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Math

Machine Learning Could Solve Economists' Math Problem 153

An anonymous reader writes: Noah Smith argues that the field of economics frequently uses math in an unhealthy way. He says many economists don't use math as a tool to describe reality, but rather as an abstract foundation for whatever theory they've come up with. A possible solution to this, he says, is machine learning: "In other words, econ is now a rogue branch of applied math. Developed without access to good data, it evolved different scientific values and conventions. But this is changing fast, as information technology and the computer revolution have furnished economists with mountains of data. As a result, empirical analysis is coming to dominate econ. ... [Two economists pushing this change] stated that machine learning techniques emphasized causality less than traditional economic statistical techniques, or what's usually known as econometrics. In other words, machine learning is more about forecasting than about understanding the effects of policy. That would make the techniques less interesting to many economists, who are usually more concerned about giving policy recommendations than in making forecasts."
Communications

Ashley Madison Source Code Shows Evidence They Created Bots To Message Men 309

An anonymous reader writes: Gizmodo's Annalee Newitz looked through the source code contained in the recent Ashley Madison data dump and found evidence that the company created tens of thousands of bot accounts designed to spur their male users into action by sending them messages. "The code tells the story of a company trying to weave the illusion that women on the site were plentiful and eager." The evidence suggests bots sent over 20 million messages on the website, and chatted with people over 11 million times. The vast majority of fake accounts — 70,529 to 43 — pretended to be female, and the users targeted were almost entirely men. Comments left in the code indicate some of the issues Ashley Madison's engineers had to solve: "randomizing start time so engagers don't all pop up at the same time" and "for every single state that has guest males, we want to have a chat engager." The AI was unsophisticated, though one type of bot would try to convince men to pay and then pass them to a real person.
AI

How Artificial Intelligence Can Fight Air Pollution In China 50

An anonymous reader writes: IBM is testing a new way to help fix Beijing's air pollution problem with artificial intelligence. Like many other cities across the country, the capital is surrounded by many coal burning factories. However, the air quality on a day-to-day basis can vary because of a number of reasons like industrial activity, traffic congestion, and the weather. IBM is testing a computer system capable of learning to predict the severity of air pollution several days in advance using large quantities of data from several different models. "We have built a prototype system which is able to generate high-resolution air quality forecasts, 72 hours ahead of time," says Xiaowei Shen, director of IBM Research China. "Our researchers are currently expanding the capability of the system to provide medium- and long-term (up to 10 days ahead) as well as pollutant source tracking, 'what-if' scenario analysis, and decision support on emission reduction actions."
Programming

Deep Learning Pioneer On the Next Generation of Hardware For Neural Networks 45

An anonymous reader writes: While many recognize Yann LeCun as the father of convolutional neural networks, the momentum of which has ignited artificial intelligence at companies like Google, Facebook and beyond, LeCun has not been strictly rooted in algorithms. Like others who have developed completely new approaches to computing, he has an extensive background in hardware, specifically chip design and this recognition of specialization of hardware, movement of data around complex problems, and ultimately core performance, has proven handy. He talks in depth this week about why FPGAs are coming onto the scene as companies like Google and Facebook seek a move away from "proprietary hardware" and look to "programmable devices" to do things like, oh, say, pick out a single face of one's choosing from an 800,000 strong population in under five seconds.
Facebook

Facebook Is Now Working On Its Own Digital Assistant Called M 56

Mark Wilson writes: Sounding like a character from a James Bond movie, M is Facebook's personal digital assistant. Ready to compete with the likes of Cortana, M will live inside Facebook Messenger and take artificial intelligence a step further. Rather than just helping you to find information or create calendar entries, M will actually perform tasks on your behalf.

