Bryan Weisbard, Director and Head of Online Safety Operations at Twitter, has been appointed to the Rutgers University Big Data Advisory Board. Weisbard is an expert in Online and Cyber Security, Trust & Safety, Digital Privacy, Corporate Security, and Risk Management. He is recognized for leveraging technological innovation to solve security challenges. In his Board capacity, Weisbard will advise industry professionals on how best to solve cyber security, machine learning, privacy, online safety, and data analytics challenges.
The University of Delaware’s Bintong Chen and Deshen Wang are tackling this problem in their latest research. Working with Jing Chen of Canada’s Dalhousie University, the team has created a system of consumer incentives that encourage individuals and merchants to engage in practices that significantly reduce the risk of credit card fraud.
In “Credit card fraud detection strategies with consumer incentives,” a paper published in Omega, The International Journal of Management Science, the team applied this strategy to data from a major European bank. The data included almost 285,000 transactions made over a two-day period.
At age 16, Danielle Bassett spent most of her day at the piano, trying to train her fingers and ignoring a throbbing pain in her forearms. She hoped to pursue a career in music and had been assigning herself relentless practice sessions. But the more she rehearsed Johannes Brahms’s feverish Rhapsody in B Minor on her family’s Steinway, the clearer it became that something was wrong. Finally, a surgeon confirmed it: Stress fractures would force her to give up the instrument for a year.
“What was left in my life was rather bleak,” Bassett says. Her home-schooled upbringing in rural central Pennsylvania had instilled a love of math, science, and the arts. But by 17, discouraged by her parents from attending college and disheartened at her loss of skill while away from the keys, she expected that responsibilities as a housewife and mother would soon eclipse any hopes of a career. “I wasn’t happy with that plan,” she says.
Right now, AI systems are powerful but unreliable. Many of them are vulnerable to sophisticated attacks or fail when used outside the environment in which they were trained. Governments want their systems to work properly, but competition brings pressure to cut corners. Even if other countries aren’t on the brink of major AI breakthroughs, the perception that they’re rushing ahead could push others to do the same. And if a government deployed an untested AI weapons system or relied on a faulty AI system to launch cyberattacks, the result could be disaster for everyone involved.
Policymakers should learn from the history of computer networks and make security a leading factor in AI design from the beginning. They should also ratchet down the rhetoric about an AI arms race and look for opportunities to cooperate with other countries to reduce the risks from AI. A race to the bottom on AI safety is a race no one would win.
Rapid advances in technology are enabling engineers to program these voice assistants with a better understanding of the emotions in someone’s voice and the behaviors associated with those emotions. The better we understand these nuances, the more agile and emotionally intelligent our AI systems will become.
A detailed roadmap outlining research priorities for artificial intelligence (AI) in radiology was published April 16 in Radiology, and the organizations involved have announced that a second report is due later this year.
The research roadmap was co-sponsored by the National Institutes of Health, RSNA, the American College of Radiology (ACR) and the Academy for Radiology and Biomedical Imaging Research. It covers issues discussed and agreed upon back in August 2018, when a workshop of stakeholders gathered in Bethesda, Maryland, to tackle this topic.
As concerns mount about the overuse of powerful and costly diagnostic imaging tests, such as CT scans and MRIs, a new study from MIT suggests that software designed to help doctors make better decisions could decrease certain scans by about 6%. The results of the study are published in the journal PLOS ONE.
“There is a lot of debate about the health risks and high costs that stem from the overuse of potentially inappropriate tests,” says
, the Erwin H. Schell Professor of Management and Applied Economics at the MIT Sloan School of Management, and one of the authors of the study. “Our research shows that technology can improve healthcare delivery by helping physicians make the right decisions about which diagnostic scans to use when.”
The ASA Excellence in Statistical Reporting Award Committee has selected National Public Radio reporter Hansi Lo Wang as the 2019 recipient of its eponymous award.
Committee chair Alan Tupek stated, “We are proud to honor Hansi Lo Wang. The many letters from prominent members of our community supporting his nomination were effusive in their praise for all aspects of his reporting, from timeliness and depth to extent and insight.”
The work is described in the journal Transactions of the Association for Computational Linguistics, in a paper by Rumen Dangovski and Li Jing, both MIT graduate students; Marin Soljačić, a professor of physics at MIT; Preslav Nakov, a senior scientist at the Qatar Computing Research Institute, HBKU; and Mićo Tatalović, a former Knight Science Journalism fellow at MIT and a former editor at New Scientist magazine.
In an effort to further strengthen Canada’s position in the world of quantum computing, artificial intelligence and machine learning technology, the federal government is investing $41 million in four high-tech organizations in Waterloo Region.
Navdeep Bains, minister of innovation, science and economic development and the minister responsible for the Federal Economic Development Agency for Southern Ontario, made the announcement Thursday afternoon at Quantum Valley Investments, a 90,000-square-foot facility near the northern edge of the University of Waterloo campus and one of the investment recipients.
