Joe Biden’s presidential campaign, in a bid to broaden its appeal with younger voters and small donors, has turned to a data science software and consulting company backed by former Google chairman Eric Schmidt.
The emergence of deep learning and AI technologies on mobile and embedded devices has created exciting new possibilities for applications such as detecting cancers, self-driving cars and smart homes. However, developing robust Deep Neural Network (DNN) models for everyday devices remains a significant challenge for both human engineers and computers. A single DNN can require billions of expensive floating-point operations for each input classification. This computation overhead limits the applicability of DNNs to low-power, embedded platforms and incurs high cost in data centers. Accordingly, techniques that enable efficient processing of DNNs to improve energy-efficiency and throughput without sacrificing application accuracy or increasing hardware cost are critical to the widespread deployment of DNNs in AI systems. Since raising a seed round with TandemLaunch Inc. and partnering with Brown University and University of Southern California in early 2018, our team at Deeplite is tackling this problem to make artificial intelligence more accessible and affordable.
Washington state lawmakers passed a major tax hike on the region’s biggest tech companies over the weekend.
The bill increases the state business and occupation tax by 67 percent on “advanced computing businesses with revenue of more than $100 billion.” That category applies to two companies: Amazon and Microsoft.
Microsoft has been pushing for the bill as a way to increase the number of Washington students who are prepared for the tech jobs of the future. The Bureau of Labor estimates that there will be 1.4 million computer-science related jobs and just 400,000 graduates with the skills needed to fill them by 2020.
AI-MC extends CMC (Computer-Mediated Communication). Our interpersonal communication is no longer simply mediated by technology; it is increasingly augmented—or even generated—by algorithms to achieve specific communicative or relational outcomes.
Sen. Bernie Sanders flaunted his ground operation Saturday with what he called the “largest distributed day of action ever in a presidential campaign” and announced a new online organizing tool called BERN.
“We need to put together the strongest grassroots movement in the history of politics,” Sanders said in a pre-recorded video played for more than 4,700 volunteer-driven organizing kickoff events nationwide. “And we’re off to a good start!”
The online tool allows everyday supporters to contribute to the campaign’s voter database by logging names and background information of anyone from a family member to a stranger met at a bus stop. It matches each name to a voter record before noting their level of support, priority issue and even union membership.
Northrop Grumman Corporation launched a new research consortium with universities to advance machine learning and artificial intelligence programs. The REALM consortium is an industry-academia partnership to advance research, foster collaboration and address technological challenges due to advances in machine learning, cognition and artificial intelligence.
As part of the consortium, Northrop Grumman has selected three research teams to collaborate on applied research that addresses key customer applications including multiple sensor track classification, identification and correlation; situational knowledge on demand; and quantitative dynamic adaptive planning.
Each team is comprised of multiple universities. All three teams, including researchers from Carnegie Mellon University; Johns Hopkins University; Massachusetts Institute of Technology, Purdue University; Stanford University; University of Illinois at Chicago; University of Massachusetts Amherst and the University of Maryland, College Park received a total of $1.2 million research funding from Northrop Grumman.
Walmart has opened a store in Levittown, N.Y. that is intended to showcase the power of artificial intelligence.
The store, announced last week, is packed with video cameras, digital screens, and over 100 servers, making it appear more like a corporate data center than a discount retailer.
All that machinery helps Walmart automatically track inventory so that it knows when toilet paper is running low or that milk needs restocking. The company’s goal is to create “a glimpse into the future of retail,” when computers rather than humans are expected to do a lot of retail’s grunt work.
Johns Hopkins University announced Monday it is reorganizing its Center for Government Excellence, a think tank that trains city-government officials on how to incorporate data analytics into their decision-making processes, under a new program called the Centers for Civic Impact.
The program’s introduction represents an expansion of the university’s effort to promote the use of data and research in public administration. In addition to housing the Center for Government Excellence, also known as GoxEx, the program also includes an educational component, GovEx Academy, in which public-sector employees can take online academic courses in data science, and a Center for Applied Public Research, which will develop economic, workforce, nutrition and educational policy recommendations using evidence-based methods.
In February, the Institute established five working groups to generate ideas for different components of the structure and operation of the new MIT Stephen A. Schwarzman College of Computing. Nicholas Roy, professor of aeronautics and astronautics, and Benoit Forget, associate professor of nuclear science and engineering, are co-chairs of the Working Group on College Infrastructure, which is charged with examining how to ensure that departments, labs, and centers (DLCs) have the information and resources they require to meet their computational needs such as accessing and storing data. MIT News checked in with Roy and Forget to find out about the group’s goals, processes, and progress so far.
One fundamental problem with Alexa or other voice assistants is that the technology is prone to fail. Devices like the Echo come equipped with always-on microphones that are only supposed to record when you want them to listen. While some devices require the push of a physical button to beckon Alexa, many are designed to start recording you after you’ve said the wake word. Anyone who has spent any time using Alexa knows that it doesn’t always work like this. Sometimes the software hears random noise, thinks it’s the wake word, and starts recording.
