They call it Herb2. It’s a dapper robot, wearing a bowtie even while it sits at home in its lab at the University of Washington. Its head is a camera, which it cranes up and down, taking in the view of a dimly lit corner where two computer monitors sit.
All perfectly normal stuff for a robot—until the machine speaks: “Hello from the hackers.”
Clear across the country at Brown University, researchers have compromised Herb2. They’ve showed how they can scan for internet-connected research robots in labs and take command—with the blessing of the robot’s owners at the University of Washington, of course.
“We could read the camera, essentially spying,” says roboticist Stefanie Tellex. “We could see where its arms were and they were moving. There was a text-to-speak API so we could have the robot mysteriously talk to you.”
… [Lu] Liu said that there are many cases when the most famous works of an individual came in sequence. She cited Peter Jackson, director of “The Lord of the Rings” film series; Vincent Van Gogh, whose most famous paintings were completed late in his career; and Albert Einstein, whose four published papers in his “miracle year” of 1905 contributed significantly to the foundation of modern physics.
“[A hot streak] doesn’t just matter to these individuals,” said Liu. “It matters to society as well.”
Liu said that this could help to understand the innovative process, and have the potential to discover and cultivate individuals during a hot streak.
As the research shows that hot streaks do in fact exist in creative careers, the researchers hope to apply the research methods to more domains, including musicians, inventors and entrepreneurs.
Stretchable plant wearables and smart tags dropped by drones aim to help give farming a big data makeover. The relatively cheap technologies for mass monitoring of individual plants across large greenhouses or crop fields could get field tests in three countries starting in 2019.
The idea came from researchers at King Abdullah University of Science and Technology (KAUST) in Saudi Arabia with expertise in flexible electronics. After talking with colleagues who were cultivating genetically engineered plants in greenhouses, they recognized the need for inexpensive sensors that could be deployed en masse and report on individual plant conditions. Their early offerings include a stretchable sensor for measuring micrometer-level changes in plant growth and a “PlantCopter” temperature and humidity sensor designed to be dropped from a drone and corkscrew its way through the air for a gradual descent.
In a series of conversations over the summer, I talked to Zuckerberg about Facebook’s problems, and about his underlying views on technology and society. We spoke at his home, at his office, and by phone. I also interviewed four dozen people inside and outside the company about its culture, his performance, and his decision-making. I found Zuckerberg straining, not always coherently, to grasp problems for which he was plainly unprepared. These are not technical puzzles to be cracked in the middle of the night but some of the subtlest aspects of human affairs, including the meaning of truth, the limits of free speech, and the origins of violence.
Zuckerberg is now at the center of a full-fledged debate about the moral character of Silicon Valley and the conscience of its leaders. Leslie Berlin, a historian of technology at Stanford, told me, “For a long time, Silicon Valley enjoyed an unencumbered embrace in America. And now everyone says, Is this a trick? And the question Mark Zuckerberg is dealing with is: Should my company be the arbiter of truth and decency for two billion people? Nobody in the history of technology has dealt with that.”
A University of Oklahoma team is the recipient of a National Science Foundation Major Research Instrumentation grant in the amount of $967,755 for a new academic research data storage instrument—a massive tape archive known as the OU and Regional Research Store, which will serve as a national model for affordable, large-scale, multi-institutional storage.
When computer scientist Christian Berger’s team sought to get its project about self-driving vehicle algorithms on the road, it faced a daunting obstacle. The scientists, at the University of Gothenburg in Sweden, found an overwhelming number of papers on the topic — more than 10,000 — in a systematic literature review. Investigating them properly would have taken a year, Berger says.
Luckily, they had help: a literature-exploration tool powered by artificial intelligence (AI), called Iris.ai. Using a 300-to-500-word description of a researcher’s problem, or the URL of an existing paper, the Berlin-based service returns a map of thousands of matching documents, visually grouped by topic. The results, Berger says, provide “a quick and nevertheless precise overview of what should be relevant to a certain research question”.
