[Nick] Yee started a business in 2015, Quantic Foundry, that sells his data to companies including League of Legends owner Tencent, Plants vs Zombies studio PopCap and Magic: The Gathering publisher Wizards of the Coast.
“Historically, game development was disentangled from actual data,” says Yee. “When people were still playing on non-internet connected consoles, the developers didn’t get that data back. You didn’t really have a clear view of how people were playing their games.”
Now, developers say, they have plenty of data, both from product telemetry (players’ in-game behavior) and external sources (like Yee’s surveys). And some are getting concerned they may have too much.
Emily Oster is a health economist and mother of two who had a lot of those same questions as she raised her kids. She dove into the data to find out what the science actually says about sleep training, breastfeeding, introducing solid foods, and lots more.
She wrote about the science of pregnancy in her first book Expecting Better. Her latest, on everything that comes after, is called Cribsheet: A Data-Driven Guide to Better, More Relaxed Parenting, from Birth to Preschool. In this segment, Oster answers listener questions and discusses common parenting myths. [audio, 33:05]
Here are some ways the IoMT is already changing health care:
1. Facilitating Better Management of Chronic Conditions
In the United States alone, 6 in 10 adults have a chronic disease. In-person appointments between providers and patients are essential for managing many of those ailments, but changes can nonetheless occur between face-to-face visits that require prompt intervention. A 2016 study found that wearable devices associated with the IoMT improve chronic disease management by letting physicians keep tabs on things like vital signs and activity levels.
Many patients will proactively look at metrics that are measured by wearable technologies and see how lifestyle changes contribute to better health. The length of hospital stays could go down, or providers could get prompt feedback about how one medication affects a patient versus another.
MIT News, Institute for Data, Systems, and Society
As a focal point for statistics at MIT, the Statistics and Data Science Center (SDSC) reflects the unique nature of statistics at MIT: steeped in cutting-edge computation, with both theoretical explorations and novel applications across departments and domains. As part of the Institute for Data, Systems, and Society (IDSS), the SDSC also fosters multi-disciplinary collaborations that bring new approaches to complex societal challenges. … SDSCon brought together over 200 participants from academia and industry, with talks ranging from tactics and techniques like machine learning to statistical applications in biology and business. “The purpose of SDSCon is to bring together folks … interested in statistics and data science, to both celebrate as well as build community,” said SDSC director and professor of electrical engineering and computer science (EECS) Devavrat Shah in his opening remarks. School of Engineering Dean Anantha Chandrakasan commented on the work the SDSC has done in building that community by “coalescing a community of scholars across campus around the shared mission to use statistical tools to advance research and education.”
How does today’s entry-level labor market compare with the past?
As of April 2019, unemployment in the U.S. was only 3.6%, an almost-50-year low (though a broader measure of employment that includes people out of the labor force — the prime-age employment-population ratio — was back only to its pre-recession level).
But the job market for recent graduates rarely looks like the job market at large. One reason: recent grads — 22-27-year-olds who have earned a bachelor’s degree and are no longer in school — tend to cluster in particular jobs and industries.
Don’t be distracted by the shiny new “Nest” smart display that was just announced: Nest died at Google I/O 2019. “Google Nest” is the new reality now, where Nest is no longer a standalone company but instead is a sub-brand (not even a division) of Google. The shutdown of Nest as an independent company was announced in 2018, but the pile of announcements at and around I/O 2019 marks the first time we’re seeing what the future of Nest looks like inside of Google.
Nest laid out its future in an ominously titled “What’s Happening” page on Nest.com and a notice on the Works with Nest page. It sounds like a brutal outcome for users, who are looking at a dead-end ecosystem, potentially broken smart homes, and the shattering of the Google/Nest privacy firewall.
John Urschel is used to having to prove himself. In four years at Penn State and three with the Baltimore Ravens, Urschel could never let up. It was a daily challenge to prove to coaches, scouts, and GMs that he was big enough, tough enough, and athletic enough to earn a starting spot on the offensive line.
But when Urschel was accepted into the PhD program for applied mathematics at MIT in 2016, he faced a different challenge — to prove that he wasn’t just a novelty. That he deserved to be learning and teaching with some of the most brilliant mathematical minds on the planet.
The Massachusetts Institute of Technology (MIT) and Liberty Mutual Insurance announced a $25 million, five-year collaboration to support artificial intelligence (AI) research in computer vision, computer language understanding, data privacy and security, and risk-aware decision making, among other topics.
Stony Brook University officially launched the new Institute for AI-Driven Discovery and Innovation to advance AI research and apply the transformative power of innovation driven by AI across disciplines. The AI Institute will focus on four grand challenges: health care; infrastructure; education; and, finance. It will also focus on five foundational research areas: automated and scalable knowledge acquisition; predictive intelligence; explainable AI; trustworthy AI; and, ethical AI.
The AI Institute for AI-Driven Discovery and Innovation will support efforts centered on the overarching vision of Human-Machine Symbiosis, based on the idea that AI technology should amplify human intelligence, instead of replacing it. In this way, it will serve as an intellectual hub to coordinate and encourage faculty AI research and educational initiatives across the University and beyond.