The room was packed with dozens of local tech leaders, including BlackBerry and Quantum Valley Investments co-founder Mike Lazaridis, University of Waterloo president Feridun Hamdullahpur and Iain Klugman, president and CEO of Communitech.
IBM Watson Health is tapering off its Drug Discovery program, which uses “AI” software to help companies develop new pharmaceuticals, blaming poor sales.
The service isn’t completely shutting down, however. IBM spokesperson Ed Barbini told The Register: “We are not discontinuing our Watson for Drug Discovery offering, and we remain committed to its continued success for our clients currently using the technology. We are focusing our resources within Watson Health to double down on the adjacent field of clinical development where we see an even greater market need for our data and AI capabilities.”
The recent AI boom has had all sorts of weird and wonderful side effects as amateur tinkerers find ways to repurpose research from universities and tech companies. But one of the more unexpected applications has been in the world of video game mods. Fans have discovered that machine learning is the perfect tool to improve the graphics of classic games.
The technique being used is known as “AI upscaling.” In essence, you feed an algorithm a low-resolution image, and, based on training data it’s seen, it spits out a version that looks the same but has more pixels in it. Upscaling, as a general technique, has been around for a long time, but the use of AI has drastically improved the speed and quality of results.
“It was like witchcraft,” says Daniel Trolie, a teacher and student from Norway who used AI to update the visuals of 2002 RPG classic The Elder Scrolls III: Morrowind.
A Brown University graduate who went on to a successful career as an investor has donated $25 million to expand economics research at the school.
Orlando Bravo, co-founder of private-equity firm Thoma Bravo LLC, will split his gift between $15 million to launch a new Orlando Bravo Center for Economic Research and $10 million to “fund the recruitment and retention of world-class economics faculty,” according to Brown.
“This work deviates from the old way of manually trying to clean the data which was expensive, didn’t scale, and does not meet the current needs for cleaning the data,” said Ilyas of Waterloo’s Faculty of Mathematics. “This system addresses the problem where the information is out there, and people are using it to run analytics, but it is not correct. It doesn’t provide information that was not there, but instead corrects information you assume is correct.”
The University of Louisville is teaming up with IBM to create a skills academy that will be the first of its kind in the nation and will teach students about growing digital fields like artificial intelligence.
“Accepted startups will receive mentoring from the BMO Harris team, as well as access to the 1871 space and resources, including 300+ workshops per year.” Deadline to apply is April 19.
“UKSG is launching a new white paper series. The purpose will be to promote discussion within the field of open scholarship and scholarly communication. White papers will be commissioned which take a thoughtful and provocative approach to the lifecycle of open scholarship, and to the open dissemination of scholarly outputs for knowledge gain, public awareness, and impact.” Deadline for applications is June 14.
In today’s IT landscape — already overstuffed with hype about hybrid cloud, hybrid IT, and “hybrid this” or “hybrid that” — it may be tempting to dismiss concepts such as hybrid API management as just another entry in the buzzword parade. But make no mistake: we on Google Cloud’s Apigee team do not believe that hybrid architectures can be safely or efficiently created without hybrid API management. After all, the cloud native world means businesses rely on software in many locations — and because APIs are how software talks to other software, enterprises must have visibility into and control over their APIs and how they are used.
Proceedings of the National Academy of Sciences; Dmitry Krotov and John J. Hopfield
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It is widely believed that end-to-end training with the backpropagation algorithm is essential for learning good feature detectors in early layers of artificial neural networks, so that these detectors are useful for the task performed by the higher layers of that neural network. At the same time, the traditional form of backpropagation is biologically implausible. In the present paper we propose an unusual learning rule, which has a degree of biological plausibility and which is motivated by Hebb’s idea that change of the synapse strength should be local—i.e., should depend only on the activities of the pre- and postsynaptic neurons. We design a learning algorithm that utilizes global inhibition in the hidden layer and is capable of learning early feature detectors in a completely unsupervised way. These learned lower-layer feature detectors can be used to train higher-layer weights in a usual supervised way so that the performance of the full network is comparable to the performance of standard feedforward networks trained end-to-end with a backpropagation algorithm on simple tasks. [full text]
A standalone Jupyter notebook … Carnets provides a complete, stand-alone, implementation of Jupyter notebooks. Everything runs on your device; you do not need an internet connection. Numpy, Sympy, Matplotlib and nbextensions (including ipywidgets) are pre-installed.
NVIDIA is partnering with three leading universities — Georgia Tech, the University of California, Davis, and Texas A&M — as part of our NVIDIA AI Labs program, to build the future of graph analytics on GPUs.
NVIDIA’s work with these three new NVAIL partners aims to ultimately create a one-stop shop for customers to take advantage of accelerated graph analytics algorithms.