The University of Utah announced Tuesday it has been selected by Schmidt Futures to solicit and develop ideas for strengthening the middle class in America.
The university will partner with other Alliance partners to seek policy and technology ideas from individuals or groups throughout Utah that have the potential to increase net income for 10,000 of the state’s middle-class households by 10 percent by 2020, a press release stated.
Eric Schmidt, founder of Schmidt Futures, said the best ideas come from people working together, in their own communities, using an interdisciplinary approach grounded in facts, data science and diverse perspectives.
Henry Kautz, the founding director of the Goergen Institute for Data Science at the University of Rochester, will direct the National Science Foundation (NSF) division that supports artificial intelligence, human-computer interaction, and data science.
“We at NSF are absolutely delighted to have Henry coming on board as division director of our Division of Information and Intelligent Systems,” says Jim Kurose, assistant director of NSF for computer and information science and engineering. “At this particularly important time for the field, it is critical to have a leader with such outstanding research accomplishments, deep insight, and tremendous national and international experience.”
I have noticed a trend in the five years that I have been part of the big data community. Most of the experts that I speak with almost exclusively discuss the benefits of using big data in the private sector. Far fewer data scientists emphasize its role in academia.
While its contributions in educational institutions have been frequently overlooked, big data is changing the profession in numerous ways. Administrators, students and faculty members are all benefiting from the emergence of big data and its potential in the halls of higher learning. Here are some of the applications of big data in academia in 2018 and beyond.
Government Data Science News
The European Space Agency released Gaia, a data record of 1.7 billion stars in the Milky Way galaxy. David Hogg [NYU and Flatiron Institute] marvels at the team’s accomplishment, “We’re really talking about an immense change to our knowledge about the Milky Way….The amount of information this is revealing in some sense is thousands or even hundreds of thousands of times larger than any amount of information we’ve had previously.” Gaia data are available for free.
Meanwhile in the US, satellite data from the US Geological Survey and an aerial-survey programme run by the Department of Agriculture (USDA) are currently free, but may be moved to a fee-based model.
Henry Kautz, of the University of Rochester will now direct the National Science Foundation division that supports artificial intelligence, human-computer interaction, and data science.
The European Union, in an effort to catch up to the US and China, has committed $1.5bn to support artificial intelligence initiatives (see ELLIS in University Data Science News above). Researchers there blame Europe’s trailing status on lower access to venture capital funds and a host of other factors. One commentator noted that Europe’s focus on ethical oversight will continue in this new round of funding, and that Europeans “are betting on being the good guy.” Perhaps they are not familiar with the plaintive American question: Why do good guys always finish last?
The Environmental Protection Agencymay soon be prohibited from making decisions based on studies published without open access data and code. Though I believe many of us are in favor of open access science, we are also reluctant to ignore results from studies published in paywalled journals and/or without full access to data. EPA head Scott Pruitt refers to such studies as “secret science” which feels like a dog whistle tactic designed to discredit science and scientists. For the love of the planet and our existence on it, please publish your data and code!
Recognizing the opportunities of artificial intelligence (AI) for its customers, Farelogix has partnered with Florida International University (FIU) to set up a dedicated program that will apply data analytics to optimize airline revenue management and generate dynamic offers.
The new Data Science for Airlines Informatics (DSAI) program, which will open at FIU in May of this year, is the result of a collaboration between airline IT company Farelogix and the university’s School of Computing and Information Sciences (SCIS). DSAI will be focused on the study, and implementation, of predictive analytics, machine learning and artificial intelligence for the airline business – “the new frontier in air commerce,” according to Jim Davidson, CEO of Farelogix.
St. Bonaventure University students now have a space to research cybersecurity and even protect local businesses from cyberattacks.
Approximately 170 people were on hand Tuesday for the unveiling of the Western New York Cybersecurity Research Center, which university officials said is the first of its kind in the region and will allow students and faculty to both perform research and provide monitoring and defense services to clients.
Computer scientists at Rice University have created a deep-learning, software-coding application that can help human programmers navigate the growing multitude of often-undocumented application programming interfaces, or APIs.
Known as Bayou, the Rice application was created through an initiative funded by the Defense Advanced Research Projects Agency aimed at extracting knowledge from online source code repositories like GitHub. A paper on Bayou will be presented May 1 in Vancouver, British Columbia, at the Sixth International Conference on Learning Representations, a premier outlet for deep learning research. Users can try it out at askbayou.com.
An analysis of more than 400 use cases across 19 industries and nine business functions highlights the broad use and significant economic potential of advanced AI techniques.
Each of us carries in our genomes about 10 million genetic variations called single nucleotide polymorphisms (SNPs), which represent a difference of just one letter in the genetic code. Every human’s pattern of SNPs is unique and quite stable, as they are inherited from our parents and are rarely mutated, making them a kind of “natural barcode” that can identify the cells from any individual. A group of researchers from the Wyss Institute for Biologically Inspired Engineering at Harvard University and Harvard Medical School (HMS) has developed a new genetic analysis technique that harnesses these barcodes to create a faster, cheaper, and simpler way to track what happens to cells from different individuals when they are exposed to any kind of experimental condition, enabling large pools of cells to be analyzed simultaneously.