Maria Uriarte, a professor in the department of ecology, evolution and environmental biology at Columbia University, is trying to understand how Hurricane Maria in 2017 altered plant life in Puerto Rico.
But trying to identify which species of tree survived and which was destroyed over acres of rain forests by looking at aerial photographs is a near-impossible task for the human eye.
“The challenge with ecology as a field and climate change as an area is that the world is highly variable,” Dr. Uriarte said. “You can learn something about what happens in one place, but then the question is: How applicable is this in other areas that I haven’t worked at?”
For years the tech industry has dreamed of computing appliances that are considered unremarkable items of household machinery, like washing machines or fridges. The smart speaker has finally realised this promise. It can sit on a kitchen counter and summon the wonders of the internet without the need for swiping or typing.
Science Advances; Gregory D. Erhardt, Sneha Roy, Drew Cooper, Bhargava Sana, Mei Chen and Joe Castiglione
This research examines whether transportation network companies (TNCs), such as Uber and Lyft, live up to their stated vision of reducing congestion in major cities. Existing research has produced conflicting results and has been hampered by a lack of data. Using data scraped from the application programming interfaces of two TNCs, combined with observed travel time data, we find that contrary to their vision, TNCs are the biggest contributor to growing traffic congestion in San Francisco. Between 2010 and 2016, weekday vehicle hours of delay increased by 62% compared to 22% in a counterfactual 2016 scenario without TNCs. The findings provide insight into expected changes in major cities as TNCs continue to grow, informing decisions about how to integrate TNCs into the existing transportation system. [full text]
For roughly 18 months, AirPods play music, or podcasts, or make phone calls. Then the lithium-ion batteries will stop holding much of a charge, and the AirPods will slowly become unusable. They can’t be repaired because they’re glued together. They can’t be thrown out, or else the lithium-ion battery may start a fire in the garbage compactor. They can’t be easily recycled, because there’s no safe way to separate the lithium-ion battery from the plastic shell. Instead, the AirPods sit in your drawer forever.
Stanford University, Global Digital Policy Incubator
Stanford, CA May 23, starting at 1:30 p.m., Stanford University (Oksenberg Conference Room, 3rd Floor). “The RDR Index is the leading ranking of 24 of the world’s most powerful telecommunications, internet, and mobile companies on their commitments and policies affecting users’ freedom of expression and privacy.” [free, registration required]
“We welcome early-stage startups across the food and agriculture ecosystem to apply. Startups admitted into the NY-based accelerator program will follow a structured curriculum over a 5-month timeline, beginning in October 2019.” Deadline to apply is June 1.
London, England October 4-5 at BMA House. The mission “is to bring together all parties working on automated approaches to augment manual efforts on improving the truthfulness and trustworthiness of online communications.” Deadline for submissions is June 3.
McKinsey & Company; Roger Burkhardt, Nicolas Hohn, and Chris Wigley
As AI supercharges business and society, CEOs are under the spotlight to ensure their company’s responsible use of AI systems beyond complying with the spirit and letter of applicable laws. Ethical debates are well underway about what’s “right” and “wrong” when it comes to high-stakes AI applications such as autonomous weapons and surveillance systems. And there’s an outpouring of concern and skepticism regarding how we can imbue AI systems with human ethical judgment, when moral values frequently vary by culture and can be difficult to code in software.
While these big moral questions touch a select number of organizations, nearly all companies must grapple with another stratum of ethical considerations, because even seemingly innocuous uses of AI can have grave implications. Numerous instances of AI bias, discrimination, and privacy violations have already littered the news, leaving leaders rightly concerned about how to ensure that nothing bad happens as they deploy their AI systems.
The best solution is almost certainly not to avoid the use of AI altogether—the value at stake can be too significant, and there are advantages to being early to the AI game. Organizations can instead ensure the responsible building and application of AI by taking care to confirm that AI outputs are fair, that new levels of personalization do not translate into discrimination,
Andreessen Horowitz, a16z blog, Martin Casado and Peter Lauten
“Treating data as a magical moat can misdirect founders from focusing on what is really needed to win. So, do data network effects exist? How might a scale effect behave differently from the traditional network effect? And once we get past the hype of having to have them… how can startups establish more durable data moats — or at least figure out where data best plays into their strategy?”
Ruby on Jets allows you to create and deploy serverless services with ease, and to seamlessly glue AWS services together with the most beautiful dynamic language: Ruby. It includes everything you need to build an API and deploy it to AWS Lambda. Jets leverages the power of Ruby to make serverless joyful for everyone.
As a practitioner, my goal is to get people excited about how data relates to them: to engage their curiosity, and for them to feel inspired, rather than overwhelmed by it. Design is the best means we have for making information useful—not just presenting it visually, but giving people ways to work and think with it. To this end, there are four central themes that we’re looking at when we talk about data and design.
And in the tropiest of design tropes (tropiest might not be a word), I’m gonna do this with a framework of four words that all start with the same letter.
New America Foundation, Sophie Nguyen and Amanda Martinez
“The HigherEd Polling Dashboard comprises public opinion surveys on higher education that have been conducted in the U.S. since 2010. Surveys in the dashboard explore the general public’s opinion on issues pertaining to higher education such as funding, diversity, and value. Some focus on opinion of first-year college students, college and university presidents, and faculty.”