The extent to which false positives are a problem became glaringly evident the moment I started reading through my history of Alexa commands on Amazon’s website.
Detecting cancer might be AI’s most altruistic and convoluted challenge yet. Standard screening methods such as radiological imaging can miss signs of cancer, or return a false negative (as it does in 20-30% of cases). The process of scanning images is particularly in need of improvement, as doctors must often visually search for signs of cancer which can leave only the largest, most advanced tumors to be detected. Hereditary testing is another detection method that determines genetic predisposition to cancer, but this does not provide much detail and cannot reveal if a person has cancer now.
AI can not only greatly improve the accuracy of image detection for cancer, but could also open up entirely new fields between genomics and cancer screening. AI faces its own unique challenges in this field – such as the lack of enough data to train neural networks – but companies on the cutting-edge of cancer detection are finding novel ways to get around the problems, and achieving impressive results.
How does a leading research institution ensure the flow of computer science talent and keep the most talented minds in the space focused on solving today’s truly challenging problems? The Microsoft Research Faculty Fellowship recognizes innovative, promising new faculty members with $100,000 USD annually for two years to pursue breakthrough, high-impact research. The grant is an unrestricted gift, providing the Fellows the freedom to plan their research, hire graduate students, build labs, and acquire equipment.
These researchers were chosen through a rigorous, multi-tier selection process that involved 22 reviewers. The reviewers looked for future leaders who are at the beginning of their careers. The selection criteria included not only the capability to pursue cutting-edge research, but also the skills that are necessary to bring those ideas to fruition and to communicate complex concepts.
Earlier this week, WIRED spoke with Heather Wilson, the secretary of the Air Force. She was just finishing a visit to Carnegie Mellon University, which has developed a special relationship with the service. We spoke about the Air Force’s new Science and Technology Strategy, which was announced earlier this month, as well as their new initiatives in artificial intelligence, surveillance, and space.
Hola, Alexa. ¿Cómo estás? Amazon today announced that the Alexa Skills Kit (ASK), the software development kit that enables developers to build voice apps (or skills) for Alexa, now supports Spanish in the U.S. courtesy a new voice model. It also revealed that, thanks to this same model, Alexa-enabled devices in the U.S. will gain support for Spanish later this year.
The British Psychological Society, Research Digest, Emma Young
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How do we acquire our native language? Are the basics of language and grammar innate, as nativists argue? Or, as empiricists propose, is language something we must learn entirely from scratch?
This debate has a long history. To get at an answer, it’s worth setting the theories aside and instead looking at just how much information must be learned in order to speak a language with adult proficiency, argue Francis Mollica at the University of Rochester, US, and Steven Piantadosi at the University of California, Berkeley. If the amount is vast, for instance, this could indicate that it’s impracticable for it all to be learned without sophisticated innate language mechanisms. In their new paper, published in Royal Society Open Science, Mollica and Piantadosi present results suggesting that some language-specific knowledge could be innate – but probably not the kind of syntactic knowledge (the grammatical rules underlying correct word order) that nativists have tended to argue in favour of. Indeed, their work suggests that the long-running focus on whether syntax is learned or innate has been misplaced.
Berlin, Germany November 25-26. “Our Open Call for DN19 Speakers is now officially live. Whether you’re a seasoned speaking pro or a first-time applicant with something vital to say, we want to hear from you!”
“scite is a platform that allows anyone to see if a scientific report has been supported or contradicted by subsequent work. We do this by using deep learning and a network of experts to analyze hundreds of millions of citation statements, classifying them as supporting, contradicting, or just mentioning, and presenting the results in an easy to understand interface. Thus, anyone can check if a scientific paper has been supported or contradicted with just a few clicks.”
“Build Accelerator, BuildXL for short, is a build engine originally developed for large internal teams at Microsoft, and owned by the Tools for Software Engineers team, part of the Microsoft One Engineering System internal engineering group. Internally at Microsoft, BuildXL runs 30,000+ builds per day on monorepo codebases up to a half-terabyte in size with a half-million process executions per build, using distribution to thousands of datacenter machines and petabytes of source code, package, and build output caching. Thousands of developers use BuildXL on their desktops for faster builds even on mega-sized codebases.”
University of Michigan, Institute for Research on Innovation & Science
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The University of Wisconsin-Madison and the University of Michigan have publicly released data on student earnings through agreements with the Institute for Research on Innovation and Science (IRIS). IRIS partners with the U.S. Census Bureau to link data from participating universities to the Census Bureau’s Longitudinal Employer-Household Dynamics (LEHD) dataset to produce detailed earnings information on alumni.
Release of the data, which show 75th percentile, median, and 25th percentile income levels one, five and 10 years after graduation, is an important step not only for prospective students and their families, but for researchers seeking to learn more about the value of a university education, said Jason Owen-Smith, IRIS executive director and a professor of sociology at U-M.
Stories build empathy and make the user needs and pain points memorable to your team. Effective stories speak the language of the audience, are rooted in data, and take advantage of compelling artifacts.