Discussions about the application of artificial intelligence (AI) in healthcare often span multiple areas, most commonly about making more accurate diagnoses, identifying at-risk populations, and better understanding how individual patients will respond to medicines and treatment protocols. To date, there has been relatively little discussion about practical applications of AI to improve medication management across the care continuum, an area this article will address. What's the first thing that comes to mind when someone mentions prescription drugs in the United States? In poll after poll, the high and rising costs of medications are American voters' top healthcare-related issue. This concern is well founded.
Microsoft's talks to acquire Tik Tok don't make a whole lot of sense on the surface. In fact, nothing about this deal makes sense given you have a tech giant that is known for the enterprise, President Trump tweeting about Tik Tok, legislators chiming in and a 45-day deal deadline. Sure, I've read a few Wall Street analysts do some mental gymnastics to argue for the Microsoft purchase of Tik Tok. Depending on price ($10 billion too good to pass up and $50 billion crazy), Microsoft CEO Satya Nadella is going to have some explaining to do. With all that said, here is a bit of informed speculation about why this Microsoft-Tik Tok lunacy is happening. The Department of Defense's JEDI cloud contract is to be announced soon.
A new galaxy, which is likely to be very young by cosmic standards, has been discovered thanks to the power of big data and machine learning. The galaxy, captured by an international team studying data from the Subaru Telescope in Hawaii, has broken the record for the lowest oxygen abundance in any galaxy observed from Earth. Extremely low oxygen abundance The galaxy, called HSC J1631 4426, has an extremely low oxygen abundance of 1.6% solar abundance, meaning it breaks the previous record of the lowest known oxygen abundance in a […]
A new galaxy, which is likely to be very young by cosmic standards, has been discovered thanks to the power of big data and machine learning. The galaxy, captured by an international team studying data from the Subaru Telescope in Hawaii, has broken the record for the lowest oxygen abundance in any galaxy observed from Earth. The galaxy, called HSC J1631 4426, has an extremely low oxygen abundance of 1.6% solar abundance, meaning it breaks the previous record of the lowest known oxygen abundance in a galaxy. This, the researchers explained in a press release, means that the stars in the galaxy likely formed very recently. As galaxies that are still in the early stages of formation in the modern Universe are rare, the international team behind the new discovery searched for them using wide-field imaging data taken with the Subaru Telescope.
Investment in warehouse robotics technology startups clocked in at $381 million in the first quarter of 2020, up 57% from the same period in 2019. The study examines venture capital (VC) investment levels, trends, new business models and notable startups within last-mile delivery, freight, warehousing and enterprise supply chain management. While warehouse robotics investment exploded during this period, overall investment in supply chain tech declined in the first quarter of 2020. Supply chain technology companies raised $1 billion in VC across 59 deals in North America and Europe, a decline from $1.4 billion in Q1 2019. The PitchBook report comes one month after the firm conducted a survey in partnership with last month's Collision From Home conference examining investor sentiment toward technology in a post-COVID-19 world.
The resurgence of artificial intelligence (AI) is largely due to advances in pattern-recognition due to deep learning, a form of machine learning that does not require explicit hard-coding. The architecture of deep neural networks is somewhat inspired by the biological brain and neuroscience. Like the biological brain, the inner workings of exactly why deep networks work are largely unexplained, and there is no single unifying theory. Recently researchers at the Massachusetts Institute of Technology (MIT) revealed new insights about how deep learning networks work to help further demystify the black box of AI machine learning. The MIT research trio of Tomaso Poggio, Andrzej Banburski, and Quianli Liao at the Center for Brains, Minds, and Machines developed a new theory as to why deep networks work and published their study published on June 9, 2020 in PNAS (Proceedings of the National Academy of Sciences of the United States of America).
