96 posts tagged Ai
An intelligent robot equipped with emotion might feel sad at its lack of progress, and eventually give up and do something else. (via Artificial Emotions - Issue 1: What Makes You So Special - Nautilus)
If a robot read a novel, how would it feel? You might get a sense from these little jingles. Below are some songs that were automatically created by a series of algorithms that turn the emotions in novels into short pieces of music. If the songs remind you, traumatically, of your untalented little sister practicing piano… well, you can’t say I didn’t warn you. Actually, the origins of the songs are pretty cool, as the Physics arXiv Blog reports. They start with sentiment analysis, a field in computer science that got hot not long after Twitter did. As more and more people started tweeting, computer scientists and companies wanted to automatically process those tweets, to figure out what emotions people were expressing in them. For example, do people feel negatively or positively about… snack cakes? How do people feel about a specific brand, say, Little Debbie? You can see the commercial interest in this. The same techniques computer scientists use to analyze Twitter are also able read the feels in any text. So now it’s possible to automatically read the emotions in novels, too. To make the songs below, two researchers—one of them a programmer and a musician—went one step beyond that. After running novels through a sentiment-analysis algorithm, they created an algorithm that would express those sentiments through music.
Venture Capital Firm Appoints Machine Intelligence As Board Member
Hong Kong based venture capital firm Deep Knowledge Ventures (DKV) has appointed a machine learning program to its board. Called VITAL, it’s an “equal member” that will uncover trends “not immediately obvious to humans” in order to make investment recommendations. This is probably an attempt to attract media attention, but it could truly be the start of a larger trend; it’s the world’s first software program to be appointed as a board member. The move could also herald a new direction in the way venture capital is done. The tool was developed by Aging Analytics UK who’s licensing it out to DKV, a capital fund that focuses on companies developing therapies for age-related diseases and regenerative medicine. DKV will use VITAL (Validating Investment Tool for Advancing Life Sciences) to analyze financing trends in databases of life science companies in an effort to predict successful investments. It works by poring over massive data sets and applying machine learning to predict which life science companies will make successful investments. The company has already used VITAL to inform investment decisions in two start-up life science companies, Pathway Pharmaceuticals, Limited in Hong Kong and InSilico Medicine, Inc in Baltimore, USA. The long-term goal is to get the intelligence to the stage where it’ll be capable of autonomously allocating an investment portfolio. Eventually, the software is expected to get an equal vote on investment decisions. (via Venture Capital Firm Appoints Machine Intelligence As Board Member)
The Mystery of Go, the Ancient Game That Computers Still Can’t Win
The challenge is daunting. In 1994, machines took the checkers crown, when a program called Chinook beat the top human. Then, three years later, they topped the chess world, IBM’s Deep Blue supercomputer besting world champion Garry Kasparov. Now, computers match or surpass top humans in a wide variety of games: Othello, Scrabble, backgammon, poker, even Jeopardy. But not Go. It’s the one classic game where wetware still dominates hardware. Invented over 2500 years ago in China, Go is a pastime beloved by emperors and generals, intellectuals and child prodigies. Like chess, it’s a deterministic perfect information game — a game where no information is hidden from either player, and there are no built-in elements of chance, such as dice.1 And like chess, it’s a two-person war game. Play begins with an empty board, where players alternate the placement of black and white stones, attempting to surround territory while avoiding capture by the enemy. That may seem simpler than chess, but it’s not. When Deep Blue was busy beating Kasparov, the best Go programs couldn’t even challenge a decent amateur. And despite huge computing advances in the years since — Kasparov would probably lose to your home computer — the automation of expert-level Go remains one of AI’s greatest unsolved riddles. (via The Mystery of Go, the Ancient Game That Computers Still Can’t Win | Enterprise | WIRED)
But What Would the End of Humanity Mean for Me?
Preeminent scientists are warning about serious threats to human life in the not-distant future, including climate change and superintelligent computers. Most people don’t care.