Once up and running, M will be able to book restaurants for you, purchase shopping, and more. It will also be possible to use the service to ask for advice — such as looking for somewhere to visit nearby, or gift suggestions — and Facebook says the AI behind M is "trained and supervised by people".
Robotics

Video More From Tim O'Reilly about the 'WTF?!' Economy (Videos) 61

More From Tim O'Reilly about the 'WTF?!' Economy (Video) On August 12 we ran two videos of Tim O'Reilly talking with Slashdot's Tim Lord about changes in how we work, what jobs we do, and who profits from advances in labor-saving technology. Tim (O'Reilly, that is) had written an article titled, The WTF Economy, which contained this paragraph:

"What do on-demand services, AI, and the $15 minimum wage movement have in common? They are telling us, loud and clear, that we’re in for massive changes in work, business, and the economy."

We're seeing a shift from cabs to Uber, but what about the big shift when human drivers get replaced by artificial intelligence? Ditto airplane pilots, burger flippers, and some physicians. WTF? Exactly. Once again we have a main video and a second one available only in Flash (sorry about that), along with a text transcript that covers both videos. Good thought-provoking material, even if you think you're so special that no machine could possibly replace you.
AI

IBM 'TrueNorth' Neuro-Synaptic Chip Promises Huge Changes -- Eventually 97

JakartaDean writes: Each of IBM's "TrueNorth" chips contains 5.4 billion transistors and runs on 70 milliwatts. The chips are designed to behave like neurons—the basic building blocks of biological brains. Dharmenda Modha, the head of IBM's cognitive computing group, says a system of 24 connected chips simulates 48 million neurons, roughly the same number rodents have.

Whereas conventional chips are wired to execute particular "instructions," the TrueNorth juggles "spikes," much simpler pieces of information analogous to the pulses of electricity in the brain. Spikes, for instance, can show the changes in someone's voice as they speak—or changes in color from pixel to pixel in a photo. "You can think of it as a one-bit message sent from one neuron to another." says one of the chip's chief designers. The chips are designed well not for training neural networks, but for executing them. This has significant implications for consumer AI: big companies with lots of resources could focus on the training, which individual TrueNorth chips in people's gadgets could handle the execution.
Google

Google Research Leads To Automated Real-Time Pedestrian Detection 57

An anonymous reader writes with a link to a story about one of the unexciting but vital bits of technology that will need to be even further developed as autonomous cars' presence grows: making sure that those cars don't hit people. Google researchers have recently presented findings about a method that tops previous ones for real-time pedestrian detection using neural nets "that is both extremely fast and extremely accurate." From the article: There are other approaches that provide a real-time solution on the GPU but in doing so, have not achieved accuracy targets (in this real-time approach there was a miss rate of 42% on the Caltech pedestrian detection benchmark). Another approach called the VeryFast method can run at 100 frames per second (compared to the Google team's 15) but the miss rate is even greater. Others that emphasize accuracy, even with GPU acceleration, are up to 195 times slower.
AI

Video Tim O'Reilly and the 'WTF?!' Economy (Video) 111

This is a conversation Tim Lord had with Tim O'Reilly at OSCON. Tim O'Reilly wrote an article titled "The WTF Economy,", which started with these words: "WTF?! In San Francisco, Uber has 3x the revenue of the entire prior taxi and limousine industry." He talks about Uber and AirbnB and how, with real-time measurement of customer demand, "The algorithm is the new shift boss." And then there is this question: "What is the future when more and more work can be done by intelligent machines instead of people, or only done by people in partnership with those machines?"

My (late) father was an engineer. Politically, you could have called him a TechnoUtopian. He believed -- along with most of his engineer, ham radio, and science fiction writer and reader friends -- that as machines took over the humdrum tasks, humans would work less and create more. O'Reilly seems to have similar beliefs, even though (unlike my father) he's seen the beginnings of an economy with self-driving cars and trucks, factory machines that don't need humans to run them, and many other changes the 1950s and 1960s futurists didn't expect to see until we had flying cars and could buy tickets on Pan Am flights to the moon. Listening to these conversations, I remember my father's dreams, but O'Reilly isn't as optimistic as a full-blown TechnoUtopian. He takes a "Something's happening here; what it is ain't exactly clear" view of how work (and pay for work) will change in the near future. Please note that Tim O'Reilly has been called "The Oracle of Silicon Valley," so he's totally worth watching -- or reading, if that's your preferred method of taking in new information.

