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Trump threatens to move RNC without assurances from governor

Boston Herald

President Donald Trump threatened Monday to pull the Republican National Convention out of North Carolina if the state's Democratic governor doesn't immediately sign off on allowing a full-capacity gathering in August despite the ongoing COVID-19 pandemic. Trump's tweets about the RNC, planned for Charlotte, come just two days after North Carolina recorded its largest daily increase in positive cases yet. On Friday, Gov. Roy Cooper moved the state into a second phase of gradual reopening by loosening restrictions on hair salons, barbers and restaurants. But he said the state must continue to closely watch virus trends and has ordered indoor entertainment venues, gyms and bars to remain closed for several more weeks. "Unfortunately, Democrat Governor, @RoyCooperNC is still in Shutdown mood & unable to guarantee that by August we will be allowed… full attendance in the Arena," Trump tweeted Monday.


NASA seeks participants for eight-month isolation study

Daily Mail - Science & tech

NASA is on the hunt for volunteers for a'social isolation' mission that simulates the psychological effects of confinement. In a nod to the current virus pandemic, the space agency is after healthy participants to live together in isolation for eight months in Moscow, Russia. The ground based'SIRIUS-20' mission will help NASA learn more about'the physiological and psychological effects of isolation and confinement on humans'. The chosen participants – who have to be'US citizens, between the ages of 30 to 55 and'highly motivated' – will experience'environmental aspects' similar to those astronauts will experience on future missions to the Moon and Mars. SIRIUS is an international mission conducted in the NEK, a ground-based analog facility in Moscow.


KT deploys 5G autonomous carts at warehouses

ZDNet

One of the carts, called, Targo, will trail behind staff. South Korean telco KT has deployed autonomous carts with 5G connectivity at its smartphone warehouses to alleviate the workload of staff, the company announced. The carts were co-developed by South Korean autonomous robot developer Twinny. One version of the cart, dubbed NarGo, will have a cart that has multiple carts trailing behind it, like a freight train. It is designed to carry large quantities of cargo, with each cart being able to carry 100 kilograms of goods.


The Morning After: Texas Instruments makes it harder to cheat on its calculators

Engadget

Graphing calculators have clung on to school lives despite us all carrying around smartphones that are several magnitudes more powerful. In a bid to reduce cheating in exam settings, Texas Instruments is pulling support for assembly- and C-based programs. If you install the latest firmware update, those kinds of programs won't work, and you won't be able to roll-back the device. While this could please teachers worried that students will use apps on their calculator to cheat during exams, enthusiasts are, unsurprisingly, mad. It reduces the control programmers have over their calculator apps.


Assessing the information content of structural and protein–ligand interaction representations for the classification of kinase inhibitor binding modes via machine learning and active learning

#artificialintelligence

For kinase inhibitors, X-ray crystallography has revealed different types of binding modes. Currently, more than 2000 kinase inhibitors with known binding modes are available, which makes it possible to derive and test machine learning models for the prediction of inhibitors with different binding modes. We have addressed this prediction task to evaluate and compare the information content of distinct molecular representations including protein–ligand interaction fingerprints (IFPs) and compound structure-based structural fingerprints (i.e., atom environment/fragment fingerprints). IFPs were designed to capture binding mode-specific interaction patterns at different resolution levels. Accurate predictions of kinase inhibitor binding modes were achieved with random forests using both representations.


Rwanda has enlisted anti-epidemic robots in its fight against coronavirus – IAM Network

#artificialintelligence

With 314 confirmed cases of the virus as of May 22, the East African country has enlisted the help of five anti-epidemic robots to battle the virus. The robots were donated by the United Nations Development Program (UNDP) to the Kanyinya treatment center that treats Covid-19 patients in the capital city, Kigali. The robots -- named Akazuba, Ikirezi, Mwiza, Ngabo, and Urumuri -- were received by the country's Minister of Health and Minister of ICT and Innovation last week. They will be used for mass temperature screening, monitoring patient status, and keeping medical records of Covid-19 patients, according to Rwanda's Ministry of ICT and Innovation. Keeping healthworkers safeThe robots perform a number of tasks relating to managing coronavirus.


Automated screening of sickle cells using a smartphone-based microscope and deep learning

#artificialintelligence

Sickle cell disease (SCD) is a major public health priority throughout much of the world, affecting millions of people. In many regions, particularly those in resource-limited settings, SCD is not consistently diagnosed. In Africa, where the majority of SCD patients reside, more than 50% of the 0.2–0.3 million children born with SCD each year will die from it; many of these deaths are in fact preventable with correct diagnosis and treatment. Here, we present a deep learning framework which can perform automatic screening of sickle cells in blood smears using a smartphone microscope. This framework uses two distinct, complementary deep neural networks.


Here's how to check in on your AI system, as COVID-19 plays havoc

#artificialintelligence

The machine learning approach works well when these new cases are similar to the examples in the training data. The ability of machine learning algorithms to identify subtle patterns in the training data can allow it to make a faster and possibly better predictions than a human. However, if the new cases are radically different from the training data, and especially if we are playing by a whole new rulebook, then the patterns in the training data will no longer be a useful basis for prediction. Some algorithms are designed to continuously add new training data and therefore update the algorithm, but with large changes this gradual updating will not be sufficient. To learn completely new rules, machine learning algorithms need large amounts of new data.


Professor Erwin Loh posted on LinkedIn

#artificialintelligence

Scientists in #SouthKorea has developed an #artificialintelligence-based #deeplearning chest #Xray #COVID19 diagnosis technology that is more accurate than medical specialists, reported in a new study in IEEE Transactions on Medical #Imaging (8 May 2020). Link to press release: https://lnkd.in/gYzhUeH


Microsoft's new supercomputer will train AI to outperform humans

#artificialintelligence

Microsoft has teamed up with a startup co-founded by Elon Musk to build one of the fastest supercomputers in the world, the company announced Tuesday during its annual Build developers conference -- held virtually this year because of the coronavirus pandemic. The startup is OpenAI, the charter of which underscores that it's working to ensure that AI which can outperform humans nevertheless benefits all of humanity. Microsoft stressed that this work represents a key milestone in a partnership announced last year to jointly create new supercomputing technologies in Azure. This is a first step, the computing giant explained, toward debuting large AI models "and the infrastructure needed to train them" as a platform that developers and other organizations can build on. "The exciting thing about these models is the breadth of things they're going to enable," said Microsoft Chief Technical Officer Kevin Scott in a company blog post about the news.