a bit like a human — and you even start talking to the car, ‘What are you doing?’”
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.
Military working dogs charge into places the rest of us would flee. So, I understand why anyone would want to breed tougher, healthier dogs for the job.
Warhound, a new startup from Colossal Biosciences co-founder Ben Lamm and Anduril co-founder Palmer Luckey, has stepped out of stealth with $200 million to clone and gene-edit working dogs for American troops, police departments, and emergency services (via TechCrunch).
AI can describe a picture, identify objects, and answer questions about what a camera sees. But when a blind user needs a quick answer, getting an entire spoken essay about the scene isn't exactly helpful. Researchers at the University of Maryland (UMD) have found that AI-powered visual assistance can leave blind users doing too much work to get the information they actually need.
The study, titled Say It My Way: Exploring Control in Conversational Visual Question Answering with Blind Users, examined how people interact with Be My AI, an AI-powered feature of the Be My Eyes app. The researchers found that users often received lengthy descriptions that didn't adequately address their immediate goals, forcing them to ask follow-up questions or find ways to steer the AI towards a more useful answer.