Iris.ai is among a bevy of new AI-based search tools offering targeted navigation of the knowledge landscape.
“The thing that I’ve seen happening in the last few years at Google is this real push to democratize AI tools and make them available to folks who are not themselves technology companies,” he said. “I think that is a really positive direction for the world.”
“I am bursting with excitement about this,” said Moore. “I have always deeply believed in the power of technology to improve the state of the world, so for me it’s a big opportunity to help Google bring useful AI to all the other industry verticals.”
There is little doubt that the Department of Defense needs help from Silicon Valley in order to compete with China in the race for artificial intelligence. The question is whether Silicon Valley is willing to cooperate and whether President Donald Trump’s combative nature risks damaging the vital partnership.
Last week reports surfaced that Secretary of Defense Jim Mattis had warned Trump that the United States is not keeping pace with the ambitious plans of China in artificial intelligence.
Data & Society: Points blog; Mikaela Pitcan, Alex Rosenblat, Mary Madden, and Kadija Ferryman
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Patterns of human behavior in the physical world — how we get around, where we live, how we work and play — are increasingly influenced by digital and data-driven technologies. As digital and internet technologies become more deeply embedded in our everyday lives, they create a critical layer of infrastructure that affects the distribution of health resources across society. At the same time, decision-makers are already accommodating the growing consumer demand for digital technologies in planning and infrastructure projects — whether allocating rural land for data centers instead of parks or reducing public transportation due to the increased availability of on-demand car services. In each of these cases, rapid technological change produces radically different outcomes for different communities.
Pulsars—whirling stellar corpses that send beams of radio waves across the cosmos—are today’s astrophysical Swiss army knives. With them, scientists can test some of the most fundamental theories in physics, detect gravitational waves, navigate the cosmic ocean, and maybe even communicate with aliens.
But if it weren’t for the work of Dame Jocelyn Bell Burnell, who discovered pulsars in 1967 while still a graduate student at the University of Cambridge, these distant stellar lighthouses may not have become such powerful celestial tools.
Now, 51 years after she first noticed an odd bit of “scruff” in her observations, Bell Burnell has been awarded a $3-million Special Breakthrough Prize in Fundamental Physics. The prize committee not only cites her “detection of radio signals from rapidly spinning, super-dense neutron stars” but also her “lifetime of inspiring scientific leadership.”
Stanford, CA November 6-7 at Stanford University. “Attendees should have an idea for a specific biomedical problem of their own to which they would like to apply Snorkel. Individuals who submit project ideas which utilize a dataset to which he/she already has access or which utilize PubMed or other open access document collections are more likely to be accepted.” Deadline to apply to attend is September 21.
“Google AI is challenging Kagglers to develop models that are robust to blind spots that might exist in a data set, and to create image recognition systems that can perform well on test images drawn from different geographic distributions than the ones they were trained on.” Deadline for entries is October 29.
“Google and DeepMind are generously supporting all families attending NIPS by offering a stipend of up to $100 USD per day (receipts required) to those attending the conference.” Deadline to submit request form is November 2.
“deon is a command line tool that allows you to easily add an ethics checklist to your data science projects. We support creating a new, standalone checklist file or appending a checklist to an existing analysis in many common formats.”
The web provides a rich, open-domain environment with textual, structural, and spatial properties. We propose a new task for grounding language in this environment: given a natural language command (e.g., “click on the second article”), choose the correct element on the web page (e.g., a hyperlink or text box). We collected a dataset of over 50,000 commands that capture various phenomena such as functional references (e.g. “find who made this site”), relational reasoning (e.g. “article by john”), and visual reasoning (e.g. “top-most article”). We also implemented and analyzed three baseline models that capture different phenomena present in the dataset.
In this post, we will use the Ford GoBike Real-Time System, StreamSets Data Collector, Apache Kafka and MapD to create a real-time data pipeline of bike availability in the Ford GoBike bikeshare ecosystem. We’ll walk through the architecture and configuration that enables this data pipeline and share a simple auto-updating dashboard within MapD Immerse.