Fortune 1000 companies are now recognizing that they must become more adept at leveraging their data assets if they are to compete successfully against highly agile data-driven competitors. Over the past decade, exponential growth of data, coupled with access to much larger data volumes and data sources, has enabled rapid evolution of AI capabilities — with the result that organizations are now able to apply AI capabilities at scale to deliver business value.
Three-quarters of the executives surveyed in 2018 cited fear of disruption as the principal motivating business driver as they enter 2019. This fear has built an increasing sense of urgency across companies and industries — with 87.8% stating there is a greater urgency to invest in big data and AI initiatives now more than ever. In order to continue to compete in a turbulent landscape, an overwhelming majority (91.7%) of executives identified the need to transform their organizations to be nimbler and more data-driven in order to keep pace with competitors.
Kerstin Cable, a language coach and host of the Fluent Show podcast, first wrote about Duolingo in 2015, criticizing it for its impractical vocabulary, its insistence upon one acceptable translation per sentence prompt, and its lack of explanation for incorrect answers, and she tells me much of this criticism still holds. “In this app,” she wrote back then, “you learn by parroting phrases, without even beginning to cover the background stories that grammar and pragmatics tell.”
But what annoys Cable most about Duolingo is the app’s own propaganda. “For a while, Duolingo told you, ‘You’re X% fluent.’ Which is one of the most insane things I’ve ever seen,” she told me.
For someone tasked with advancing a technology which, in the words of Google’s chief executive, is “more profound than electricity and fire”, Jeff Dean is a remarkably calm man.
Acquiring the Newseum building will allow Hopkins to consolidate its D.C. operations — currently spread across four buildings on Massachusetts Avenue — into one space. “Hopkins D.C.” will be anchored by the university’s School of Advanced International Studies. The district is also home to Hopkins programs including graduate courses in applied economics, government analytics, communication and global security, as well as support services for students.
Harvard John A. Paulson School of Engineering and Applied Sciences
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[Barbara] Grosz and collaborator Alison Simmons, the Samuel H. Wolcott Professor of Philosophy, developed a model that draws on the expertise of the philosophy department and integrates it into a growing list of more than a dozen computer science courses, from introductory programming to graduate-level theory.
Under the initiative, dubbed Embedded EthiCS, philosophy graduate students are paired with computer science faculty members. Together, they review the course material and decide on an ethically rich topic that will naturally arise from the content. A graduate student identifies readings and develops a case study, activities, and assignments that will reinforce the material. The computer science and philosophy instructors teach side by side when the Embedded EthiCS material is brought to the classroom.
Grosz and her philosophy colleagues are at the center of a movement that they hope will spread to computer science programs around the country. Harvard’s “distributed pedagogy” approach is different from many university programs that treat ethics by adding a stand-alone course that is, more often than not, just an elective for computer science majors.
Unfortunately, the recent lapse in appropriations (lapse) resulted in missed panels, a backlog of proposal actions, and delays that may result in the cancelation of related activities and certain programs. It is fully recognized that it will take time to work through this extensive backlog of activities. The Foundation is establishing processes that will enable us to focus on a specific set of high-priority areas, particularly in light of the three-week CR.
Proposers, awardees and reviewers who have questions are encouraged to await communications from NSF, at least initially, as we resume operations. We appreciate your patience.
An increasing number of animal tracking devices, known as biologgers, also measure environmental variables such as sound, temperature, and ocean salinity.
Data from biologgers complement information on an animal’s movements and help scientists understand its environment, but can have measurable effects on the animal’s behavior or reproduction.
As the field of biologging rapidly grows, scientists are trying to develop ethical frameworks for applying devices to wild animals.
Pressure colleges to stop chasing the same small subset of privileged, highly test-prepped applicants and start admitting needier kids. But new research suggests that the particular form this pressure has taken — including popular rankings based on Pell enrollment — has been at least partly backfiring.
In fact, at some of the schools most celebrated for providing opportunities for poor students, admissions and financial aid offices appear to be worsening their neglect of the low- and middle-income kids we want them to help.
Microsoft on Thursday said that it’s acquiring Citus Data, a start-up that has commercialized open-source database software called PostgreSQL. Terms of the deal weren’t disclosed.
The deal could help Microsoft make its argument that it supports open-source technologies, particularly in the cloud, while continuing to make money from popular proprietary software like Windows and Office. In the cloud business, Microsoft wants to use openness as a way to pick up business amid competition from Google, market leader Amazon and others.
