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“If something goes wrong, I can just chop off that part of the skin.” Josiah Zayner took a swig from his beer and squinted into the spotlight. He was already kind of drunk. He also hadn’t bothered to write a speech. Tattooed and heavily pierced with a shock of blue-gray hair, he shuffled around uneasily on stage. But 150-odd people had flown in from around the country to hear him speak—the mad pirate-king of biotech. “It all is coming from my heart,” he said, choking up a little. “Everything you’re going to hear today is me to the core.” Advertisement Zayner’s audiencesat in the fashionably…
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Concept artist Maciej Rebisz created this awesome image of Project Lyra laser sail spacecraft flying by the interstellar asteroid ‘Oumuamua! Please have a look at the Project Lyra paper, which is currently going viral: https://arxiv.org/abs/1711.03155
You can find more of Maciej’s incredible art here:
http://maciejrebisz.com/
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More than 15,000 scientists around the world have issued a global warning: there needs to be change in order to save Earth.
It comes 25 years after the first notice in 1992 when a mere 1,500 scientists issued a similar warning.
This new cautioning — which gained popularity on Twitter with #ScientistsWarningToHumanity — garnered more than 15,000 signatures.
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Artificial intelligence could be the powerful tool we need to solve some of the biggest problems facing our world, argues Raia Hadsell. In this talk, she offers an insight into how she and her colleagues are developing robots with the capacity to learn. Their superhuman ability to play video games is just the start.
Raia Hadsell is a research scientist on the Deep Learning team at DeepMind. She moved to London to join DeepMind in early 2014, feeling that her fundamental research interests in robotics, neural networks, and real world learning systems were well-aligned with the agenda of Demis, Shane, Koray, and other members of the original team. Raia’s research at DeepMind focuses on a number of fundamental challenges in AGI, including continual and transfer learning, deep reinforcement learning, and neural models of navigation. Raia came to AI research obliquely. After an undergraduate degree in religion and philosophy from Reed College, she veered off-course (on-course?) and became a computer scientist. Raia’s PhD with Yann LeCun, at NYU, focused on machine learning using Siamese neural nets (often called a ‘triplet loss’ today) and on deep learning for mobile robots in the wild. Her thesis, ‘Learning Long-range vision for offroad robots’, was awarded the Outstanding Dissertation award in 2009.
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