Sometimes Stephen Hawking writes an article that both mentions Johnny Depp and strongly warns that computers are an imminent threat to humanity, and not many people really care. That is the day there is too much on the Internet. (Did the computers not want us to see it?) Hawking, along with MIT physics professor Max Tegmark, Nobel laureate Frank Wilczek, and Berkeley computer science professor Stuart Russell ran a terrifying op-ed a couple weeks ago in The Huffington Post under the staid headline “Transcending Complacency on Superintelligent Machines.” It was loosely tied to the Depp sci-fi thriller Transcendence, so that’s what’s happening there. “It’s tempting to dismiss the notion of highly intelligent machines as mere science fiction,” they write. “But this would be a mistake, and potentially our worst mistake in history.” And then, probably because it somehow didn’t get much attention, the exact piece ran again last week in The Independent, which went a little further with the headline: “Transcendence Looks at the Implications of Artificial Intelligence—but Are We Taking A.I. Seriously Enough?” Ah, splendid. Provocative, engaging, not sensational. But really what these preeminent scientists go on to say is not not sensational. “An explosive transition is possible,” they continue, warning of a time when particles can be arranged in ways that perform more advanced computations than the human brain. “As Irving Good realized in 1965, machines with superhuman intelligence could repeatedly improve their design even further, triggering what Vernor Vinge called a ‘singularity.’” Get out of here. I have literally a hundred thousand things I am concerned about at this exact moment. Do I seriously need to add to that a singularity? (via But What Would the End of Humanity Mean for Me? - James Hamblin - The Atlantic)
The rise of the thinking machines
At the intersection of Big Data and artificial intelligence computers are quickly beginning to rival the decision making power of humans. While the technology has the capacity to offer vast improvements in precision and efficiency it also raises questions about how much responsibility should be ceded to machines and what humans’ role will be in the future workplace. (via The rise of the thinking machines - E & T Magazine)
For the French philosopher Paul Virilio, technological development is inextricable from the idea of the accident. As he put it, each accident is ‘an inverted miracle… When you invent the ship, you also invent the shipwreck; when you invent the plane, you also invent the plane crash; and when you invent electricity, you invent electrocution.’ Accidents mark the spots where anticipation met reality and came off worse. Yet each is also a spark of secular revelation: an opportunity to exceed the past, to make tomorrow’s worst better than today’s, and on occasion to promise ‘never again’.
Will humankind become obsolete?
The main fear about the very image of machines replacing humans is the one of mankind obsolescence. This idea that our civilization will evolve into a world like Matrix, where we would be relegated to a mere peripheral equipment became incapable of managing its destiny. But as illustrated by Erik Brynjolfsson and Andrew McAfee in “Race Against The Machine”, this feeling of an obsolescent humanity is linked to a vision of humans competing against the machine instead of man working with it. The question is to define this “with” and which concepts it underlies? Classical notion of tools external and fully subdue to man probably lived with the arrival of autonomous machines. A concept that may emerge is “partnership”. After having been for centuries a simple tool, our machines would become associated with us; and thus this manmachine duo creation, made effective by osmosis between our animal adaptability and digital speed and highprecision, will allow both sides to find a new place and prosper. Another way is the idea of anthropotechny,(11) working directly on bodies to the point of permanently blurring distinction between man and machine. This is of course a longerterm prospective vision and in a more practical and immediate point of view, what can be done when we see autonomous systems outperform humans in such a specific domain as medical diagnosis?
A recent study investigates how readers perceive computer-generated news articles. The advent of new technologies has always spurred questions about changes in journalism — how it is produced and consumed. A recent development which has come to the fore in the digital world is software-generated content. A recent article investigates how readers perceive automatically produced news articles vs. articles which have been written by a journalist.
The results suggest that the journalist-authored content was observed to be coherent, well-written and pleasant to read. However, while the computer generated content was perceived as descriptive and boring, it was also considered to be objective and trustworthy. Overall readers found it difficult to tell which articles had been written by journalists, and which were software-generated.
Perhaps most significant in Clerwall’s study is the discovery that there were no substantial differences in how the different articles were perceived by readers. Does that mean that computer robots are capable of doing as good a job as journalists? Should journalists be considering a career change just yet? There are certainly advantages to be had in the speed with which computer-generated content can be produced, but will a robot writer ever be able to match the creativity, flexibility and analysis of journalist authored articles? The technology in place may not be quite able to reach these levels of sophisticated reporting yet, but it certainly provides food for thought as to how automated content might influence journalism in the future.