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Oct 31, 2016

Michael Fossel on Aging and the Telomerase Revolution

Posted by in categories: biotech/medical, life extension, singularity

Dr. Michael Fossel is one of those few theoreticians who can see much of the big picture of aging. While some use mostly guesswork, and others hope to improve on that with logic, Fossel never shies away from the clear verdict that only data can give. Add his overwhelming compassion as a human being and you will understand why he is a clinician who really cares. You will also get a pretty good idea of what kind of a person Michael is – both personally and professionally. And those are just some of the reasons why enjoy having him back on my Singularity 1on1 podcast for an in-depth discussion of his latest book on the topic titled the Telomerase Revolution.

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Oct 31, 2016

Elon Musk Unveils ‘Solar Roof ’

Posted by in categories: Elon Musk, solar power, sustainability

Elon Musk Unveils ‘Solar Roof ‘

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Oct 31, 2016

Tiny swarm bots form a queue

Posted by in category: robotics/AI

These little robots can swarm like insects — or form an orderly queue. (Original video from the University of Toronto:

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Oct 31, 2016

The world in 2045, according to the Pentagon

Posted by in category: military

Some predictions for 2045, from the Pentagon.

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Oct 30, 2016

Breaking into the Simulated Universe

Posted by in categories: computing, Elon Musk, ethics, internet, neuroscience

I argued in my 2015 paper “Why it matters that you realize you’re in a Computer Simulation” that if our universe is indeed a computer simulation, then that particular discovery should be commonplace among the intelligent lifeforms throughout the universe. The simple calculus of it all being (a) if intelligence is in part equivalent to detecting the environment (b) the environment is a computer simulation © eventually nearly all intelligent lifeforms should discover that their environment is a computer simulation. I called this the Savvy Inevitability. In simple terms, if we’re really in a Matrix, we’re supposed to eventually figure that out.

Silicon Valley, tech culture, and most nerds the world over are familiar with the real world version of the question are we living in a Matrix? The paper that’s likely most frequently cited is Nick Bostrom’s Are you living in a Computer Simulation? Whether or not everyone agrees about certain simulation ideas, everyone does seem to have an opinion about them.

Recently, the Internet heated up over Elon Musk’s comments at a Vox event on hot tub musings of the simulation hypothesis. Even Bank of America published an analysis of the simulation hypothesis, and, according to Tad Friend in an October 10, 2016 article published in New Yorker, “two tech billionaires have gone so far as to secretly engage scientists to work on breaking us out of the simulation.”

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Oct 30, 2016

NASA’s New ‘Intruder Alert’ System Spots An Incoming Asteroid

Posted by in categories: robotics/AI, space

A space rock zips by earth Sunday night. Astronomers know it doesn’t pose a threat, in part thanks to a new automated warning program called Scout.

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Oct 30, 2016

HoloLens gets more battlefield use

Posted by in categories: augmented reality, military, security

We have already seen the HoloLens mixed reality headset put to military use by the Israeli Defense Force for advanced battlefield planning.

Now Ukrainian company LimpidArmor has shown off a new application for the augmented reality device on the actual battlefield to improve the field of view of tank commanders without exposing them to additional risk. The technology was shown off at the Arms and Security show, held in Kiev from 11 to 14 October.

LimpidArmor’s hardware and software system uses a HoloLens integrated with a helmet and cameras mounted around the tank to give commanders a 360 degree view of their environment in both optical and thermal and makes this available in real-time.

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Oct 30, 2016

Nightmare Machine at CSIRO is slowly but surely learning how to terrify humans

Posted by in categories: computing, information science, robotics/AI

Story just in time for Halloween.

The prospect of artificial intelligence is scary enough for some, but Manuel Cebrian Ramos at CSIRO’s Data61 is teaching machines how to terrify humans on purpose.

Dr Cebrian and his colleagues Pinar Yanardag and Iyad Rahwan at the Massachusetts Institute of Technology have developed the Nightmare Machine.

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Oct 30, 2016

Harley-Davidson Says Artificial Intelligence Drives 40% of New York Sales

Posted by in categories: business, robotics/AI, transportation

Nice job Harley-Davidson when can I have my discount for my new wheels?

Harley-Davidson Says Artificial Intelligence Drives 40% of New York Sales Lookalike modeling is a key component of lead generation, and for motorcycle brand Harley-Davidson, the tactic now goes hand in hand with artificial intelligence (AI). In March 2016, the company began working with machine learning technology provider Adgorithms to grow its ecommerce reach and hasn’t looked back since. Asaf Jacobi, president of Harley-Davidson’s New York City division, spoke with eMarketer’s Maria Minsker about the brand’s experience with AI and discussed the results he has seen so far.

EMarketer: What are some of the business challenges that drove you to try artificial intelligence?

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Oct 30, 2016

Google’s neural networks created their own encryption method

Posted by in categories: cybercrime/malcode, encryption, information science, robotics/AI

Fortifying cybersecurity is on everyone’s mind after the massive DDoS attack from last week. However, it’s not an easy task as the number of hackers evolves the same as security. What if your machine can learn how to protect itself from prying eyes? Researchers from Google Brain, Google’s deep Learning project, has shown that neural networks can learn to create their own form of encryption.

According to a research paper, Martín Abadi and David Andersen assigned Google’s AI to work out how to use a simple encryption technique. Using machine learning, those machines could easily create their own form of encrypted message, though they didn’t learn specific cryptographic algorithms. Albeit, compared to the current human-designed system, that was pretty basic, but an interesting step for neural networks.

To find out whether artificial intelligence could learn to encrypt on its own or not, the Google Brain team built an encryption game with its three different entities: Alice, Bob and Eve, powered by deep learning neural networks. Alice’s task was to send an encrypted message to Bob, Bob’s task was to decode that message, and Eve’s job was to figure out how to eavesdrop and decode the message Alice sent herself.

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