Recently, we met up with Matt Van Horn, the co-founder and CEO of June. They’re making an oven with a camera inside that automatically recognizes your food and helps you cook it perfectly! [video, 3:25]
McGill University and Université de Montréal inaugurated a new artificial intelligence hub on Monday. As Global’s Billy Shields, explains, it is being touted as a major step forward in AI, one that cements Montreal’s position in the world of computer science. [video, 1:59]
Communications of the ACM, Carol Frieze and Jeria L. Quesenberry
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The persistent underrepresentation of women in computing has gained the attention of employers, educators, and researchers for many years. In spite of numerous studies, reports, and recommendations we have seen little change in the representation of women in computer science (CS)—consider that only 17.9% of bachelor’s degrees in computer science were awarded to women in 2016 according to the annual Taulbee Survey.15 At Carnegie Mellon University (CMU) we do not believe the situation is an intractable problem.
When Ken-Ichiro Kamei, a microengineer at Kyoto University, goes out drinking with his friends, he usually brings along one of his “bodies on a chip.” When the topic of work inevitably comes up, he’ll whip out the chip – which looks like a lab slide, but with an added crystal-clear silicone rubber layer containing faintly visible troughs and channels – and declare, “I’m making these devices to recreate humans and animals.”
Wows inevitably ensue. “It’s like I’m a magician and my friends have asked me to do some tricks,” Kamei chuckles.
Kamei is at the forefront of a new field of biotechnology that seeks to replicate organs, systems and entire bodies on chips such as the one he likes to show off.
“You get it all the time, truthfully,” Abdul-Rahman said. He’s been concerned that the true meaning of statements like “I don’t fool with them” glide past the ears of listeners who aren’t black. The unaware might think the speaker has a problem with someone. But saying this doesn’t necessarily imply hard feelings — it means the speaker isn’t really in someone’s circle.
Along with lapses in comprehension, Abdul-Rahman has observed persisting biases around how African Americans speak: “The system keeps perpetuating the same faulty norms about us.”
New research confirms his hunch. For a forthcoming study in the journal Language, researchers evaluated how well Philadelphia court reporters transcribe dialect. The team, which includes University of Pennsylvania linguists, a New York University sociologist, and a co-founder of Philadelphia Lawyers for Social Equity, tested 27 court reporters for both accuracy and comprehension.
Berkeley, CA “Join the Women in Data Science (WiDS) Datathon Collaboration Day on Saturday, February 2, to meet other participants, form teams, learn the basics of participating in Kaggle competitions, and get a jump start on your Datathon submissions with the help of technical mentors and domain experts.” [registration required]
Amherst, MA May 20-22 at the University of Massachusetts. “Knowledge gathering, representation, and reasoning are among the fundamental challenges of artificial intelligence. Large-scale repositories of knowledge about entities, relations, and their abstractions are known as “knowledge bases”. Most major technology companies now have substantial efforts in knowledge base construction.”
New York, NY February 4-8. “NYCDH Week gives individuals across the region who are interested in digital humanities an opportunity to learn new techniques and skills, hear about DH projects from across the city, and become part of a vibrant and diverse community of scholars and practitioners.” [registration required]
Chicago, IL April 6-7 at 1871 (222 W. Merchandise Mart Plaza). “For one weekend a year, 1871 brings together more than 100 students from local universities for the ultimate startup experience.” Deadline to apply is February 1.
During the rstudio::conf(2019L), I’ve presented an eposter called “Building Big Shiny Apps — A Workflow”. You can find the poster here, and this blog post is an attempt at a transcription of what I’ve been talking about while presenting the poster.
As this is a rather long topic, I’ve divided this post into two parts: this first post will talk about the background and motivation, and the second post will present a step by step workflow and the necessary tools.
SageMaker Neo is designed to ensure that ML models run as efficiently as possible on a variety of machines and environments. Unlike the training stage, in which models are generally honed on high-powered machines, for the inference stage, where the model makes predictions based on new data, it may be running on much lowlier devices.
I’ve been chewing on uncertainty visualizations since Matthew Kay’s excellent talk at Tapestry 2018. The recent release of the R package gganimate has also brought a number of animated visualizations across my feed, so let’s talk about an animated uncertainty visualization: hypothetical outcome plots (HOPs). What are they for, besides inspiring truly terrible puns?
I decided to start a newsletter about Amazon first and foremost because I wanted to read a newsletter about Amazon.
I love Casey Newton’s The Interface. The Interface is about “the intersection of social media and democracy,” but when it started, it was primarily a newsletter about Facebook. I’ve loved its evolution—the idea that when you pay particularly close attention to a particular company, all of its emanations and penumbras, all of the fields and subfields it touches and pulls into its gravitational well, have to be covered as well.
And I thought, “why isn’t someone doing something like this for Amazon?”