University


Making robots see

#artificialintelligence

"There is a fundamental disconnect between what we roboticists say and what the public perceives," says Ian Reid, deputy director of the Australian Centre for Robotic Vision, in Brisbane. And that leads to the heart of the problem, and what researchers mean when they talk about "robotic vision": using cameras to guide robots to carry out tasks in increasingly uncontrolled environments. Is this another of Ian Reid's "disconnects" between the research world and the public's sci-fi driven expectations? "In rich countries like Japan where there are also demographic challenges, you will see a big increase in social robotics – in aged, robotic companions and robotic pets," Mahony predicts.


Facebook heads to Canada in search of the next big AI advance

@machinelearnbot

Several leading figures in AI, including LeCun, have studied or taught at Canadian universities. Reinforcement learning builds on deep learning to let machines learn through experimentation. Michael Bowling, a U.S.-born computer scientist who leads a lab at the University of Alberta that has produced cutting-edge poker-playing machines, says the new Facebook lab simply shows that Canada already leads the rest of the world in AI. Indeed, after seeing AI researchers snapped up by big U.S. companies in recent years, Canada may well hope that the environment fostered by new labs, including the one in Montreal, will eventually produce companies that rival the likes of Facebook.


Facebook opens a new AI research lab in Montreal

#artificialintelligence

The lab will be helmed by Joelle Pineau, a computer science professor at McGill University interested in learning and the co-director of the university's Reasoning and Learning Lab. LeCun says that, like other Facebook AI research labs, the Montreal site will engage with research communities via publications, conferences and collaborations. "Montreal already has an existing fantastic academic AI community, an exciting ecosystem of startups, and promising government policies to encourage AI research. We are excited to become part of this larger community, and we look forward to engaging with the entire ecosystem and helping it continue to thrive," said LeCun.


Amazon has developed an AI fashion designer

#artificialintelligence

The effort points to ways in which Amazon and other companies could try to improve the tracking of trends in other areas of retail--making recommendations based on products popping up in social-media posts, for instance. For instance, one group of Amazon researchers based in Israel developed machine learning that, by analyzing just a few labels attached to images, can deduce whether a particular look can be considered stylish. An Amazon team at Lab126, a research center based in San Francisco, has developed an algorithm that learns about a particular style of fashion from images, and can then generate new items in similar styles from scratch--essentially, a simple AI fashion designer. The event included mostly academic researchers who are exploring ways for machines to understand fashion trends.


Amazon has developed an AI fashion designer

#artificialintelligence

The effort points to ways in which Amazon and other companies could try to improve the tracking of trends in other areas of retail--making recommendations based on products popping up in social-media posts, for instance. For instance, one group of Amazon researchers based in Israel developed machine learning that, by analyzing just a few labels attached to images, can deduce whether a particular look can be considered stylish. An Amazon team at Lab126, a research center based in San Francisco, has developed an algorithm that learns about a particular style of fashion from images, and can then generate new items in similar styles from scratch--essentially, a simple AI fashion designer. The event included mostly academic researchers who are exploring ways for machines to understand fashion trends.


New AI can work out whether you're gay or straight from a photograph

#artificialintelligence

Artificial intelligence can accurately guess whether people are gay or straight based on photos of their faces, according to new research that suggests machines can have significantly better "gaydar" than humans. The study from Stanford University – which found that a computer algorithm could correctly distinguish between gay and straight men 81% of the time, and 74% for women – has raised questions about the biological origins of sexual orientation, the ethics of facial-detection technology, and the potential for this kind of software to violate people's privacy or be abused for anti-LGBT purposes. The research found that gay men and women tended to have "gender-atypical" features, expressions and "grooming styles", essentially meaning gay men appeared more feminine and vice versa. The data also identified certain trends, including that gay men had narrower jaws, longer noses and larger foreheads than straight men, and that gay women had larger jaws and smaller foreheads compared to straight women.


Amazon has developed an AI fashion designer

#artificialintelligence

The effort points to ways in which Amazon and other companies could try to improve the tracking of trends in other areas of retail--making recommendations based on products popping up in social-media posts, for instance. For instance, one group of Amazon researchers based in Israel developed machine learning that, by analyzing just a few labels attached to images, can deduce whether a particular look can be considered stylish. An Amazon team at Lab126, a research center based in San Francisco, has developed an algorithm that learns about a particular style of fashion from images, and can then generate new items in similar styles from scratch--essentially, a simple AI fashion designer. The event included mostly academic researchers who are exploring ways for machines to understand fashion trends.


Amazon has developed an AI fashion designer

#artificialintelligence

The effort points to ways in which Amazon and other companies could try to improve the tracking of trends in other areas of retail--making recommendations based on products popping up in social-media posts, for instance. For instance, one group of Amazon researchers based in Israel developed machine learning that, by analyzing just a few labels attached to images, can deduce whether a particular look can be considered stylish. An Amazon team at Lab126, a research center based in San Francisco, has developed an algorithm that learns about a particular style of fashion from images, and can then generate new items in similar styles from scratch--essentially, a simple AI fashion designer. The event included mostly academic researchers who are exploring ways for machines to understand fashion trends.


Is IBM Watson A 'Joke'?

#artificialintelligence

On the May 8th edition of Closing Bell on CNBC, venture capitalist Chamath Palihapitiya, founder and CEO of Social Capital, created quite a stir in enterprise artificial intelligence (AI) circles, when he took on Watson, Big Blue's AI platform. "Human intelligence outperforms machine-learning applications in complex decision making routinely required during the course of care, because machines do not yet possess mature capabilities for perceiving, reasoning, or explaining," explained Ernest Sohn, a chief data scientist in Booz Allen's Data Solutions and Machine Intelligence group; Joachim Roski, a principal at Booz Allen Hamilton; Steven Escaravage, vice president in Booz Allen's Strategic Innovation Group; and Kevin Maloy, MD, assistant professor of emergency medicine at Georgetown University School of Medicine. "A health care organization that relies on a single EHR [Electronic Health Record] vendor's analytic solutions, as well as its own legacy analytics infrastructure created before the era of big data, may see limited progress," they continued. "While many machine-learning solutions are not yet mature and sophisticated enough to support complex clinical decisions, machine learning can be effectively deployed today to reduce more routine, time-consuming, and resource-intensive tasks, allowing freed-up personnel to be redeployed to support higher-end work."


How AI Is Transforming Drug Creation

#artificialintelligence

But samples also were sent to a lab where computers using artificial intelligence are changing the way pharmaceutical companies develop drugs. Biological insights driven by machine learning also could help pharmaceutical companies better identify and recruit patients for clinical trials of therapies most likely to work for them, perhaps boosting the chances of those medications' getting approved by regulatory agencies such as the Food and Drug Administration. AI systems trained on various data sources, including preclinical data sets, have helped make "significant performance improvements" by enabling "better selections of which compounds to…make and test" in the lab and by "flagging" whether compounds might have "toxic" effects or "unexpected favorable" ones, he says. German pharmaceutical company Merck KGaA has developed two drugs using computer-vision software, which analyzes images of cells and tissues, and other AI systems capable of drawing insights from public databases of genetic and chemical information, says Joern-Peter Halle, Merck KGaA's head of external innovation.