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Meet ‘Prosthesis’, the terrifying 14ft-tall ‘anti-robot’ that can carry a human and run over 20mph almost SILENTLY…


A 14-foot-tall exo-bionic racing robot could soon be tearing across the Nevada desert.

Exhibitors revealed the massive Prosthesis bot at CES 2017 in Las Vegas today, and they say it can hit a top speed of roughly 20 miles per hour – and despite its imposing size, it’s nearly silent when it moves.

Not sure where the author got his messaging on AI and QC (namely AI more fluid and human like due to QC); but it sounds a lot like my words. However, there is one lost piece to the AI story even with QC to make AI more human like and that is when you have Synbio involved in the mix. In fact I can not wait to see what my friend Alex Zhavoronkov and his team does with QC in his anti-aging work. I expect to see many great things with QC, AI, and Synbio together.

Nonetheless, I am glad to see others also seeing the capability that many of us do see.


Applications of Artificial Intelligence In Use Today

Beyond our quantum-computing conundrum, today’s so-called A.I. systems are merely advanced machine learning software with extensive behavioral algorithms that adapt themselves to our likes and dislikes. While extremely useful, these machines aren’t getting smarter in the existential sense, but they are improving their skills and usefulness based on a large dataset. These are some of the most popular examples of artificial intelligence that’s being used today.

Researchers at MIT’s Computer Science and Artificial Intelligence Laboratory have developed a new computational model of a neural circuit in the brain, which could shed light on the biological role of inhibitory neurons — neurons that keep other neurons from firing.

The model describes a neural circuit consisting of an array of input neurons and an equivalent number of output neurons. The circuit performs what neuroscientists call a “winner-take-all” operation, in which signals from multiple input neurons induce a signal in just one output neuron.

Using the tools of theoretical computer science, the researchers prove that, within the context of their model, a certain configuration of inhibitory neurons provides the most efficient means of enacting a winner-take-all operation. Because the model makes empirical predictions about the behavior of inhibitory neurons in the brain, it offers a good example of the way in which computational analysis could aid neuroscience.

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In Brief

  • Numerai is making a collective artificial intelligence in order to make stock market predictions.
  • So far, their data scientists have submitted over 12 billion equity price predictions in less than a year

There’s a new way to make stock market predictions. One company, Numerai, is synthesizing machine intelligence to command the capital of an American hedge fund.

The team outlines the focus of their work, asserting that they take the most accurate and original machine learning models from the world’s best data scientists and synthesize them into “a collective artificial intelligence.” This AI controls the capital in Numerai’s hedge fund.

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The article does bring up many of the same points that many have raised with self driving cars; and folks still don’t seem to understand that we have thousands if not millions of laws in the US alone that must be reviewed and possibly changed to address this technology on the roads. When you look at every state, each county, and each town or city’s laws around driving on their roads; it could be a long and painful period for companies and consumers before the legal side of things catch up.


Self-driving car technology is not yet ready for prime time. Driver assist is.

The Legal challenges and potential liability are immense.

How to play the hype.