Sensitive robots can tell your gender from a handshake

Daily Mail

First results show a robot is capable of inferring someone's gender and personality in 75 per cent of cases simply by shaking hands (stock image) First results show that a robot is capable of inferring someone's gender and personality in 75 per cent of cases simply by shaking hands. The ENSTA research team have developed robots that can detect emotions and change their behaviour accordingly. The ENSTA robots detect emotions and change their behaviour accordingly. First results show a robot is capable of inferring someone's gender and personality in 75 per cent of cases simply by shaking hands.

Robot judges? Edmonton research crafting artificial intelligence for courts


A professor in computing science at the University of Alberta, Goebel has partnered with scientists in Japan to develop artificial intelligence programs designed for the legal world. "It's just extending the research required to more deeply understand language, so you can support or take over some of the things that humans do with legal reasoning," Goebel said in an interview with CBC Edmonton's Radio Active. "My colleague started studying law [in Japan], he took a law degree and started writing bar exams and he failed the bar exams," said Goebel. Building machines that understand language well enough to reason about law is a pretty interesting challenge."

Analyzing Data Science Job Roles and Qualifications - JungleML


The'data analytics and data engineer' roles shared similar results, as did the'machine learning and data scientist' roles. 'Statistics' and'Mathematics' appeared about 2000 times over the'machine learning and data scientist' job postings and only 1000 times for'data engineer and data analytics'. Clearly having a PhD is highly preferred in direct machine learning and scientist roles but nowadays a Masters is good enough in most cases. If you're mathematically/research inclined, then you'll be better suited for ML jobs.

Gene-editing technology developer Feng Zhang awarded $500,000 Lemelson-MIT Prize

MIT News

Feng Zhang, a pioneer of the revolutionary CRISPR gene-editing technology, TAL effector proteins, and optogenics, is the recipient of the 2017 $500,000 Lemelson-MIT Prize, the largest cash prize for invention in the United States. Prior to harnessing CRISPR-Cas9, Zhang engineered microbial TAL effectors (TALEs) for use in mammalian cells, working with colleagues at Harvard University, authoring multiple publications on the subject and becoming a co-inventor on several patents on TALE-based technologies. Zhang was also a key member of the team at Stanford University that harnessed microbial opsins for developing optogenetics, which uses light signals and light-sensitive proteins to monitor and control activity in brain cells. Zhang's numerous scientific discoveries and inventions, as well as his commitment to mentorship and collaboration, earned him the Lemelson-MIT Prize, which honors outstanding mid-career inventors who improve the world through technological invention and demonstrate a commitment to mentorship in science, technology, engineering and mathematics (STEM).

The Engine announces investments in first group of startups

MIT News

The Engine, founded last year by MIT, today announced investments its first group of seven startups that are developing innovations poised for transformative impact on aerospace, renewable energy, synthetic biology, medicine, and other sectors. To genetically engineer organisms, scientists expose cells to an electric field, which opens pores within the cell membrane, allowing customized DNA to flow into the cell. Buie and his Kytopen co-founder, MIT research scientist Paulo Garcia, developed a microfluidics device that shocks cells continuously. "Anyone in the energy industry will recognize that turning renewable energy into baseload electricity available all day, every day, is an extremely ambitious goal," Chiang says.

Prospect of Synthetic Embryos Sparks New Bioethics Debate

MIT Technology Review

Two years ago, Shao, a mechanical engineer with a flair for biology, was working with embryonic stem cells, the kind derived from human embryos able to form any cell type. The work in Michigan is part of a larger boom in organoid research--scientists are using stem cells to create clumps of cells that increasingly resemble bits of brain, lungs, or intestine (see "10 Breakthrough Technologies: Brain Organoids"). Scientists have started seeking ways to coax stem cells to form more complicated, organized tissues, called organoids. Following guidelines promulgated last year by Kimmelman's international stem-cell society, Fu's team destroys the cells just five days after they're made.

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


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.

What do movies teach us about Artificial Intelligence?


It goes rogue and tries to initiate a world war, eventually taking many human lives. It can make machines of its own, intended for human good, but eventually it becomes so corrupted, sadistic, and bloodthirsty that it builds war machines that eliminate humans themselves. If you noticed, there is something common in all the movies mentioned above, the Artificial intelligence in all these movies eventually becomes aware of its superior capabilities to humans. These reasons are basic human instincts bring depicted by the A.I.

5 Reasons Why Your Data Science Team Needs The DGX Station


I immediately pulled a container and started work on a CNTK NCCL project, the next day pulled another container to work on a TF biomedical project. By running Nvidia Optix 5.0 on a DGX Station, content creators can significantly accelerate training, inference and rendering (meaning both AI and graphics tasks). Flexibility to do AI work at the desk, data center, or edge The Fastest Personal Supercomputer for Researchers and Data Scientists 15. However, for our current projects we need a compute server that we have exclusive access to." By running Nvidia Optix 5.0 on a DGX Station, content creators can significantly accelerate training, inference and rendering (meaning both AI and graphics tasks).

Amazon Is Scouring the Globe for AI Talent @themotleyfool #stocks $GOOGL, $AMZN, $GOOG


Earlier this year, Alphabet Inc. (NASDAQ:GOOGL) (NASDAQ:GOOG), a pioneer in the AI revolution, revealed that it would launch Google Brain Toronto, the second such research facility in the Great White North. Amazon has revealed plans to build a new AI research hub in Barcelona, Spain, which will be located in the city's 22@ start-up district, and plans to hire more than 100 scientists and software engineers to staff the facility over time. Earlier this year the company expanded its research and development center in Cambridge, England, by adding a 60,000-square-foot facility to house over 400 "machine learning scientists, knowledge engineers, data scientists, mathematical modelers, speech scientists, and software engineers" according to a press release. The Motley Fool owns shares of and recommends Alphabet (A shares), Alphabet (C shares), and Amazon.