As Executive Vice President of UC Health, I applaud Governor Brown’s proposal to allocate $30 million to establish the California Institute to Advance Precision Health and Medicine.
This institute would build on the exceptional work of the California Initiative to Advance Precision Medicine (CIAPM), an ongoing partnership between the State of California, the University of California system, and nonprofit, academic and industry partners to stimulate collaboration and innovation in precision medicine across California.
Hosted by UC Health and UC San Francisco, the initiative is working to advance the field of precision medicine by integrating clinical data with genetic, environmental, socioeconomic, mobile and other data from patients so that scientists can understand diseases better and develop more precise therapies.
General, widespread legislative regulation of AI is not going to be the right way to prepare our society for these changes. The AI field is already humming with a wide variety of new research at an international scale, such that blindly constraining AI research in its early days in the United States would only serve to put us behind the global curve in developing the most important technology of the future. It is also worth noting that there are many applications of AI currently under development that have huge potential benefits for humanity in the fields of medicine, security, finance, and personal services; we would risk a high human and economic cost by slowing or stopping research in those areas if we hastily impose premature, overbearing, and poorly understood constraints.
The most impactful way to shape the future of AI is not going to be through the regulation of research, but rather through understanding and correctly controlling the tangible impacts of AI on our lives. For example, it is our belief that AI should not be weaponized, and that humans should always have the ultimate “off switch.” Beyond these obvious limitations, there are three rules we propose for AI that can be meaningfully applied now to mitigate possible future harm.
The New York Times, Daisuke Wakabayashi and Nick Wingfield
from
A management consulting firm recently looked at heavy users of virtual assistants, defined as people who use one more than three times a day. The firm, called Activate, found that the majority of these users turned to virtual assistants to play music, get the weather, set a timer or ask questions.
Activate also found that the majority of Alexa users had never used more than the basic apps that come with the device, although Amazon said its data suggested that four out of five registered Alexa customers have used at least one of the more than 30,000 “skills” — third-party apps that tap into Alexa’s voice controls to accomplish tasks — it makes available.
The FedEx Institute of Technology, located at the University of Memphis (UofM), has gained a powerful ally in its efforts to increase the size and technical sophistication of the Mid-South technology workforce. Analytics leader SAS is locating a first-of-its-kind training center at the FedEx Institute, offering the resources people need to gain valuable SAS® skills and certifications.
Carnegie Mellon University announced Monday it has been chosen to lead a $27.5 million research initiative with five other universities to connect computing systems and the cloud.
The CONIX Research Center will be headquartered at CMU and will be directed by CMU’s Anthony Rowe, who is associate professor of electrical and computer engineering. The funding from the Supercomputer Research Corp. comes from industry and the Defense Advanced Research Projects Agency (DARPA).
Elsevier, the information analytics business specializing in science and health, and the University of Oxford, a world-leading centre of learning, teaching and research and the oldest university in the English-speaking world, today announced their five-year collaboration to develop exceptional research talent in the field of mathematics and data science.
The initiative will enable five early career researchers from Oxford Mathematics to apply for the internationally competitive three-year Hooke and Titchmarsh Fellowship Program. Through this fellowship scheme the selected post-doc researchers are provided with opportunities to work alongside and learn from globally-distinguished academics who are at the forefront of the most profound advances in mathematics.
The University of Virginia’s School of Engineering and Applied Science has been picked to establish a center to help remove a bottleneck that is hindering technological advances.
The new Center for Research in Intelligent Storage and Processing in Memory, or CRISP, will bring together researchers from eight universities to remove the separation between memories that store data and processors that operate on the data.
Distinguished scientist and professor Andrew McCallum, director of the Center for Data Science at the University of Massachusetts Amherst, will lead a new partnership with the Chan Zuckerberg Initiative to accelerate science and medicine. The goal of this project, called Computable Knowledge, is to create an intelligent and navigable map of scientific knowledge using a branch of artificial intelligence known as knowledge representation and reasoning.
The Computable Knowledge project will facilitate new ways for scientists to explore, navigate, and discover potential connections between millions of new and historical scientific research articles. Once complete, the service will be accessible through Meta, a free CZI tool, and will help scientists track important discoveries, uncover patterns, and deliver insights among an up-to-date collection of published scientific texts, including more than 60 million articles.
When we both joined Google Cloud just over a year ago, we embarked on a mission to democratize AI. Our goal was to lower the barrier of entry and make AI available to the largest possible community of developers, researchers and businesses.
Our Google Cloud AI team has been making good progress towards this goal. In 2017, we introduced Google Cloud Machine Learning Engine, to help developers with machine learning expertise easily build ML models that work on any type of data, of any size. We showed how modern machine learning services, i.e., APIs—including Vision, Speech, NLP, Translation and Dialogflow—could be built upon pre-trained models to bring unmatched scale and speed to business applications. Kaggle, our community of data scientists and ML researchers, has grown to more than one million members. And today, more than 10,000 businesses are using Google Cloud AI services, including companies like Box, Rolls Royce Marine, Kewpie and Ocado.
