In his 1854 book, Walden, Henry David Thoreau wrote, “Men have become the tools of their tools.” Thoreau’s assertion is as valid today as it was when he made it over one hundred and sixty years ago. Whenever we shape technology, it shapes us, both as individuals and as a society. We created cars, and cars turned us into motorists, auto mechanics, and commuters.
Over the centuries we’ve populated our world with machines that help us do things we can’t or don’t want to do ourselves. Our world has become so saturated with machines that they’ve faded into the background. We hardly notice them. We are reaching a new threshold. Our machines are getting networked, and enabling new forms of human machine symbiosis. We’re entering a new era where fifty billion machines are in constant communication, automating and orchestrating the movement and interactions among individuals, organizations, and cities.
Institute for the Future (IFTF) is a non-profit think tank in Silicon Valley, that helps organizations and the public think about long term future plans to make better decisions in the present. Mark Frauenfelder, a research director at IFTF interviewed Rod Falcon, IFTF’s Director of the Technology Horizons Program, which combines a deep understanding of technology and societal forces, to identify and evaluate these discontinuities and innovations in the near future. Rod discussed Tech Horizon’s recent research into how machine automation is becoming an integrated, embedded, and ultimately invisible part of virtually every aspect of our lives. Read the rest
The Allen Institute for Artificial Intelligence (AI2), funded by billionaire Paul Allen's, is developing projects like an AI-based search engine for scientific papers and a system to extract "visual knowledge" from images and videos. According to Scientific American, another goal of AI2 is "to counter messages perpetuated by Hollywood and even other researchers that AI could menace the human race." SciAm's Larry Greenemeier interviewed AI2 CEO and computer scientist Oren Etzioni:
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Why do so many well-respected scientists and engineers warn that AI is out to get us?
It’s hard for me to speculate about what motivates somebody like Stephen Hawking or Elon Musk to talk so extensively about AI. I’d have to guess that talking about black holes gets boring after awhile—it’s a slowly developing topic. The one thing that I would say is that when they and Bill Gates—someone I respect enormously—talk about AI turning evil or potential cataclysmic consequences, they always insert a qualifier that says “eventually” or this “could” happen. And I agree with that. If we talk about a thousand-year horizon or the indefinite future, is it possible that AI could spell out doom for the human race? Absolutely it’s possible, but I don’t think this long-term discussion should distract us from the real issues like AI and jobs and AI and weapons systems. And that qualifier about “eventually” or “conceptually” is what gets lost in translation...
How do you ensure that an AI program will behave legally and ethically?
If you’re a bank and you have a software program that’s processing loans, for example, you can’t hide behind it.
A group of some of the most powerful technology companies on the planet have formed a partnership on artificial intelligence.
My friend and Cool Tools partner Kevin Kelly was interviewed about his book, The Inevitable. In this video, he discuss what will happen when artificial intelligence is sold like electricity, as a utility.
NPR has a quiz that invites you to guess which of six poems were written by a computer program, and which were written by humans. A group of 10 judges weren't fooled, but I had trouble correctly guessing all of them. I appreciated the computer-generated poems as much as the human-written ones.
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The dirty rusty wooden dresser drawer. A couple million people wearing drawers, Or looking through a lonely oven door, Flowers covered under marble floors.
And lying sleeping on an open bed. And I remember having started tripping, Or any angel hanging overhead, Without another cup of coffee dripping.
Surrounded by a pretty little sergeant, Another morning at an early crawl. And from the other side of my apartment, An empty room behind the inner wall.
A thousand pictures on the kitchen floor, Talked about a hundred years or more.
Researchers from MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL) trained a neural network to recognize materials (e.g., metal grate, plants, concrete sidewalk) being hit with a drumstick, and synthesize sounds to accompany the actions. It did well enough to fool humans into thinking the sounds were real. From the abstract:
Objects make distinctive sounds when they are hit or scratched. These sounds reveal aspects of an object's material properties, as well as the actions that produced them. In this paper, we propose the task of predicting what sound an object makes when struck as a way of studying physical interactions within a visual scene. We present an algorithm that synthesizes sound from silent videos of people hitting and scratching objects with a drumstick. This algorithm uses a recurrent neural network to predict sound features from videos and then produces a waveform from these features with an example-based synthesis procedure. We show that the sounds predicted by our model are realistic enough to fool participants in a "real or fake" psychophysical experiment, and that they convey significant information about material properties and physical interactions.
This 'Trump Deep Nightmare' video is insane. Insanely accurate, that is. Don't watch while using psychedelic drugs, unless highly experienced.
MIT professor Marvin Minsky, a "founding father" of the field of artificial intelligence whose work opened up new vistas in computer science, cognitive psychology, philosophy, robotics, and optics, has died of a brain hemorrhage. He was 88.
In 1959, Minsky co-founded MIT's Artificial Intelligence Laboratory (now the Computer Science and Artificial Intelligence Laboratory) and dedicated his career to exploring how we might replicate the functions of the human brain in a machine, a research journey he hoped would help us better understand our own minds.
"No computer has ever been designed that is ever aware of what it's doing," Minsky once said. "But most of the time, we aren't either."
What if we could automate the writing of clickbait headlines, thus freeing up clickbait writers to do useful work? That's the question Lars Eidnes wanted to answer when he programmed a recurrent neural network to generate "formulaic and unoriginal" headlines like these: Top Yoga Songs For Halloween How To Make A Classic Cold Cheese Cake Are You Living Without A 5,000-Year-Old Style? Jimmy Kimmel And David Beckham Play A Girl At The San Francisco Comic Con
Eidnes trained the network by feeding it two million headlines scraped from Buzzfeed, Gawker, Jezebel, Huffington Post and Upworthy.
How realistic can we expect the output of this model to be? Even if it can learn to generate text with correct syntax and grammar, it surely can’t produce headlines that contain any new knowledge of the real world? It can’t do reporting? This may be true, but it’s not clear that clickbait needs to have any relation to the real world in order to be successful. When this work was begun, the top story on BuzzFeed was “50 Disney Channel Original Movies, Ranked By Feminism." More recently they published “22 Faces Everyone Who Has Pooped Will Immediately Recognized." It’s not clear that these headlines are much more than a semi-random concatenation of topics their userbase likes, and as seen in the latter case, 100% correct grammar is not a requirement.
After training the neural network, Eidnes concludes, "It surprised me how good these headlines turned out. Most of them are grammatically correct, and a lot of them even make sense."
The US military's Defense Advanced Research Projects Agency is funding a new project to develop musical robots that can improvise a solo when playing with human jazz musicians. A collaboration between new media researchers at the University of Illinois at Urbana-Champaign and musicians at the University of Arizona, the goal of the MUSICA (Musical Improvising Collaborative Agent) project is to explore non-traditional "languages" for people and computers to interact. From Scientific American:
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"There is definitely a desire for more natural kinds of communications with computational systems as they grow in their ability to be intelligent," Ben Grosser, an assistant professor of new media at the University of Illinois at Urbana-Champaign, told Live Science. "A lot of us are familiar with various methods of interacting with computers, such as text-based and touch-based interfaces, but language-based interfaces such as Siri or Google Now are extremely limited in their capabilities...."
To develop a machine capable of playing improvisational jazz, the researchers will create a database of jazz solos from a variety of musicians and have computers analyze the recordings to figure out the various processes that come into play when a musician improvises. The researchers will then develop a performance system to analyze the components of human jazz performances, including the beat, pitch, harmony and rhythm. The system will also consider what it has learned about jazz solos to communicate and respond musically in real time....
"Let's face it—trying to develop a system that can play jazz is a crazy idea," Grosser said.