In response to the coronavirus health crisis, USC researchers have made a hard pivot, adapting labs and lessons learned from treating other diseases to help check the virus and save lives. At their disposal are numerous technologies that give a human advantage, despite the fast-break spread of COVID-19 once it exited central China and spread across the globe. The disease has afflicted thousands of Californians and poses a serious risk to public health and the world economy. Tools such as supercomputers, software apps, virtual reality, big data and algorithms are now in play. They are using the tools to find ways to search and destroy coronavirus DNA, turn smartphones into personal protection devices and use people-friendly simulators to help cope with the crush of medical cases.
Applying artificial intelligence and other advanced digital technologies in the real economy isn't a job for tech nerds. Instead, Europe needs more people who can combine a deep knowledge of industry sectors with some expertise in data analytics. That was the verdict of guests at a Science Business roundtable on digital skills, hosted by Sorbonne University's Center for Artificial Intelligence (SCAI) in Paris on 23 January 2020. The event was part of a series of events and publications by Science Business as part of its Digital Skills project. Conversations about AI's impact on the labour market often assume it will create jobs for a small elite of tech nerds, while destroying many more conventional roles.
ResoluteAI, the Connect to Discover company, announced the addition of a News dataset to their Foundation search platform for scientific content. In partnership with FinTech Studios, the leading AI-based intelligent search and analytics platform for Wall Street, the News database provides ResoluteAI's clients with a robust offering of timely scientific content. Foundation is a multi-source research hub that allows public scientific content to be searched as if it's single-source. ResoluteAI applies the most sophisticated artificial intelligence and machine learning to unstructured content. This AI-driven solution creates structured metadata and organizes it into datasets that include Companies, Patents, Grants, Clinical Trials, Technology Transfer, and Publications.
Nothing is surprising about this list. Despite splashy claims that this place or that is the "new Silicon Valley," the real Silicon Valley is still the place to be. According to the latest report from Burning Glass, California, by far, is still hiring the most AI experts in terms of real numbers, followed by New York, Texas, and Massachusetts. Environmental issues and the perception of unfriendliness to business, and yet people still look to California as the nation's supreme tech hub. You have to look back at the history of the tech spread.
IMAGE: Simulated low temperature (left) and high temperature (right) phase of a 2D Ising model, where blue points are spins pointing up, and the red points are spins pointing down. Tokyo, Japan - Researchers from Tokyo Metropolitan University have used machine learning to study spin models, used in physics to study phase transitions. Previous work showed that image/handwriting classifying AI could be applied to distinguish states in the simplest models. The team showed the approach is applicable to more complex models and found that an AI trained on one model and applied to another could reveal key similarities between distinct phases in different systems. Machine learning and artificial intelligence (AI) are revolutionizing how we live, work, play, and drive.
MADRID – Some political leaders are hailing a potential breakthrough in the fight against COVID-19: simple pin-prick blood tests or nasal swabs that can determine within minutes if someone has, or previously had, the virus. The tests could reveal the true extent of the outbreak and help separate the healthy from the sick. But some scientists have challenged their accuracy. Hopes are hanging on two types of quick tests: antigen tests that use a nose or throat swab to look for the virus, and antibody tests that look in the blood for evidence someone had the virus and recovered. The tests are in short supply, and some of them are considered unreliable.
The C3.ai Digital Transformation Institute (C3.ai DTI) is a new research consortium established by C3.ai, Microsoft Corporation, the University of Illinois at Urbana-Champaign (UIUC), the University of California, Berkeley, Princeton University, the University of Chicago, the Massachusetts Institute of Technology, Carnegie Mellon University, and the National Center for Supercomputing Applications at UIUC. Jointly managed and hosted by UC Berkeley and UIUC, C3.ai DTI was created to establish the new Science of Digital Transformation of Societal Systems. C3.ai DTI's mission is to attract the world's leading scientists to join in a coordinated and innovative effort to advance the digital transformation of business, government, and society. Through partnerships with leading universities and strategic engagement with key industry partners, C3.ai DTI will catalyze advances in mathematical, statistical, and computing research, including Machine Learning (ML), Artificial Intelligence (AI), and the Internet of Things (IoT).
Researchers are utilising artificial intelligence (AI) to develop an early warning system that can identify manipulated images, deepfake videos and disinformation online in 2020 US election. The project is an effort to combat the rise of coordinated social media campaigns to incite violence, sew discord and threaten the integrity of democratic elections. According to the study, published in the journal Bulletin of the Atomic Scientists, the scalable, automated system uses content-based image retrieval and applies computer vision-based techniques to root out political memes from multiple social networks. "Memes are easy to create and even easier to share. When it comes to political memes, these can be used to help get out the vote, but they can also be used to spread inaccurate information and cause harm," said study researcher Tim Weninger, Associate Professor at the University of Notre Dame in the US.
To date, there are more than 830,000 data science LinkedIn profiles registered worldwide. Despite this number of Data Scientists available/in roles online currently, it's no secret there is still a major talent shortage. In fact, according to a report by O'Reilly Media, nearly half of all European companies are struggling to fill data science positions. Studies performed by Indeed's Hiring Lab show an overall increase of 256% in data science job openings since 2013, with an increase of 31% year over year from as recent as December 2018. Data science is a vast, complex industry with many subsets. Variations in roles oftentimes require such specific skillsets that positions are left unfilled for an average of up to 45 days. So what does this mean for you as someone in data science, engineering, or machine learning? There are start-ups, unicorns, and conglomerates that will want to work with you. For recruitment specialists, they want to be able to identify candidates who can offer organisations a unique set of skills.