From now through April 15, NASA is enlisting citizen scientists and amateur cloud-gazers around the world to help validate satellite data on cloud formations. Anyone who wants to participate can simply point their phone at the sky and snap a photo.
The initiative is part of the GLOBE (Global Learning and Observations to Benefit the Environment) program, an international education effort to encourage students and anyone interested in science to participate in data collection.
Marilé Colón Robles from the Langley Research Center explained that the data helps scientists classify cloud formations in satellite images. “The GLOBE Program is offering this challenge to show people how important it is to NASA to have citizen scientist observations; observations from the ground up,” she said. “We’re going from winter to spring, so the types of storms will change, which will also change the types of clouds.”
If you’d like to be a part of it, you can download the GLOBE Observer app from its website. Participants can submit up to ten cloud photos per day, and those with the most observations will be recognized in a NASA video.
NASA is asking for on-the-ground observations now because data is coming in from a new CERES (Clouds and the Earth’s Radiant Energy System) instrument. CERES, which launched into orbit in November, uses a variety of sensors to monitor the Earth below.
Even with advanced technology, it can sometimes be difficult to tell the difference between wispy cirrus clouds and patches of snow on the ground, for example. “Looking at what an observer recorded as clouds and looking at their surface observations really helps us better understand the images that were matched from the satellite,” said Colón Robles.
NASA recommends that you wait 10-15 minutes between observations for atmospheric changes. You can use the app to see when satellites are overhead and when your photos might be most useful.
The website also has some tips for photographers, as well as some basic information on the different cloud types. Colón Robles noted that you don’t need to be an atmospheric scientist or avid photographer to participate, NASA is interested in all the data they can collect. “Just go outside,” she said.
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.