NOTE: Today we have a "main video," plus a "bonus video" that is viewable only with Flash. But we have a transcript that covers both of them. Enjoy!
AI

Microsoft Creates an AI That Can Spot a Joke In a New Yorker Cartoon 66

An anonymous reader writes: For over a decade Bob Mankoff, the cartoon editor at the New Yorker, and his assistants have gone through 5,000 cartoon entries for the magazine's caption contest each week. Needless to say, the burnout rate of his assistants is quite high, "The process of looking at 5,000 caption entries a week usually destroys their mind in about two years, and then I get a new one," Mankoff says. But now thanks to a collaboration with Microsoft, Bob may finally have found the perfect helper. Researchers have been working on an artificial intelligence project to teach a computer what's funny. Fortune reports: "Dafna Shahaf, a researcher at Microsoft, used the database of cartoons to train the program to understand commonalities and differences in the millions of cartoons, which lets the AI run through the entries the New Yorker receives each week for its back-of-magazine cartoon caption contest. About 55.8% of the time the humans agree with the captions the AI selects, which is a pretty good percentage."
AI

IBM Drops $1 Billion On Medical Images For Watson 53

An anonymous reader writes: IBM is purchasing a company called Merge Healthcare for $1 billion. The company specializes in medical imaging software, and it will be a key new resource for IBM's Watson AI. Big blue's researchers estimate that 90% of all medical data is contained within images. Having a trove of them and the software to mine that data should help Watson learn how to make more accurate diagnoses. IBM thinks it'll also provide better context for run-of-the-mill medical imaging. "[A] radiologist might examine thousands of patient images a day, but only looking for abnormalities on the images themselves rather than also taking into account a person's medical history, treatments and drug regimens." They can program Watson to do both. The AI is already landing contracts to assist with medical issues: "Last week, IBM announced a partnership with CVS Health, the large pharmacy chain, to develop data-driven services to help people with chronic ailments like diabetes and heart disease better manage their health."
AI

Will Robot Cabs Unjam the Streets? 280

An anonymous reader writes: The Atlantic has a story with some video of a traffic simulator showing just how the roads can be jammed up by people looking for a place to park. (You can play with the simulator too.) This has been suspected for a long time by many traffic researchers and city planners, but the simulator shows just how quickly the roads jam up after just a few of the blocks fill up with parked cars. The good news is that autonomous cars don't need to park-- they just go give someone else a ride. They could change city life forever.
AI

Apple Testing Service That Allows Siri to Answer Calls and Transcribe Voicemail 70

An anonymous reader writes: Apple is reportedly testing a new feature which would allow Siri to answer your calls and then transcribe the voicemails as text messages. The iCloud service would then send users the text of that transcribed voicemail. Apple employees are testing a voicemail service currently and a public release isn't expected until sometime in 2016 in iOS10.
AI

Answering Elon Musk On the Dangers of Artificial Intelligence 262

Lasrick points out a rebuttal by Stanford's Edward Moore Geist of claims that have led the recent panic over superintelligent machines. From the linked piece: Superintelligence is propounding a solution that will not work to a problem that probably does not exist, but Bostrom and Musk are right that now is the time to take the ethical and policy implications of artificial intelligence seriously. The extraordinary claim that machines can become so intelligent as to gain demonic powers requires extraordinary evidence, particularly since artificial intelligence (AI) researchers have struggled to create machines that show much evidence of intelligence at all.
AI

A Computer Umpires Its First Pro Baseball Game 68

An anonymous reader writes: Baseball has long been regarded as a "game of inches." Among the major professional sports it arguably requires the greatest amount of precision — a few extra RPMs can turn a decent curveball into an unhittable one, and a single degree's difference in the arc of a bat swing can change a lazy popup into a home run. As sensor technology has improved, it's been odd to see how pro baseball leagues have made great efforts to keep it away from the sport. Even if you aren't a fan of the game, you're probably familiar with the cultural meme of an umpire blowing a key call and altering the course of the game.

