This Week’s “Planet Earth” Report –Aging Mount Agung’s Deadly Eruptions to Species-Jumping Virus and Dark Secret of AI



Bali's Mount Agung Poised to Erupt

An eruption at Bali’s Mount Agung volcano is imminent, according to experts. Hundreds of tremors are being recorded at the site each day, and more than 75,000 people evacuated in the past few days after local authorities declared a state of emergency. Last week Indonesian authorities announced the highest possible alert warning, and besides the evacuations they’ve also set up an exclusion zone that stretches 12km from the crater in some places.

Scott Bryan, an associate professor from the Queensland University of Technology, says there have been “very good indications” that an eruption is imminent. “The fact that the seismic tremors beneath the volcano are increasing in number, intensity, and the reduction in their depth in the last week or so, is a very good indication that magma is moving up to the surface,” he said.

As well as seismic activity, Bryan said there are two other signs that an eruption is imminent: gas emissions from the summit, and bulging on the volcano’s surface. He said gas emissions were a sign that pressure under the ground had become too great, sending magma towards the summit of the volcano and releasing gas and steam in the process. “It’s like a bottle of Coke or champagne, if you shake them up the pressure builds until you release the lid,” he said.

Mount Agung hasn’t erupted for more than 50 years. The last time it did, in 1963, more than 1,000 people were killed and hundreds more were injured. Lava flowed for 7km from the crater, and the ABC reports that survivors of the catastrophe recall a “rain of ashes”. But the most deadly feature of the volcano were the devastating pyroclastic flows: waves of superheated gas containing gas, ash and rock that can travel hundreds of kilometres an hour.

“Pyroclastic flows are the main hazard and threat in terms of killing a lot of people very quickly with little to no warning,” Bryan said. “If it’s at night and people are in bed they have literally seconds or minutes to move and people get caught and trapped and die. It’s what caused the deaths in 1963, and at Mount Merapi in 2010.”

This time authorities have taken plenty of precautions, but Bryan said there was no way to be totally sure of its impact. “What we need to worry about when it does erupt is how much of the gasses have been able to escape from magma,” he said. “If you think about your bottle of Coke again, if you shake it up and take the lid off you get it all foaming out, but, if you take the lid off, let it stand there for a day and then shake it, all the gas has escaped and nothing happens.”

In 1963, when Mount Agung last erupted, global temperatures dropped by between 0.1C and 0.4C. And in 1991 the eruption of Mount Pinatubo in the Philippines created a significant dip in global temperatures of about 0.5C. That might not sound like much, but Ubide explains that it can have a “significant impact”.

“Obviously you will not feel a massive change personally but it’s going to affect everything on Earth because everything responds to climate,” she said. But volcanos also contribute to global warming by releasing CO2; underwater and land-based volcanoes are estimated to release between 100m–300m tonnes of CO2 each year.

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The Dark Secret at the Heart of AI




We will soon be co-existing with machines that think and make decisions differently from the way a human would. We’ve never before built machines that operate in ways their creators don’t understand. How well can we expect to communicate—and get along with—intelligent machines that could be unpredictable and inscrutable?

No one really knows how the most advanced algorithms do what they do. That could be a problem. Last year, a strange self-driving car was released onto the quiet roads of Monmouth County, New Jersey. The experimental vehicle, developed by researchers at the chip maker Nvidia, didn’t look different from other autonomous cars, but it was unlike anything demonstrated by Google, Tesla, or General Motors, and it showed the rising power of artificial intelligence. The car didn’t follow a single instruction provided by an engineer or programmer. Instead, it relied entirely on an algorithm that had taught itself to drive by watching a human do it.

Getting a car to drive this way was an impressive feat. But it’s also a bit unsettling, since it isn’t completely clear how the car makes its decisions. Information from the vehicle’s sensors goes straight into a huge network of artificial neurons that process the data and then deliver the commands required to operate the steering wheel, the brakes, and other systems. The result seems to match the responses you’d expect from a human driver. But what if one day it did something unexpected—crashed into a tree, or sat at a green light? As things stand now, it might be difficult to find out why. The system is so complicated that even the engineers who designed it may struggle to isolate the reason for any single action. And you can’t ask it: there is no obvious way to design such a system so that it could always explain why it did what it did.

The mysterious mind of this vehicle points to a looming issue with artificial intelligence. The car’s underlying AI technology, known as deep learning, has proved very powerful at solving problems in recent years, and it has been widely deployed for tasks like image captioning, voice recognition, and language translation. There is now hope that the same techniques will be able to diagnose deadly diseases, make million-dollar trading decisions, and do countless other things to transform whole industries.

But this won’t happen—or shouldn’t happen—unless we find ways of making techniques like deep learning more understandable to their creators and accountable to their users. Otherwise it will be hard to predict when failures might occur—and it’s inevitable they will. That’s one reason Nvidia’s car is still experimental.

Already, mathematical models are being used to help determine who makes parole, who’s approved for a loan, and who gets hired for a job. If you could get access to these mathematical models, it would be possible to understand their reasoning. But banks, the military, employers, and others are now turning their attention to more complex machine-learning approaches that could make automated decision-making altogether inscrutable. Deep learning, the most common of these approaches, represents a fundamentally different way to program computers.

This raises mind-boggling questions. As the technology advances, we might soon cross some threshold beyond which using AI requires a leap of faith. Sure, we humans can’t always truly explain our thought processes either—but we find ways to intuitively trust and gauge people. These questions took me on a journey to the bleeding edge of research on AI algorithms, from Google to Apple and many places in between, including a meeting with one of the great philosophers of our time.

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Viruses Would Rather Jump to New Hosts Than Evolve With Them 



The discovery that viruses move between species unexpectedly often is rewriting ideas about their evolutionary history — and may have troubling implications for the threat from emerging diseases. When new species evolve, where do their viruses come from? As little more than free-ranging bundles of genetic material, viruses desperately need to hijack their hosts’ cellular machinery and resources to replicate, over and over again. Without its host, a virus is nothing.

Because of that dependence, some viruses have stuck with their hosts throughout evolution, mutating to make minor adjustments every time the host branched into a new species — a process called co-divergence. Humans and chimpanzees, for instance, have slightly different versions of the hepatitis B virus, both of which likely mutated from a version that infected their shared ancestor more than four million years ago.

The other option — cross-species transmission — occurs when a virus jumps into a completely new type of host largely unrelated to its former one. That kind of viral evolution is notoriously linked to severe emerging diseases like bird flu, HIV, Ebola fever and SARS. Given the extreme virulence of those diseases, the apparent rarity of cross-species transmission seemed fortunate.

But recently, when researchers in Australia conducted the first study of the long-term evolution of thousands of diverse viruses, they reached a startling conclusion: cross-species transmission has been more important and more frequent than anyone realized. Jumps between species have driven most major evolutionary innovations in the viruses. Meanwhile, co-divergence has been less common than was assumed and has mostly caused incremental changes.

“They showed rather convincingly that co-divergence is the exception rather than the rule,” said Pleuni Pennings, an evolutionary biologist and assistant professor at San Francisco State University who was not involved with the study.

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