The team of professor Sergey Levine at University of California at Berkeley engineered a novel mash-up of two machine learning tasks, resulting in ways to have a computer continually update its ability to generalize from one learned task to another.
Solving a murder or tracking down the perpetrators of sexual abuse often requires dogged police work. What if a machine could help detectives spot the vital clues they need?
How can I process the data I collect about citizens both safely and with integrity? How can I present my conclusions honestly? How can I best deal with the responsibility that comes with possessing large amounts of data? These are essential questions for data scientists and statisticians. This is the reason for the emphasis on ethics during the National Data Science Programme of the Ministry of the Interior and Kingdom Relations (BZK) and Statistics Netherlands (CBS).
For underfunded conservation scientists, AI provides an attractive alternative to manually processing huge troves of data, such as camera-trap images or audio recordings. A PhD student could “spend months labelling it all by hand before they can get anywhere near answering their hypothesis”, says Dan Stowell, a computer scientist at Queen Mary University of London. Citizen science is one option to help with the data, but it isn’t always the right one: volunteers might work too slowly, and recruiting for projects that involve non-charismatic species can be difficult. AI tools don’t experience fatigue-related performance deterioration, as humans do, and they might be better at detecting infrequent or complex patterns.
Scientists need answers to pressing questions, such as whether conservation actions are working. And some problems need near real-time results — for instance, law-enforcement agencies pursuing illegal wildlife traffickers need to determine quickly if an animal for sale on social media is protected. AI could fit the bill.
In an effort to cement the United States’ reign as the global leader of digital innovation, President Trump recently signed an executive order outlining a new federal government strategy aiming to fuel progress in artificial intelligence (AI) research, development, and deployment.
AI has become a defining technology of the century and its potential is only just beginning to surface. While many are hopeful that this mandate will open new doors and create opportunities for both academia and industry, there are also questions and concerns about how the administration will provide the proper funding necessary to support its mission.
Here, two experts in AI and data sciences, Margrit Betke, a researcher and professor of computer science at Boston University, and Azer Bestavros, professor and founding director of the university’s Hariri Institute for Computing, give their reaction to the new executive order and its potential impact.
Apple Inc. Chief Executive Officer Tim Cook said he has “never been more optimistic” about where the company is today and where it’s heading. In a pep talk to investors, Cook said the iPhone maker is “planting seeds” and “rolling the dice” on future products that will just “blow you away.”
Speaking at the company’s annual general meeting in Cupertino, California, Cook reiterated that the iPhone maker is still on track to double revenue from services in 2020 from the nearly $25 billion in 2016. Referencing speaking notes on an iPad, Cook touched on several of the company’s product categories.
He said eventually the goal is to lower the price on the $1,200 MacBook Air laptop with a higher-resolution screen and said there’s a “long, great roadmap of fantastic” products related to the Apple Watch and AirPods. He indicated that more health features would come to the smartwatch.
One of the smart city’s most alluring features is its promise of innovation: It uses cutting-edge technology to transform municipal operations. Like efficiency, innovation possesses the nebulous appeal of being both neutral and optimal, which is difficult to oppose. After all, who would want her city to stagnate rather than innovate?
There is little doubt that cities can benefit from new ideas, policies, practices, and tools that make data easier to interpret and access. Where smart-city proponents such as Alphabet’s Sidewalk Labs go astray, however, is when they equate innovation with technology.
The perspective is deeply misguided. Technological innovation in cities is primarily a matter not of adopting new technology but of deploying technology in conjunction with nontechnical change and expertise. This requires data scientists to reach out beyond the realm of databases and analytics to access as much contextual knowledge as possible.
“You come in with your fancy machine learning algorithm in your pocket,” says Amen Ra Mashariki, former chief analytics officer at the Mayor’s Office of Data Analytics in New York City, “but what’s always going to be your ace in the hole is the knowledge of the people who actually do the real work.”
Mobile computing is accelerating beyond the smartphone era. Today, people wear smart glasses, smart watches and fitness devices, and they carry smartphones, tablets and laptops. In a decade, the very same people are likely to wear or carry tens of wireless devices and interact with the internet and computing infrastructure in markedly different ways. Computer scientist Xia Zhou is working to make sure there are no traffic jams with the increased demand. With support from the National Science Foundation (NSF), Zhou and her team at Dartmouth College are developing ways to encode and transmit all that data faster and more securely with the visible light spectrum. They see visible light communication as a much-needed advance in wireless data transmission. [video, 3:34]
In the last several months, Clarion, Edinboro and Lock Haven universities all unveiled pet-friendly policies, setting aside a portion of campus housing so students can bring with them, as one staffer put it, ”a piece of home that can hug you and love you back.”