“There are numerous experiments that this technique could be applied to,” says first author Yingleong Chan, Ph.D., a Postdoctoral Fellow in George Church’s lab at the Wyss Institute and HMS. “You can test a cancer drug against different cell lines from different people, see whether a particular patient’s cell line responded well to the drug, and then use that drug for a targeted approach to treatment. We’ve effectively built a discovery tool to enable personalized medicine.” The research is reported in Genome Medicine.
Europe’s plan to catch up to the United States and China in an artificial intelligence (AI) arms race is coming into focus. The European Commission today announced that it would devote €1.5 billion to AI research funding until 2020. It also said it would present ethical guidelines on AI development by the end of the year, suggesting that Europe could become a precautionary counterweight to its global rivals in a field that has raised fears about a lack of fairness and transparency even as it has made great advances.
Both the United States and China practice “permissionless innovation: Break things as you go and go fast,” says Eleonore Pauwels, a Belgian ethics researcher at the United Nations University in New York City. In contrast, Europeans “are betting on being the good guy,” she says. This could mean, for instance, developing AI systems that require smaller data sets, enhance privacy and trust, and are more transparent than their competitors, Pauwels says. “This is noble, but I don’t know if they have the means of their politics.”
The United Kingdom is planning a big investment in artificial intelligence technologies in a deal worth nearly £1 billion, or about $1.3 billion.
The U.K. government said Thursday that part of its multi-year AI investment–about £300 million, or more than $400 million–would come from U.K.-based corporations and investment firms and those located outside the country.
Some of the U.S.-based companies involved with the U.K.’s AI deal include Microsoft, Hewlett Packard Enterprise, IBM, McKinsey, and Pfizer, but the U.K. did not say how much each firm was planning to individually invest. A few of these U.S. companies helped consult on an earlier independent review on developing AI in the U.K. that the government is using as a template for its new initiative.
Toronto and Montreal always receive the most “AI capital of Canada” discussion, but Vancouver is pulling itself closer to the top with more additions to the growing sector.
Borealis AI is helping the cause with the announcement of a brand new research centre in the city. The esteemed AI hub is expanding its network of labs further across the country and this new institute will focus on computer vision—a smaller field within machine learning that looks at how computers see and process the visual world.
The Vancouver lab will feature Greg Mori as its research director.
On her first day at NASA in 1999, Dr. Ayanna Howard walked into the Telerobotics Research and Applications Group at the Jet Propulsion Laboratory, excited to begin programming Mars rovers with her newly assigned staff. But a male staff member barely registered her presence, saying “The secretaries work down the hall.” So began the rise of one of the few female African American roboticists in America.
To be fair, Dr. Howard’s staffer probably didn’t realize that the young woman entering the lab was his boss because he had never met a female robotics Ph.D. Even today, although 74 percent of girls are interested in technology-related fields such as computer science, as adults they represent only 25 percent of all computing occupations. As if that isn’t low enough, women leave the tech industry at twice the rate men do.
“The only thing that’s saved me is that I was stubborn,” says Dr. Howard. “I credit my upbringing with giving me confidence, although even then that wasn’t enough.”
The Environmental Protection Agency announced long-expected plans on Tuesday to stop using “secret science” — meaning studies that don’t make all of their data publicly available — when making rules.
Because this science includes medical studies with confidential patient information, it effectively means that the agency would restrict the public health research that’s now used to support pollution laws.
EPA chief Scott Pruitt announced the proposal at a closed-door event at the agency’s headquarters in Washington, DC, calling it a big step forward for increasing transparency at the agency. It comes as he faces growing scrutiny from Congress, the White House, and government watchdogs for his travel, spending, and treatment of staff on the job.
Boston, MA May 1-4. “Attend ODSC East 2018 and learn the latest AI & data science topics, tools, and languages from some of the best and brightest minds in the field.” [$$$]
Los Alamos, NM June 11-14. “The goal of this conference is to stimulate interdisciplinary research and innovative solutions to practical problems though interactions among statisticians, quality professionals, engineers, and scientists from diverse fields.” [$$$]
Want to more efficiently automate the scaling up and down of your IT systems? Take a close look at the traditional practice of control theory, advised Allan Espinosa, a DevOps engineer for Bloomberg, and author of “Docker High Performance,” who spoke last week in a session at the Cloud Foundry Summit in Boston.
Though widely used in mechanical engineering for centuries, control theory has yet to be deployed much to automatically adjust the performance of the distributed IT systems. This is surprising, given how much scalable services from Kubernetes to serverless rely on an ability to quickly adjust the workload demand to the available resources as accurately as possible.