Thus, it's significant that for the first time ever, sensors and a computer have called balls and strikes for a professional game. In a minor league game between the San Rafael Pacifics and the Vallejo Admirals, a three-camera system tracked the baseball's exact position as it crossed home plate, and a computer judged whether it was in the strike zone or not. The game went without incident, and it provided valuable data in a real-life example. The pitch-tracking system still has bugs to work out, though. Dan Brooks, founder of a site that tracks ball/strike accuracy for real umpires, said that for the new system to be implemented permanently, fans must be "willing to accept a much smaller amount of inexplicable error in exchange for a larger amount of explicable error."
AI

Musk, Woz, Hawking, and Robotics/AI Experts Urge Ban On Autonomous Weapons 313

An anonymous reader writes: An open letter published by the Future of Life Institute urges governments to ban offensive autonomous weaponry. The letter is signed by high profile leaders in the science community and tech industry, such as Elon Musk, Stephen Hawking, Steve Wozniak, Noam Chomsky, and Frank Wilczek. It's also signed — more importantly — by literally hundreds of expert researchers in robotics and AI. They say, "The key question for humanity today is whether to start a global AI arms race or to prevent it from starting. If any major military power pushes ahead with AI weapon development, a global arms race is virtually inevitable, and the endpoint of this technological trajectory is obvious: autonomous weapons will become the Kalashnikovs of tomorrow. Unlike nuclear weapons, they require no costly or hard-to-obtain raw materials, so they will become ubiquitous and cheap for all significant military powers to mass-produce."
AI

A Programming Language For Self-Organizing Swarms of Drones 56

New submitter jumpjoe writes: Drones are becoming a staple of everyday news. Drone swarms are the natural extension of the drone concept for applications such as search and rescue, mapping, and agricultural and industrial monitoring. A new programming language, compiler, and virtual machine were recently introduced to specify the behaviour of an entire swarm with a single program. This programming language, called Buzz, allows for self-organizing behaviour to accomplish complex tasks with simple program. Details on the language and examples are available here. Full disclosure: I am one of the authors of the paper.
AI

Which Movies Get Artificial Intelligence Right? 236

sciencehabit writes: Hollywood has been tackling Artificial Intelligence for decades, from Blade Runner to Ex Machina. But how realistic are these depictions? Science asked a panel of AI experts to weigh in on 10 major AI movies — what they get right, and what they get horribly wrong. It also ranks the movies from least to most realistic. Films getting low marks include Chappie, Blade Runner, and A.I.. High marks: Bicentennial Man, Her, and 2001: a Space Odyssey.
AI

Taking the Lawyers Out of the Loop 116

An Associated Press story carried by the Christian Science Monitor suggests that expert systems can already replace lawyers in a great many disputes (especially low-level ones, where the disputants don't need or don't want to see each other), and the realm of legal expertise that can be embodied in silicon will only grow. The article spends most of its time on Modria, a company whose software is being used in Ohio to "resolve disputes over tax assessments and keep them out of court, and a New York-based arbitration association has deployed it to settle medical claims arising from certain types of car crashes," but mentions a few others as well. Modria's software has also been used to negotiate hundreds of divorces in the Netherlands, including ones with areas of dispute: "If they reach a resolution, they can print up divorce papers that are then reviewed by an attorney to make sure neither side is giving away too much before they are filed in court."
Patents

Google Applies For Patents That Touch On Fundamental AI Concepts 101

mikejuk writes: Google may have been wowing the web with its trippy images from neural networks but meanwhile it has just revealed that it has applied for at least six patents on fundamental neural network and AI [concepts]. This isn't good for academic research or for the development of AI by companies. The patents are on very specific things invented by Geoffrey Hinton's team like using drop out during training, or modifying data to provide additional training cases, but also include very general ideas such as classification itself. If Google was granted a patent on classification it would cover just about every method used for pattern recognition! You might make the charitable assumption that Google has just patented the ideas so that it can protect them — i.e. to stop other more evil companies from patenting them and extracting fees from open source implementations of machine learning libraries. Google has just started an AI arms race, and you can expect others to follow.