The drug, baricitinib, is currently marketed by Eli Lilly to treat rheumatoid arthritis. Now, thanks to AI, it is being tested against COVID-19 in a major randomised-controlled trial in collaboration with the U.S. National Institute for Allergies and Infectious Diseases (NIAID) in combination with remdesivir, an antiviral drug from Gilead Sciences that recently won emergency-use approval for COVID-19. Eli Lilly has now commenced its own independent trial of baricitinib as a therapy for COVID-19 in South America, Europe and Asia.
The concept of frugal innovation originated in emerging markets, where social entrepreneurs and enthusiastic designers perfected the idea of creating low-cost, highly user-friendly devices that also fulfil a social need. A clay fridge that uses no electricity but keeps food cool, mobile money services for people without bank accounts like M-PESA, and a billboard that collects water from humid air in a rain-scarce area of Peru are all cited as examples of frugal innovation in developing markets. But increasingly the idea is being used more broadly. The recent COVID-19 outbreak has shown just how far frugal innovation can take off in developed markets: companies, healthcare organisations and entrepreneurs were faced with a real problem to tackle in a short amount of time with unexpectedly limited resources. That resulted in innovations like PPE that could be 3D printed at home or made from scuba masks, ventilators hacked with readily available equipment to double their capacity, and companies sharing the designs for their kit to allow other organisations to manufacture it themselves.
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.
COVID-19 Outbreak-Global Artificial Intelligence (AI) in Healthcare Industry Market Report-Development Trends, Threats, Opportunities and Competitive Landscape in 2020 is latest research study released by HTF MI evaluating the market, highlighting opportunities, risk side analysis, and leveraged with strategic and tactical decision-making support. The study provides information on market trends and development, drivers, capacities, technologies, and on the changing investment structure of the COVID-19 Outbreak-Global Artificial Intelligence (AI) in Healthcare Market. Some of the key players profiled in the study are Zephyr Health, Inc., Atomwise, Inc, Enlitic, Inc., Nvidia Corporation, Welltok, Inc., General Vision, Inc., Microsoft Corporation, Sentirian, IBM Corporation, Next IT Corporation, Intel Corporation, Google Inc. & Siemens Healthineers GmbH. If you are involved in the COVID-19 Outbreak- Artificial Intelligence (AI) in Healthcare industry or intend to be, then this study will provide you comprehensive outlook. It's vital you keep your market knowledge up to date segmented by Patient Data and Risk Analysis, Medical Imaging and Diagnosis, Lifestyle Management and Monitoring, Virtual Assistant, Precision Medicine, In-Patient Care and Hospital Management, Drug Discovery, Wearables & Research,, Deep Learning, Querying Method, NLP & Context Aware Processing and major players.
Just getting workers to the office can be a challenge, amid ongoing travel restrictions aimed at containing the pandemic, said Gaston Silva Maldonado, project and systems analyst at Chilean food processor giant Agrosuper SA. "Our employees have been prevented from moving from one city to another, or even from one point of the city to another," Mr. Maldonado said, citing local lockdown rules. Based in Rancagua, Agrosuper employs about 3,500 office workers, in addition to thousands more in its production plants. So far, he said, only administrative staff and production plant workers deemed essential have returned to the workplace. With the Chilean government in July announcing a five-week plan to gradually ease travel restrictions within the country, the company is hoping to bring back more in the weeks ahead. To do that, Agrosuper has started using robotic process automation to scan and relay employment data on its more than 12,000 workers to a government website that issues emergency travel passes required at health checkpoints scattered throughout the country.
We have developed a globally applicable diagnostic Covid-19 model by augmenting the classical SIR epidemiological model with a neural network module. Our model does not rely upon previous epidemics like SARS/MERS and all parameters are optimized via machine learning algorithms employed on publicly available Covid-19 data. The model decomposes the contributions to the infection timeseries to analyze and compare the role of quarantine control policies employed in highly affected regions of Europe, North America, South America and Asia in controlling the spread of the virus. For all continents considered, our results show a generally strong correlation between strengthening of the quarantine controls as learnt by the model and actions taken by the regions' respective governments. Finally, we have hosted our quarantine diagnosis results for the top $70$ affected countries worldwide, on a public platform, which can be used for informed decision making by public health officials and researchers alike.
What if I told a story here, how would that story start?" Thus, the summarization prompt: "My second grader asked me what this passage means: …" When a given prompt isn't working and GPT-3 keeps pivoting into other modes of completion, that may mean that one hasn't constrained it enough by imitating a correct output, and one needs to go further; writing the first few words or sentence of the target output may be necessary.
While artificial intelligence capabilities have been evolving, the COVID-19 pandemic has accelerated adoption of these tools and made intelligent machines part of our new normal lives, according to a new report from Capgemini. More than half of the consumers surveyed (54%) use AI daily–compared to just 21% in 2018, the report, "The art of customer-centric artificial intelligence," finds. Sweden, Brazil, and the US have the highest daily interactions with AI. Contactless or non-touch interfaces are finding their way into numerous sectors, the report said. Over three-quarters (77%) of respondents expect to increase the use of touchless interfaces--such as voice assistants and facial recognition--to avoid direct interactions with humans or touchscreens during COVID-19, and 62% will continue to do so post-COVID.
Nvidia and the University of Florida (UF) today announced plans to build the fastest AI supercomputer in academia. By enhancing the capabilities of UF's existing HiPerGator supercomputer with the DGX SuperPod architecture, Nvidia claims the system -- which it expects will be up and running by early 2021 -- will deliver 700 petaflops (one quadrillion floating point operations per second) of performance. Some researchers within the AI community believe that capable computers, in conjunction with reinforcement learning and other techniques, can achieve paradigm-shifting AI advances. A paper recently published by researchers at the Massachusetts Institute of Technology, MIT-IBM Watson AI Lab, Underwood International College, and the University of Brasilia found that deep learning improvements have been "strongly reliant" on increases in compute. And in 2018, OpenAI researchers released an analysis showing that from 2012 to 2018, the amount of compute used in the largest AI training runs grew more than 300,000 times with a 3.5-month doubling time, far exceeding the pace of Moore's law.
Gabriel Guimaraes grew up in Vitória, Brazil, in a yellow house surrounded by star-fruit trees and chicken coops. His father, who wrote software for a local bank, instilled in him an interest in computers. On weekends, when Guimaraes got bored with Nintendo video games, he programmed his own. In grade school, he built a humanoid robot and wrote enough assembly code to make it zip around his home. In Vitória, an island city, his most ambitious peers dreamed of attending university in São Paulo, an hour away by plane.