In Philadelphia, La Salle University will open up one of its residence halls to upperclassmen with dogs.
The Canadian theoretical physicist Robert Myers has today been unveiled as the next director of one of the world’s leading theoretical physics centres. Myers, 60, takes over from Neil Turok as head of the Perimeter Institute for Theoretical Physics (PI) in Waterloo, Ontario. Turok steps down after a decade leading the Canadian centre to spend more time doing research at the PI.
Third Rock Ventures and ARCH Venture Partners said Thursday that they would lead the launch of Maze Therapeutics. The new company has obtained $191 million from the two venture capital firms and participating firms including Google’s GV, Foresite Capital, Casdin Capital, Alexandria Venture Investments and additional undisclosed investors. The company currently has a temporary address in Redwood City, California, according to its website.
The company’s scientific approach focuses on genetic modifiers, which are genes that affect the severity of diseases. According to the company, the amount of genetic data collected from people has led to a better understanding of how genetic mutations cause disease. But what remains unclear is why some people who are carriers of genes for diseases and would be expected to have them instead show mild symptoms or are not affected. Genetic modifiers often cause those differences, and Maze’s aim is to create medicines based on them.
The Guardian, Carole Cadwalladr and Duncan Campbell
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Facebook has targeted politicians around the world – including the former UK chancellor, George Osborne – promising investments and incentives while seeking to pressure them into lobbying on Facebook’s behalf against data privacy legislation, an explosive new leak of internal Facebook documents has revealed.
The documents, which have been seen by the Observer and Computer Weekly, reveal a secretive global lobbying operation targeting hundreds of legislators and regulators in an attempt to procure influence across the world, including in the UK, US, Canada, India, Vietnam, Argentina, Brazil, Malaysia and all 28 states of the EU.
Every year I, Barb Ericson, gather and report on the data for AP CS from the College Board which is at http://research.collegeboard.org/programs/ap/data/
There was a huge increase in Advanced Placement (AP) Computer Science Principles (CSP) exam takers nationally (from 43,780 in 2017 to 70, 864 in 2018 – a 62% increase). The Computer Science A (CSA) exam also grew (from 56,088 in 2017 to 60,040 in 2018 – a 7% increase).
Fears about how robots might transform our lives have been a staple of science fiction for decades. In the 1940s, when widespread interaction between humans and artificial intelligence still seemed a distant prospect, Isaac Asimov posited his famous Three Laws of Robotics, which were intended to keep robots from hurting us. The first—“a robot may not injure a human being or, through inaction, allow a human being to come to harm”—followed from the understanding that robots would affect humans via direct interaction, for good and for ill. Think of classic sci-fi depictions: C-3PO and R2-D2 working with the Rebel Alliance to thwart the Empire in Star Wars, say, or HAL 9000 from 2001: A Space Odyssey and Ava from Ex Machina plotting to murder their ostensible masters. But these imaginings were not focused on AI’s broader and potentially more significant social effects—the ways AI could affect how we humans interact with one another.
Massive-scale predictive analytics is a relatively new phenomenon, one that challenges both decades of law as well as consumer thinking about privacy.
As a technology, it may well save thousands of lives in applications like predictive medicine, but if it isn’t used carefully, it may prevent thousands from getting loans, for instance, if an underwriting algorithm is biased against certain users.
I chatted with Dennis Hirsch a few weeks ago about the challenges posed by this new data economy. Hirsch is a professor of law at Ohio State and head of its Program on Data and Governance. He’s also affiliated with the university’s Risk Institute.
“Data ethics is the new form of risk mitigation for the algorithmic economy,” he said.
This dataset contains all stories and comments from Hacker News from its launch in 2006 to present. Each story contains a story ID, the author that made the post, when it was written, and the number of points the story received.
OpenAI; Joseph Suarez, Yilun Du, Phillip Isola & Igor Mordatch.
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We’re releasing a Neural MMO — a massively multiagent game environment for reinforcement learning agents. Our platform supports a large, variable number of agents within a persistent and open-ended task. The inclusion of many agents and species leads to better exploration, divergent niche formation, and greater overall competence.
AI is not only for engineers. If you want your organization to become better at using AI, this is the course to tell everyone–especially your non-technical colleagues–to take.