Across the University of Iowa campus, researchers are using artificial intelligence, machine learning, and big data to tackle pressing issues related to healthcare, space exploration, and public health, including the COVID-19 pandemic. For more than 30 years, this research has been made possible through expertise as well as logistical and financial support from the UI College of Engineering. "Our ability to collaborate across disciplines, departments, and colleges demonstrates that the cutting-edge research done in our College of Engineering is tremendously important to the work of our entire campus," said Harriet Nembhard, dean of the College of Engineering. "These partnerships exist in ways one might expect such as in medical imaging in the UI Carver College of Medicine and injury prevention in the College of Public Health but we also support work in the Tippie College of Business, the College of Liberal Arts and Sciences, and the College of Education." In all, the Iowa Initiative for Artificial Intelligence, funded by the Office of the Provost, Colleges of Engineering, Liberal Arts and Sciences, Medicine, Business, and Education, as well as several UI departments and research centers leads 27 active projects across campus, many of which involve engineering researchers.
Total conference attendance at the 2020 Design Automation Conference (DAC), the industry's premier event dedicated to the design and design automation of electronic circuits and systems, leapt by 52% compared to DAC 2019, according to the 57th DAC Executive Committee (EC). The intense engagement at the 57th DAC, held for the first time virtually due to the recent pandemic, reflected a voracious appetite among engineers for information and insights to propel design innovation. Submissions to DAC's research track increased by 20% in the past two years, and the Designer, IP and Embedded Tracks submissions increased by 15% compared to 2019, continuing a steady three-year rise. The global reach of DAC, July 19 - 24, soared at the 2020 virtual event with attendance from the following regions: 24% Asia Pac, 11% Europe, 52% United States and 13% a combination of Canada, South America and Middle East. Despite the economic and social disruption caused by the pandemic, design innovation never sleeps," said Zhuo Li, General Chair of the 57th DAC. "We had record attendance viewing each of the four Keynotes, plus attendees globally were able to view the recorded technical sessions at their leisure in their respected time-zones.
The conference will host keynote presentations from leading voices in data-driven innovation, lightning talks from Columbia University researchers, & interactive poster & technology demonstrations. Data Science Day provides a forum for innovators in academia, industry, & government to connect. Keynote Speakers Pat Bajari, Chief Economist, Vice President of Artificial Intelligence, Amazon Eric Schmidt, Technical Advisor to the Board, Alphabet Columbia University & Columbia University Data ScienceInstitute Affiliated Faculty Talks Lightning Talk:Cause, Learn, Optimize & Reason Melanie Wall, Professor, Department of Biostatistics, Mailman School of Public Health; & Director of Mental Health Data Science in the Department of Psychiatry, Columbia University Irving Medical Center & the New York State Psychiatric Institute Samory Kpotufe, Associate Professor, Department of Statistics, Faculty of Arts & Sciences Elias Bareinboim, Associate Professor, Department of Computer Science, Columbia Engineering; & Director of the Causal Artificial Intelligence (CausalAI) Laboratory, Columbia University Clifford Stein, Professor of Industrial Engineering & Operations Research, Department of Computer Science, Columbia Engineering; & Associate Director for Research, Data Science Institute, Columbia University Lightning Talk: Human Machine: A New Hybrid World Oded Netzer, Professor of Business, Marketing Division, Columbia Business School Lydia Chilton, Assistant Professor, Department of Computer Science, Columbia Engineering Sarah Rossetti, Assistant Professor, Biomedical Informatics, Department of Biomedical Informatics; Assistant Professor, School of Nursing, Columbia University Irving Medical Center Lightning Talk: Ethics & Privacy: Terms of Usage Roxana Geambasu, Associate Professor, Department of Computer Science, Columbia Engineering Rafael Yuste, Professor, Department of Biological Sciences, Faculty of Arts & Sciences Jeff Goldsmith, Associate Professor, Department of Biostatistics, Columbia University Mailman School of Public Health What are my transportation/parking options for getting to & from the event? Please visit the following link for directions & parking information: http://transportation.columbia.edu/For How can I contact the organizer with any questions?