That's the cat using a litter box," Dunlap explains. That's where Dunlap works and parties. He dials into weekly happy hours at Blumont, an international humanitarian group where Dunlap is director of business development. In recent weeks, dirty piles of laundry, pets chasing balls, curious babies and automated Roomba vacuum cleaners have all made cameos during video happy hour. "We had another colleague who showed us her vegetable garden; she's probably best situated, as a prepper," Dunlap says.

ZOE and King's College data science and machine learning teams have been working around the clock to create a machine learning model that uses Symptom Tracker data to predict COVID-19 in the UK. Based on data from the COVID Symptom Tracker app and the assumptions that we lay out below, we estimate that there are a total of 1.9m people in the UK with symptomatic COVID (aged 20-69 only) as of 1st April 2020. Jonathan Wolf, CEO of ZOE explains the model in our webinar below. You can find a daily feed of maps here. We used machine learning* on this data to learn which symptoms are most predictive of a positive test.

When DeepMind, the artificial intelligence company owned by Google parent Alphabet Inc., released its predictions about some of the building blocks of the virus that causes Covid-19 in early March, it gave medical researchers a small but potentially important clue that could help them develop a vaccine and treatments for the respiratory illness. The company's deep learning system, AlphaFold, which predicts the shapes of proteins when no similar structures are available, is just one example of the powerful role AI is playing in the fight against the novel coronavirus. The innovations that DeepMind and others are rapidly rolling out could be complicated by AI laws to be unveiled by the European Union this year. Even as the coronavirus upends business, economic, and legislative plans the world over, the EU is pushing ahead with its AI policy proposal, which would make it a global leader in regulating the sector. The European Commission, the bloc's executive body, released its plan in February, calling for public feedback by the end of May.

Throughout history, epidemics and chronic diseases have claimed the lives of many people and caused major crises that have taken a long time to overcome. The 2019 novel coronavirus (COVID-19) pandemic appeared in Wuhan, China in December 2019 and has become a serious public health problem worldwide. It is an acute resolved disease, but it can also be deadly, with a 2% case fatality rate. The early and automatic diagnosis of Covid-19 may be beneficial for timely referral of the patient to quarantine, and monitoring of the spread of the disease. Some tests requiring significant time to produce results (days), and a projected up to 30% false positive rate, other timely approaches to diagnosis are worthy of investigation.

Earth Observation data is valuable for journalist's reports to the public. An example are the maps released in little time during or after the tsunami in Indian Ocean in 2004 or the Fukushima disaster in 2011, accompanying the verbal or text reports of theirs. Taking advantage of the improved temporal frequency and spatial cover of the Sentinel satellite sensors SnapEarth aims to assimilate latest spaceborne retrieved information to support journalists in their work in near real time. In this context, a dedicated services' module aims to leverage on Copernicus monitoring services, like the EMS's (Emergency Management Service) EFAS (European Flood Awareness System) and EFFIS (European Forest Fire Information System). It will add in tandem to them the ability to exploit latest AI (Artificial Intelligence) techniques to automatically and unsupervised query through big data piles to deliver in minimum time required products.

The fully programmable Nao robot has been used to experiment with machine ethics. In his 1942 short story'Runaround', science-fiction writer Isaac Asimov introduced the Three Laws of Robotics -- engineering safeguards and built-in ethical principles that he would go on to use in dozens of stories and novels. They were: 1) A robot may not injure a human being or, through inaction, allow a human being to come to harm; 2) A robot must obey the orders given it by human beings, except where such orders would conflict with the First Law; and 3) A robot must protect its own existence as long as such protection does not conflict with the First or Second Laws. Fittingly, 'Runaround' is set in 2015. Real-life roboticists are citing Asimov's laws a lot these days: their creations are becoming autonomous enough to need that kind of guidance.

It's too early to quantify the economic impact of the global COVID-19 pandemic, but because of this outbreak compounded with the U.S.-China trade war, global supply chains and businesses linked to the world's second-biggest economy are being impacted. As I sit here in Singapore and monitoring the spread of the outbreak in Asia and beyond, the mounting human cost is also especially of deep concern to me. But even amid adversity comes the opportunity for innovation and invention. Chinese tech companies Alibaba, Tencent and Baidu have opened their artificial intelligence (AI) and cloud computing technologies to researchers to quicken the development of virus drugs and vaccines. U.S.-based medical startups are using AI to rapidly identify thousands of new molecules that could be turned into potential cures.

Nadella's quotes have been lightly edited for clarity. "We have to get the basics right. Let's as a nation really make sure that broadband connectivity is distributed evenly. Let's just make sure that the basics of education and healthcare are available. Then you can have the ingenuity of our system, where there's entrepreneurial energy that's more evenly distributed. What people like Steve Case (ex-AOL CEO and rural-startup investor) and others are doing to bring new sources of risk capital to those markets can be tapped into because there are people with skills and a dream, they can go on to create new jobs. They can revolutionize quote-unquote traditional industries."

Demand for artificial intelligence specialists grew 74% over the last five years. Artificial intelligence experts are in luck in 2020. LinkedIn released its list of the top emerging jobs for 2020. These jobs have grown substantially in the last five years, and LinkedIn predicts they will continue to increase demand in the new year. Demand for artificial intelligence specialists grew 74% over the last five years.

Continuing our series on artificial intelligence, AI can augment human work--if workers' representatives have a voice in implementing it. The discourse on artificial intelligence and work is shaped by conflicting narratives. Disempowering notions about mass unemployment and a loss of human control in the face of ever-more-powerful machines are widespread. But AI also inspires visions of human empowerment, according to which labour will be upgraded as machines support human effort and relieve us from the burden of onerous work, leaving us with more interesting, creative and cognitive tasks. Both narratives are one-sided, deriving projections as to the future of work from the nature of technology as such.