Artificial Intelligence To Replace Jobs In Health Care
One of the greatest benefits of medical technological innovations is the cost reduction of delivering world-class medical support to rural and developing communities. However, as technology advances, it also brings about disruption.
This video was produced by YT Wochit News using http://wochit.com
2015 Documentary – Nano Revolution
2015 Documentary, Nano technology products are becoming an important feature in our lives, this documentary will cover the most helpful things that nano tech could give us:
From electronics to healthcare,Improve the efficiency of fuel production, it can change the future of defense stronger uniforms. light-absorbing materials for camouflaging vehicles, nano-energy for blast weapons and more…
10 reasons why human level Artificial Intelligence is a false promise
Full video – Androids & Artificial Intelligence: A Modern Myth (2 hrs 40 mins) available for purchase on the Store page at http://www.collativelearning.com/. Written, edited and narrated by Rob Ager.
Michio Kaku: The Dark Side of Technology
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Dr. Michio Kaku addresses this question: What is the most dangerous technology?
Directed / Produced by
Jonathan Fowler and Elizabeth Rodd
Artificial Intelligence – Days of Rage
Track Title: Days of Rage
Artist: Artificial Intelligence
Label: V Recordings UK
Catalogue Number: PLVCD002
Released: October 18, 2010.
TRANSFORM – Amazing Technology Invented By MIT
TRANSFORM fuses technology and design to celebrate its transformation from a piece of still furniture to a dynamic machine driven by the stream of data and energy. Created by Professor Hiroshi Ishii and the Tangible Media Group from the MIT Media Lab, TRANSFORM aims to inspire viewers with unexpected transformations, as well as the aesthetics of the complex machine in motion.
The work is comprised of three dynamic shape displays that move more than one thousand pins up and down in realtime to transform the tabletop into a dynamic tangible display. The kinetic energy of the viewers, captured by a sensor, drives the wave motion represented by the dynamic pins.
The motion design is inspired by the dynamic interactions among wind, water and sand in nature, Escher’s representations of perpetual motion, and the attributes of sand castles built at the seashore. TRANSFORM tells the story of the conflict between nature and machine, and its reconciliation, through the ever-changing tabletop landscape.
Video Credit: MIT Media Lab/Tangible Media Group/Lexus Design Amazing 2014 Milan
More details at: http://tangible.media.mit.edu
Artificial Intelligence Evolved-PeterSatera
MP3 Found Here:
Zephyrus V2 By UD Youde Technology
The Zephyrus V2 by Youde now features an improved top fill design as well as a massive 6mL tank capacity.
Youde integrated a unique design within the device to prevent condensation at the bottom of the unit.
With the ability to use all of the previous Zephyrus coils as well as the option to install an RBA base which has been updated with a larger build deck compared to the version one.
Available in SS and Black.
-Unique design to prevent condensation on the bottom
-Add 1.8ohms OCC head with mouth hit airholes.
-Available with all the coils of Zephyrus series
-With bigger build deck than version one
-Rifling line inside the whole chimney & drip tip,better flavor
-Improved top filling design more convenient
-Capacity of juice : 6ml
Artificial Intelligence – Neurons, Perceptrons, and Neural Networks
Sound levels rebalanced compared to the last upload, and a small visual tweak made. No difference in script or general animation however.
An animated video providing a brief introduction to neurons, perceptrons, and neural networks.
“Jordan: Say we want to get a computer to make decisions. How do we do this? Perceptrons are one answer.
What is a perceptron? The perceptron is a machine learning algorithm for supervised classification of an input into one of several possible non-binary outputs. It is a type of linear classifier, i.e. a classification algorithm that makes its predictions based on a linear predictor function combining a set of weights with the feature vector describing a given input using the delta rule. The learning algorithm for perceptrons is an online algorithm, in that it processes elements in the training set one at a time.
Wait… this is getting too technical. Why don’t we start over…
Albert Einstein was once quoted with the saying, “Look deep into nature, and then you will understand everything better.” And so, AI researchers tend to look to nature as a template for how to create their intelligent systems. This is the case with perceptrons. A perceptron is an artificial representation of a neuron, similar in function to neurons in the brain. In an actual brain, neurons receive information from the outside world through the five senses and encode this into electrical signals. These signals are fed as input into some of these neurons, like input into a program. If the electrical input breaks the neuron’s internal threshold, the neuron will fire, sending signals to other neurons. Researchers designed the perceptron to emulate this behavior. In a perceptron, we have several inputs, a threshold function, and several outputs. These inputs are binary, in that they can either be on or off, and they’re weighted based on their relative importance. When the perceptron receives input, it sums up the weights of all the inputs that are on. If this sum exceeds the pre-specified threshold, then the perceptron will “fire” by activating its outputs.
Ryan: But this is only half of the story. The neuron itself is rather simple, so where does the vast complexity of the brain come from? How, from this simple act of firing, can we get emotion, personality, even consciousness? It’s in the way the neurons themselves are connected. The brain is made up of 100 billion neurons and over 1000 trillion connections, and these connections are constantly changing. The ability of the brain to change its own structure allows a person to learn, create memories, and change the way they act in the future. And so, to achieve this kind of complexity with perceptrons, we connect them together. Most of the time, the perceptron’s outputs feed into another perceptron’s input, thus modeling the interconnectedness of neurons in the brain. And, just like the brain learns by altering the connections between neurons, we can simulate learning in a computer by modifying the connections between the perceptrons based on whether it reaches its specified goal state.
And so, this is a very high level description of the perceptron, how it works, and how it parallels the function of the neuron. If you’re interested in learning more, there’s a lot of great resources out there. Thanks for watching.”
Music Source: https://soundcloud.com/glitchhop/lumberjack-by-paurini
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