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Daniel Estrada
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Robot. Made of robots.
Robot. Made of robots.

30,376 followers
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LOOPY
Online tool by Nicky Case lets you easily create system diagrams which can be programmed just by drawing.
More Here: http://prostheticknowledge.tumblr.com/post/158751394481/loopy-online-tool-by-nicky-case-lets-you-easily
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// The promotional clip actually shows a robot chasing a human intruder off the lawn. hahahaha

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// 2017 is the year when robots drilling into live human skulls is celebrated as a great achievement.

This robot is performing cochlear implant surgery, a delicate operation at the very limits of human dexterity. The procedure requires placing small wires in a tiny bone in the deep inner ear, an area surrounded by important nerves to the face and head. Slip a few millimeters in any direction could cause significant damage to the patient.

This robot is equipped with a variety of sensors to monitor the patient while performing the operation in much tighter bounds than any human can manage.

The full article describing the surgery is here: http://robotics.sciencemag.org/content/2/4/eaal4916.full

This issue of Science Robotics was accompanied with an editorial recommending six "levels of autonomy" for robotic surgeons that parallel the SAE framework for regulating autonomous vehicles.
http://robotics.sciencemag.org/content/2/4/eaam8638.full

Here's the pop article I took the gif from. via +Jeffrey J Davis
http://www.popsci.com/first-robot-assisted-cochlear-implant-surgery
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The body is the missing link for truly intelligent machines

I suspect that this basic imperative of bodily survival in an uncertain world is the basis of the flexibility and power of human intelligence. But few AI researchers have really embraced the implications of these insights. The motivating drive of most AI algorithms is to infer patterns from vast sets of training data – so it might require millions or even billions of individual cat photos to gain a high degree of accuracy in recognising cats. By contrast, thanks to our needs as an organism, human beings carry with them extraordinarily rich models of the body in its broader environment. We draw on experiences and expectations to predict likely outcomes from a relatively small number of observed samples. So when a human thinks about a cat, she can probably picture the way it moves, hear the sound of purring, feel the impending scratch from an unsheathed claw. She has a rich store of sensory information at her disposal to understand the idea of a ‘cat’, and other related concepts that might help her interact with such a creature. This means that when a human approaches a new problem, most of the hard work has already been done. In ways that we’re only just beginning to understand, our body and brain, from the cellular level upwards, have already built a model of the world that we can apply almost instantly to a wide array of challenges. But for an AI algorithm, the process begins from scratch each time. There is an active and important line of research, known as ‘inductive transfer’, focused on using prior machine-learned knowledge to inform new solutions. However, as things stand, it’s questionable whether this approach will be able to capture anything like the richness of our own bodily models.



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Desargues’ concertina

Suppose you draw two regular polygons with the same number of vertices, sharing the same centre, one polygon larger than the other. Allow for the possibility that one or both of these polygons are star polygons, where you draw edges not between consecutive vertices, but after skipping some fixed number of points.

The graph you get by joining up the vertices of the inner and outer polygons is known as an “I-graph”, and if the outer polygon is a normal polygon, it is known as a “Generalised Petersen graph”.

In 2012, three mathematicians proved that almost every I-graph, and every generalised Petersen graph, is a unit-distance graph: you can find a way to draw the graph so that all the edges have distance 1.

Žitnik, Arjana; Horvat, Boris; Pisanski, Tomaž, "All generalized Petersen graphs are unit-distance graphs", J. Korean Math. Soc. 49 (2012), No. 3, pp. 475–491

http://basilo.kaist.ac.kr/mathnet/thesis_file/JKMS-49-3-475-491.pdf

One example of a generalised Petersen graph is known as the Desargues graph. Here, the outer polygon is a decagon, while the inner polygon is a 10-pointed star where each vertex is joined to the one you get by adding 3, in a counter-clockwise numbering of the vertices. This turns out to be very easy to draw as a unit-distance graph: you just make the radii of the inner and outer polygons equal to the small and large golden ratios, which differ by 1. In most other examples, you need to introduce a twist between the rings of vertices, but here that isn't necessary.

You can read much more about the Desargues graph in this page by John Baez (which describes its construction in terms of relationships between subsets of a set of 5 elements):

http://math.ucr.edu/home/baez/networks/networks_14.html

The unit-distance version of the Desargues graph described above is not rigid, and in fact there is an 8-parameter family (up to overall rotations and translations) of ways of drawing the graph while maintaining the same edge lengths. The image below shows one highly symmetrical, 1-parameter family of unit-distance versions of the graph.


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> The set of collective memories that a group holds clearly evolves over time. One reason for this is that people tend to be marked most by events in their adolescence or young adulthood — a phenomenon known as the 'reminiscence bump'. As a new generation grows up, events that happen to its members during their youth override the events that previously dominated society, and thus 'update' the collective memory. A 2016 survey by the Pew Research Center in Washington DC showed that the defining historical moments for baby boomers in the United States were the assassination of John F. Kennedy and the Vietnam War, whereas for those born since 1965, they were the terror attacks on 11 September 2001 and the election of former US president Barack Obama9.

And over time, each generation adds some events and forgets others. Psychologists Henry Roediger of Washington University in St. Louis, Missouri, and Andrew DeSoto of the Association for Psychological Science in Washington DC report, for example, that successive US generations forget their past presidents in a regular manner that can be described by a power function10. They predict that Harry Truman (1945–53) will be as forgotten by 2040 as William McKinley (1897–1901) is today.

That evolution is reflected by evolving attitudes towards the future. Roediger and anthropologist James Wertsch, also of Washington University, have observed that US politicians debating the invasion of Iraq in the early 2000s fell into two groups: those who advocated invasion on the grounds that Saddam Hussein had to be stopped like Adolf Hitler before him, and those who opposed it because they feared another bloody, protracted Vietnam War. Although each might have chosen their historical precedent for political reasons, they in turn reinforced that precedent in the memory of anyone who heard them speak.

More: http://www.nature.com/news/how-facebook-fake-news-and-friends-are-warping-your-memory-1.21596
via +Sabine Hossenfelder

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> Koster says that online worlds are disproportionately used by people who are emotionally vulnerable, as a therapeutic tool. These people are the bread and butter of the games industry, but the industry does nothing to protect them from the bad behavior built into the games they design.

// This talk is fantastic. Highly recommended!

Legendary game designer Raph Koster is angry at the overwhelming amount of abusive behavior in online gaming worlds.

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"人工知能" is Japanese for "Artificial Intelligence."

人 = human.
工 = made.
知 = knowing.
能 = ability.

Language is awesome, isn't it?
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