Harvard Business Review, Lindsay Page and Hunter Gehlbach
from
As AI continues to develop, a major test of its potential will be whether it can replace human judgment in individualized, complex ways. At Georgia State University, we investigated a test case where AI assisted high school students in their transition to college, helping them to navigate the many twists and turns along the way.
From the perspective of an AI system, the college transition provides intriguing challenges and opportunities. A successful system must cope with individual idiosyncrasies and varied needs. For instance, after acceptance into college, students must navigate a host of well-defined but challenging tasks: completing financial aid applications, submitting a final high school transcript, obtaining immunizations, accepting student loans, and paying tuition, among others. Fail to support students on some of these tasks and many of them — particularly those from low-income backgrounds or those who would be the first in their families to attend college — may succumb to summer melt, the phenomenon where students who intend to go to college fail to matriculate. At the same time, providing generic outreach to all students — including those who have already completed these tasks or feel confident that they know what they need to do — risks alienating a subset of students. In addition, outreach to students who are on-track may inadvertently confuse them or lead them to opt out of the support system before they might actually need it.
A recent poll found that a majority of Americans are worried about operating cars on the same roads as driverless vehicles.
Sixty-four percent of those surveyed said they are concerned about sharing the streets with driverless vehicles, according to a poll from Advocates for Highway & Auto Safety.
Thirty-four percent of Americans surveyed said they were not concerned, while 2 percent of those polled said they did not know.
Today was the 6th annual AAS Hack Day, at #AAS231 in Washington DC. (I know it was 6th because of this post.) It was an absolutely great day, organized by Kelle Cruz (CUNY), Meg Schwamb (Gemini), and Jim Davenport (UW & WWU), and sponsored by Northrup Grumman and LSST. The Hack Day has become an integral part of the AAS winter meetings, and it is now a sustainable activity that is easy to organize and sponsor.
Georgia Institute of Technology, School of Music and Center for Music Technology
from
Atlanta, GA “An annual, 48-hour competition run by the Georgia Tech School of Music and the Georgia Tech Center for Music Technology. This year’s hackathon will be held at the Invention Studio. The competition starts 5pm on Friday evening, February 9.”
New York, NY March 5-9 at Flatiron Institute. “This workshop (inspired by the Gaia Sprints) is designed to bring together a group of people with a common interest in scientific discovery using data from NASA’s forthcoming TESS Mission.” Deadline for applications is January 26.
Gothenberg, Sweden Workshop is May 29, co-located with ICSE 2018. ” FairWare 2018 brings together academics, practitioners, and policy makers interested in solving this problem and creating software engineering technology to improve software fairness.” Deadline for submissions is February 5.
“We want you to tell us what unique research questions you think All of Us could address. Your input will be considered at a Research Priorities Workshop in March 2018 and ultimately help us build out the All of Us research platform with the tools needed to answer those questions.” Deadline for submissions is February 23.
The 2018 Data Science Bowl offers our most ambitious mission yet: Create an algorithm to automate nucleus detection and unlock faster cures. Deadline for entries is April 9.
This free, online course is for someone who wants to start doing data science and machine learning right now. You’ll spend more time writing code than reading about it. You’ll get the theoretical background you need to make good modeling decision, but won’t waste your time with historical background that won’t help you become a practicing data scientist.
Choosing a machine learning (ML) library to solve predictive use cases is easier said than done.
There are many to choose from, and each have their own niche and benefits that are good for specific use cases. Even for someone with decent experience in ML and data science, it can be an ordeal to vet all the varied solutions. Where do you start? At Salesforce Einstein, we have to constantly research the market to stay on top of it. Here are some observations on the top five characteristics of ML libraries that developers should consider when deciding what library to use:
The marketplace for science search engines is competitive and crowded. But a database launched on 15 January aims to provide academics with new ways to analyse the scholarly literature — including the grant funding behind it.
Dimensions not only indexes papers and their citations, but also — uniquely among scholarly databases — connects publications to their related grants, funding agencies, patents and clinical trials. The tool “should give researchers more power to look at their fields and follow the money”, says James Wilsdon, a research-policy specialist at the University of Sheffield, UK.
The product was created by London-based technology firm Digital Science (operated by the Holtzbrinck Publishing Group, which also has a majority share in Nature’s publisher). It says that it worked with more than 100 research organizations and funders to build the database, which is an extension of a previous product, also called Dimensions, that focused on indexing grant funding. Anyone can search through publications free of charge, and see associated grants, patents and citation-based metrics. But institutions and funders must buy access to search and analyse grant and patent data, as well as to use an application programming interface (API) that allows automated data queries
R-bloggers, Shirin's playgRound, Dr. Shirin Glander
from
The plumber package for R makes it easy to expose existing R code as a webservice via an API (Trestle Technology, LLC 2017).
You take an existing R script and make it accessible with plumber by simply adding a few lines of comments. If you have worked with Roxygen before, e.g. when building a package, you will already be familiar with the core concepts.