This article is part of our ongoing coverage of the fight against coronavirus. The past few months have taught us an important lesson: We're bad at handling highly contagious diseases. The Earth's growing population and the ease with which we can travel long distances have contributed to the fast spread of the novel coronavirus to more than 200 countries. For the moment, the main question is, how do we stop the spread of the virus? For states, the choice is between health and economy.

People have asked me about how Artificial Intelligence (AI) is being used in the fight against COVID-19. The answer is that it is being used in myriad of ways! In this blog, I've discussed five innovative AI projects being used to help stop this global pandemic and save lives. 1 - Arguably the most discussed and used dashboard is the "COVID-19 Dashboard by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University". You have likely seen it on television press conferences and it was recently featured on NPR. Developed by Ensheng Dong, Hongru Du, and Lauren Gardner at Johns Hopkins University, it provides stunning visuals of real-time data such as "Cumulative Confirmed Cases", "Active Cases", and "Testing Rate", just to name a few.

The days of clicking on traffic lights to prove you are not a robot could be ending after Google's decision to charge for the tool prompted one of the web's biggest infrastructure firms to ditch it for a competitor. "Captcha" – an awkward acronym for "completely automated public Turing test to tell computers and humans apart" – is used by sites to fight automated abuses of their services. For years, Google's version of the test, branded reCaptcha, has dominated, after it acquired the company that developed it in 2009 and offered the technology for free worldwide. Google's introduction of charges for the service has prompted Cloudflare, a little-known firm that protects around 12% of the internet from bot attacks, to seek an alternative. The company's founder and chief executive, Matthew Prince, said: "It would have added millions of dollars in annual costs just to continue to use reCaptcha for our free users. That was finally enough of an impetus for us to look for a better alternative."

Officials are turning to'talking' drones to keep citizens safe amid the coronavirus outbreak. Get all the latest news on coronavirus and more delivered daily to your inbox. DAYTONA BEACH, Fla. -- Kim Andrade was just walking along Daytona beach when a drone came buzzing by. It caught her attention, and she even went ahead and snapped a few photos. What she did not expect to learn, however, is that the drone has a voice.

Artificial Intelligence is moving at the speed of light, with multiple companies creating software, products and services in not just a vertical way – more of a horizontal disruption. Form Healthcare to Security, from Real Estate to Telecom, here is a look into 28 companies powering the disruption with AI – 1st Edition. Sherpa.ai was founded in 2012 after deep research into Artificial Intelligence, with the conviction of creating a personal assistant that would be not just useful, but indispensable for users. In order to do this, Sherpa brought together a team of experts in Artificial Intelligence who, coupled with a fantastic design, have been able to create the next generation of Digital Assistants which will help users make their life not just more exciting, but also more enjoyable. WellSaid Labs has developed state of the art text-to-speech technology that creates life-like synthetic voice, from the voices of real people.

The novel coronavirus pandemic is certainly not good for the labor market. Recent weeks have seen unemployment claims surge to record levels as businesses and entire industries shutter in order to stop the spread of the Covid-19. As a result, the economy has plummeted, with the Dow Jones Industrial Average and S&P 500 down more than 20 percent from their February highs. While social distancing measures may be temporary, this economic downturn's effect on the labor market will have long-lasting effects. In a joint post with his colleagues, Mark Muro, a senior fellow and policy director at the Brookings Institution's Metropolitan Policy Program, recently wrote, "any coronavirus-related recession is likely to bring about a spike in labor-replacing automation."

Countries in the Gulf Cooperation Council are stepping up their use of artificial intelligence tools to halt the spread of the coronavirus pandemic. Governments throughout the GCC -- a group of countries in the Middle East that includes Bahrain, Saudi Arabia, Qatar, Oman, Kuwait and the United Arab Emirates -- have enacted some of world's strictest measures, including suspending passenger flights and imposing curfews on citizens to put brakes on the number of new cases of Covid-19 that currently total over 2 million (2,064,115) globally, according to Johns Hopkins University data. But countries aren't restricting their efforts to simply imploring their residents to stay locked in and shutting down all but the most essential of businesses. They are increasingly deploying sophisticated technology to ensure that movement is limited and social distancing is in place through the use of speed cameras, drones and robots. By applying location-based contact tracing, governments can monitor those who have tested positive for coronavirus, and try to limit their exposure to the population.

High quality labeled datasets remain one of the biggest obstacles for the mainstream adoption of machine learning technologies. While we are seeing unprecedented advancements in machine learning research and technology, many of those methods can't be widely adopted due to limitations in the creation of training datasets. That hurtle has propelled research in alternative methods such as semi-supervised and self-supervised learning which are able to operate by pretraining with unlabeled datasets. In the language analysis front, we have seen remarkable achievements of these type of techniques with models such as Google BERT or Microsoft Turin-NLG breaking records in performance and efficiency. Other deep learning domains remain behind in the adoption of semi-supervised and self-supervised models.

One of the most transformational technologies of our age is artificial intelligence (AI). Security risks and pertinent questions should be foreseen and elucidated before the technology starts to conquer the world. That is why AI security-related consideration is of paramount importance. Once a new innovation emerges, people become concerned about security issues -- sometimes too late. Take a look at the advancement of different technologies, beginning with networks, which began to develop in the 1980s. The growth of network security solutions proceeded in the 1990s.

Businesses around the world are looking for innovation with the rising competition. To thrive in such an environment businesses are looking for technological solutions that can help them overcome challenges and constantly help in building new strategies. In recent years, artificial intelligence and machine learning technologies have been receiving a fair amount of attention from the business. One of the earliest forms of AI used for business applications are chatbots. In the year 2018, only the world's bigger economies reported their own AI initiatives.