The augmented-reality game "Pokémon Go" may be the hottest thing in mobile gaming right now, but new advances in computer science could give players an even more realistic experience in the future, according to a new study. In fact, researchers say a new imaging technique could help make imaginary characters, such as Pokémon, appear to convincingly interact with real objects.
A new imaging technique called Interactive Dynamic Video can take pictures of real objects and quickly create video simulations that people, or 3D models, can virtually interact with, the researchers said. In addition to fueling game development, these advances could help simulate how real bridges and buildings might respond to potentially disastrous situations, the researchers added.
The smartphone game "Pokémon Go" superimposes images onto the real world to create a mixed reality. The popularity of this game follows a decades-long trend of computer-generated imagery weaving its way into movies and TV shows. However, while 3D models that can move amid real surroundings on video screens are now commonplace, it remains a challenge getting computer-generated images to look as if they are interacting with real objects. Building 3D models of real items is expensive, and can be nearly impossible for many objects, the researchers said. [Beyond Gaming: 10 Other Fascinating Uses for Virtual-Reality Tech]
Now, Interactive Dynamic Video could bridge that gap, the researchers said.
"When I came up with and tested the technique, I was surprised that it worked quite so well," said study lead author Abe Davis, a computer scientist at the Computer Science and Artificial Intelligence Laboratory at the Massachusetts Institute of Technology.
Technological shifts outpace our awareness of them. While we're busy with our day-to-day lives—getting a new smartphone or downloading the next updates—we often don't notice how these incremental changes shape our relationship with technology. According to Ray Kurzweil, this trend will continue as we become more closely integrated with the tech around us.
“At some point, we’ll be literally a hybrid of biological and nonbiological thinking, but it's a gradual transition,” Kurzweil says.
Instead of happening overnight, he predicts we’ll steadily enhance ourselves using technology, not by replacing the parts that make us human but by building on them over time.
One of the biggest concerns people express about this idea is the fear of losing one’s body or mind in the process—that we’ll become less and less human in the future.
“I don’t want to give that up. I’m not talking about giving things up,” Kurzweil says. “I’m talking about enhancing our experience and our bodies and our brains.”
He likens this process to what happens as we grow and change through life. At what point do we cease to be our "old selves" and become our "new selves"? There isn’t a clear line. We change and grow incrementally. And day to day, those incremental changes aren’t obvious.
“You’re not the same person you were when you were four years old—where is that four-year-old girl? Is she gone, should we mourn her? Well, no, she’s contained in you. You’ve enhanced yourself to become who you are today,” Kurzweil argues.
One thing is clear: Most of us rarely go a day without technology. What do you think will happen in the coming years? Will we become even more closely tied to our tools? Should we?
Engineers from the universities of Sheffield and Sussex are planning on scanning the brains of bees and uploading them into autonomous flying robots that will then fly and act like the real thing.
Bionic bees -- or perhaps that should be "beeonic" -- could, it is hoped, be used for a range of situations where tiny thinking flying machines should be more useful than current technology, which might mean seeking out gas or chemical leaks, or people who are trapped in small spaces. They might even help pollinate plants in places where natural bee populations have fallen due to the still-mysterious Colony Collapse Disorder.
It's important to note that this won't be an entirely comprehensive model of a bee's brain -- it's only going to be the parts associated with its sense of smell and vision. These modules will be melded with other software to form what the team call a "
Green Brain", one that can react to new situations and improvise rapidly just like a "real" animal or insect brain.
Oxford philosopher Nick Bostrom, in his recent and celebrated book Superintelligence: Paths, Dangers, Strategies, argues that advanced AI poses a potentially major existential risk to humanity, and that advanced AI development should be heavily regulated and perhaps even restricted to a small set of government-approved researchers.
Bostrom’s ideas and arguments are reviewed and explored in detail, and compared with the thinking of three other current thinkers on the nature and implications of AI: Eliezer Yudkowsky of the Machine Intelligence Research Institute (formerly Singularity Institute for AI), and David Weinbaum (Weaver) and Viktoras Veitas of the Global Brain Institute. Relevant portions of Yudkowsky’s book Rationality: From AI to Zombies are briefly reviewed, and it is found that nearly all the core ideas of Bostrom’s work appeared previously or concurrently in Yudkowsky’s thinking.
However, Yudkowsky often presents these shared ideas in a more plain-spoken and extreme form, making clearer the essence of what is being claimed. For instance, the elitist strain of thinking that one sees in the background in Bostrom is plainly and openly articulated in Yudkowsky, with many of the same practical conclusions (e.g., that it may well be best if advanced AI is developed in secret by a small elite group).
Bostrom and Yudkowsky view intelligent systems through the lens of reinforcement learning — they view them as “reward-maximizers” and worry about what happens when a very powerful and intelligent reward-maximizer is paired with a goal system that gives rewards for achieving foolish goals, like tiling the universe with paperclips. Weinbaum and Veitas’s recent paper “Open-Ended Intelligence” presents a starkly alternative perspective on intelligence, viewing it as centered not on reward maximization, but rather on complex self-organization and self-transcending development that occurs in close coupling with a complex environment that is also ongoingly self-organizing, in only partially knowable ways.
