Lifeboat Foundation: Safeguarding Humanity
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New research suggests that the human brain is almost beyond comprehension because it doesn’t process the world in two dimensions or even three. No, the human brain understands the visual world in up to 11 different dimensions.

The astonishing discovery helps explain why even cutting-edge technologies like functional MRIs have such a hard time explaining what is going on inside our noggins. In a functional MRI, brain activity is monitored and represented as a three-dimensional image that changes over time. However, if the brain is actually working in 11 dimensions, looking at a 3D functional MRI and saying that it explains brain activity would be like looking at the shadow of a head of a pin and saying that it explains the entire universe, plus a multitude of other dimensions.

The team of scientists led by a group from Scientists at the École Polytechnique Fédérale de Lausanne in Switzerland detected the previously unknown complexities of the brain while working on the Blue Brain Project. The project’s goal is to create a biologically accurate recreation of the human brain.

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“Deep Learning” computer systems, based on artificial neural networks that mimic the way the brain learns from an accumulation of examples, have become a hot topic in computer science. In addition to enabling technologies such as face- and voice-recognition software, these systems could scour vast amounts of medical data to find patterns that could be useful diagnostically, or scan chemical formulas for possible new pharmaceuticals.

But the computations these systems must carry out are highly complex and demanding, even for the most powerful computers.

Now, a team of researchers at MIT and elsewhere has developed a new approach to such computations, using light instead of electricity, which they say could vastly improve the speed and efficiency of certain deep learning computations. Their results appear today in the journal Nature Photonics (“Deep learning with coherent nanophotonic circuits”) in a paper by MIT postdoc Yichen Shen, graduate student Nicholas Harris, professors Marin Soljacic and Dirk Englund, and eight others.

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Now you have until 6/30 to submit a proposal to the Agency’s Lifelong Learning Machines (L2M) program.

Here’s the vision: Muster all the creativity that you can with the goal of developing fundamentally new machine learning approaches that enable systems to learn continually as they operate and apply previous knowledge to novel situations. Current AI systems only compute with what they have been programmed or trained for in advance; they have no ability to learn from data input during execution time and cannot adapt online to changes they encounter in real environments. The goal of L2M is to develop substantially more capable systems that are continually improving and updating from experience.

Consult the Broad Agency Announcement for more information: https://www.fbo.gov/…/…/DARPA/CMO/HR001117S0016/listing.html

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I’ll be on a panel and also doing an author’s roundtable (The Transhumanist Wager) at FreedomFest in Las Vegas on July 21. It’s one of the largest gatherings of free minds in the world and this year is the 10th anniversary. If you’re there, please say hello! Others are speaking on life extension and AI. Here’s my speaker’s page:

Check out what Zoltan Istvan will be attending at FreedomFest 2017.

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NASA has revealed plans to grow bioprinted cancer cells in space in a bid to advance cancer research.

Utilizing the microgravity environment, NASA hopes to the cell structures will grow in a more natural spherical shape. Since, back on earth in vitro the cells have only able been able to grow in two-dimensional layers. However to harness the cells without the presence of gravity, NASA is hoping to employ magnets.

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