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Clams Are Giving Each Other Cancer

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The clams are dying. Since at least the 1970s, soft-shell clams (Mya arenaria) from Canada to Maryland have been plagued with a mysterious disease. This month, researchers announced that they’d finally identified the disease: clam leukemia.

Clam leukemia?!

Clams are simple creatures. They don’t have legs, or brains, or faces. But they do have hearts, and those hearts pump hemolymph (the clam version of blood) throughout their bodies. It’s in this hemolymph that the cancer has taken hold.

For years, scientists suspected that the clam-killing disease was caused by a virus. Then a team of researchers specializing in microbiology, cancer, and marine biology examined the clams’ DNA.

What they found inspired more questions than answers. The clams had cancer—and it was contagious.

Nearly all cancers are a one-shot deal, and can’t be passed from one animal to another. Until recently, there were only two known contagious cancers in the world. One is a dog STD called Canine Transmissible Venereal Tumor. The other is Devil Facial Tumor Disease, which is transmitted when one Tasmanian devil bites another one on the face.

But clams aren’t humping, and since they don’t have faces, they’re definitely not biting each other. How, then, is the cancer passed from one clam to the next? The researchers aren’t totally sure, but they think that the cancer cells may be released into the water. Clams are filter feeders, sucking up liters of water every hour. If a few clam-cer cells happened to be in the neighborhood, they could easily find themselves a new home.

Nobody knows how one clam’s leukemia could become contagious. So where did those free-floating cancer cells come from? To find out, the scientists sequenced cancer cells from clams all up and down the East Coast. Yet again, the answer was mind-boggling: the genes were all identical, which means that every clam’s cancer had all come from a single, original host. That’s one unfortunate clam—which got cancer more than 40 years ago. That clam’s cancer cells scooted off into the ocean, where they found another host, whose cancer cells eventually scooted off into the ocean … and now it’s 2015. The cancer has traveled hundreds of miles, and we’ve got a whole lot of sick clams.

And it may not just be clams. Mussels, oysters, and cockles are all afflicted with similarly mysterious illnesses. As long as people want to eat shellfish, these researchers will have jobs.

Thankfully, only clams can get clam-cer. Eating seafood and swimming in the ocean are still safe for humans. As safe as they’ve ever been, anyway.

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Google's AI Can Make Its Own AI Now
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Artificial intelligence is advanced enough to do some pretty complicated things: read lips, mimic sounds, analyze photographs of food, and even design beer. Unfortunately, even people who have plenty of coding knowledge might not know how to create the kind of algorithm that can perform these tasks. Google wants to bring the ability to harness artificial intelligence to more people, though, and according to WIRED, it's doing that by teaching machine-learning software to make more machine-learning software.

The project is called AutoML, and it's designed to come up with better machine-learning software than humans can. As algorithms become more important in scientific research, healthcare, and other fields outside the direct scope of robotics and math, the number of people who could benefit from using AI has outstripped the number of people who actually know how to set up a useful machine-learning program. Though computers can do a lot, according to Google, human experts are still needed to do things like preprocess the data, set parameters, and analyze the results. These are tasks that even developers may not have experience in.

The idea behind AutoML is that people who aren't hyper-specialists in the machine-learning field will be able to use AutoML to create their own machine-learning algorithms, without having to do as much legwork. It can also limit the amount of menial labor developers have to do, since the software can do the work of training the resulting neural networks, which often involves a lot of trial and error, as WIRED writes.

Aside from giving robots the ability to turn around and make new robots—somewhere, a novelist is plotting out a dystopian sci-fi story around that idea—it could make machine learning more accessible for people who don't work at Google, too. Companies and academic researchers are already trying to deploy AI to calculate calories based on food photos, find the best way to teach kids, and identify health risks in medical patients. Making it easier to create sophisticated machine-learning programs could lead to even more uses.

[h/t WIRED]

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European Space Agency Releases First High-Res Land Cover Map of Africa
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Land Cover CCI, ESA

This isn’t just any image of Africa. It represents the first of its kind: a high-resolution map of the different types of land cover that are found on the continent, released by The European Space Agency, as Travel + Leisure reports.

Land cover maps depict the different physical materials that cover the Earth, whether that material is vegetation, wetlands, concrete, or sand. They can be used to track the growth of cities, assess flooding, keep tabs on environmental issues like deforestation or desertification, and more.

The newly released land cover map of Africa shows the continent at an extremely detailed resolution. Each pixel represents just 65.6 feet (20 meters) on the ground. It’s designed to help researchers model the extent of climate change across Africa, study biodiversity and natural resources, and see how land use is changing, among other applications.

Developed as part of the Climate Change Initiative (CCI) Land Cover project, the space agency gathered a full year’s worth of data from its Sentinel-2A satellite to create the map. In total, the image is made from 90 terabytes of data—180,000 images—taken between December 2015 and December 2016.

The map is so large and detailed that the space agency created its own online viewer for it. You can dive further into the image here.

And keep watch: A better map might be close at hand. In March, the ESA launched the Sentinal-2B satellite, which it says will make a global map at a 32.8 feet-per-pixel (10 meters) resolution possible.

[h/t Travel + Leisure]

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