It is concluded that Bostrom and Yudkowsky’s arguments for existential risk have some logical foundation, but are often presented in an exaggerated way. For instance, formal arguments whose implication is that the “worst case scenarios” for advanced AI development are extremely dire are often informally discussed as if they demonstrated the likelihood, rather than just the possibility, of highly negative outcomes. And potential dangers of reward-maximizing AI are taken as problems with AI in general, rather than just as problems of the reward-maximization paradigm as an approach to building superintelligence.
If one views past, current, and future intelligence as “open-ended,” in the vernacular of Weaver and Veitas, the potential dangers no longer appear to loom so large, and one sees a future that is wide-open, complex and uncertain, just as it has always been.
One day in the future, we’ll look back in wonder at how our physical objects used to be singular, disconnected pieces of matter.
We’ll be in awe of the fact that a car used to be just a piece of metal full of gears and belts that we would drive from one place to another, that a refrigerator was a box that kept our food cold — and a phone was a piece of plastic we used to communicate to one other person at a time.
That’s because the future we’re rapidly moving towards is one where physical items become intelligent and interconnected — and as a fascinating result, their functionality changes.
There is probably no better example of this trend than the cell phone. The mobile phone used to be just that — a mobile phone. Now it’s your flashlight, your bank, your TV, and your funny, yet kind of dumb personal assistant. The cell phone — or really, more accurately, the hand-held computer — has become mostly a gateway to all the mobile services we use on it.
And those services are constantly morphing and improving, changing what our smartphones can do without requiring the physical phone itself to change all that much at all.
Is creativity a uniquely human trait? What about self-awareness or intuition?
Defining the line between human and machine is becoming blurrier by the day as startups, big companies, and research institutions all compete to build the next generation of advanced AI.
This arms race is bringing a new era of AI that won’t prove its power by mastering human games, but by independently exhibiting ingenuity and creativity.
Sophisticated AI is undertaking increasingly complex tasks like stock market predictions, research synthesis, political speech writing—don’t worry, this article was still written by a human—and companies are beginning to pair deep learning with new robotics and digital manufacturing tools to create “smart manufacturing.”
It was hailed as the most significant test of machine intelligence since Deep Blue defeated Garry Kasparov in chess nearly 20 years ago. Google’s AlphaGo has won two of the first three games against grandmaster Lee Sedol in a Go tournament, showing the dramatic extent to which AI has improved over the years. That fateful day when machines finally become smarter than humans has never appeared closer—yet we seem no closer in grasping the implications of this epochal event.
Combining synthetic biology approaches with time-lapse movies, a team led by Caltech biologists has determined how some proteins shape a cell's ability to remember particular states of gene expression.
What if we could program living cells to do what we would like them to do in the body? Having such control—a major goal of synthetic biology—could allow for the development of cell-based therapies that might one day replace traditional drugs for diseases such as cancer. In order to reach this long-term goal, however, scientists must first learn to program many of the key things that cells do, such as communicate with one another, change their fate to become a particular cell type, and remember the chemical signals they have encountered.
Now a team of researchers led by Caltech biologists Michael Elowitz, Lacramioara Bintu, and John Yong (PhD '15) have taken an important step toward being able to program that kind of cellular memory using tools that cells have evolved naturally. By combining synthetic biology approaches with time-lapse movies that track the behaviors of individual cells, they determined how four members of a class of proteins known as chromatin regulators establish and control a cell's ability to maintain a particular state of gene expression—to remember it—even once the signal that established that state is gone.
The researchers reported their findings in the February 12 issue of the journal Science.
Among dance forms, tango holds a unique and potent allure. It showcases two individuals—each with a separate mind, body, and bundle of goals and intentions, moving at times in close embrace, at times stepping away from each other, improvising moves and flourishes while responding to the imaginative overtures of the other—who somehow manage to give the impression of two bodies answering to a single mind. For performers and viewers alike, much of tango’s appeal comes from this apparent psychic fusion into a super-individual unit. Michael Kimmel, a social and cultural anthropologist who has researched the interpersonal dynamics of tango, writes that dancers “speak in awe of the way that individuality dissolves into a meditative unity for the three minutes that the dance lasts. Time and space give way to a unique moment of presence, of flow within and between partners.”
Tango offers more than aesthetic bliss; like all artistic practices that demand great skill, it also presents a seductive scientific puzzle, highlighting the mind’s potential to learn and re-shape itself in dramatic ways. But it’s only very recently that scientists have started building a systematic framework to explain how a person might achieve the sort of fusion that is needed for activities like social dancing, and what the impact of such an interpersonal entanglement might be.
At the heart of the puzzle is the notion of a body schema—a mental representation of the physical self that allows us to navigate through space without smashing into things, to scratch our nose without inadvertently smacking it, and to know how far and how quickly to reach for a cup of coffee without knocking it over. We can do all these things because our brains have learned to identify the edges of our bodies using information from multiple senses and devote exquisite attention to stimuli near our bodily boundaries.
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