His Excellency Mattar Mohammed Al Tayer, Director-General, Chairman of the Board of Executive Directors of Roads and Transport Authority (RTA), revealed that RTA's precautionary measures and initiatives applied to the scheduling and the operation of public buses, marine transit means and taxis had accelerated the recovery from the Covid-19 pandemic. He stated that such measures contributed to restoring the growth of public transport ridership to 70% of the pre-Covid-19 levels. They also contributed to reducing the number of kilometres travelled by 18%, improving bus on-time arrival by 6%, and cutting carbon emissions by 34 metric tons. "In cooperation with Alibaba Cloud, RTA has recently started trialling the'City Brain' system to manage traffic in urban areas using artificial intelligence and advanced algorithms. The system analysis a massive number of big data received from nol cards, operating buses and taxis as well as the Enterprise Command and Control Centre. Then it converts the data into useful information that could be used in sending instant notifications and improving bus schedules and routes. The system is expected to improve the bus ridership by 17%, average waiting time by 10%, and the journey time and the average bus usage by 5%," stated Al Tayer.

This article would try to address the basic aspects of deep learning. Deep learning attempts to copy the working mechanism of the human brain by combining data inputs, weights, and biases. The basic mechanism of deep learning is to cluster data and make predictions with a high degree of accuracy. Deep learning involves layers that form a neural network. The layers help in improving accuracy and better prediction.

All the sessions from Transform 2021 are available on-demand now. Blueprint Software Systems has released a new solution for robotic process automation (RPA) migrations to the Microsoft Power Automate platform. This could tilt the balance in the RPA market toward Microsoft's lower-cost offerings with native integrations into popular productivity apps. Leading RPA companies, including UiPath, Automation Anywhere, and Blue Prism, have an extended lead time over Microsoft. These companies have developed a substantial base of loyal enterprise customers.

A group of researchers is using artificial intelligence techniques to calibrate some of NASA's images of the Sun, helping improve the data that scientists use for solar research. The new technique was published in the journal Astronomy & Astrophysics on April 13, 2021. A solar telescope has a tough job. Staring at the Sun takes a harsh toll, with a constant bombardment by a never-ending stream of solar particles and intense sunlight. Over time, the sensitive lenses and sensors of solar telescopes begin to degrade.

In the modern age of education, almost anyone with an internet connection can learn anything they want to. This is also true for learning AI, and now, anyone with the requisite background has the opportunity to learn AI and build AI programs. When I say "democratization," I mean the easy access to AI education and learning, and more importantly, the easy access to building scalable AI applications. In an article I wrote earlier this summer, I discussed my personal experience with AI ethics and how I paid little regard to the implications of my work. I have always heard that the democratization of any sort of learning is beneficial, which I generally agree with.

Commercial Aviation has great importance in the ... [ ] transport of organs for transplants in receiving patients. Studies show that commercial air carriers carry more than 9,000 organs a year on board airplanes with passengers. In the United States, an estimated 114,000 people were waiting for organ transplants, and only 30% of those got their organs on time in 2019. According to Kaiser Health News and Reveal from the Center of Investigative Reporting, nearly 170 organs could not be transplanted. Almost 370 endured near misses with delays of two hours or more because of transportation problems.

Clinicians and surgeons are increasingly using medical devices based on artificial intelligence. These AI devices, which rely on data-driven algorithms to inform health care decisions, presently aid in diagnosing cancers, heart conditions and diseases of the eye, with many more applications on the way. In a new study, Stanford faculty discuss sex, gender and race bias in medical technologies. Pulse oximeters, for example, are more likely to incorrectly report blood gas levels in dark-skinned individuals and in women. Given this surge in AI, two Stanford University faculty members are calling for efforts to ensure that this technology does not exacerbate existing heath care disparities.

In a perfect world, what you see is what you get. If this were the case, the job of Artificial Intelligence systems would be refreshingly straightforward. Take collision avoidance systems in self-driving cars. If visual input to on-board cameras could be trusted entirely, an AI system could directly map that input to an appropriate action--steer right, steer left, or continue straight--to avoid hitting a pedestrian that its cameras see in the road. But what if there's a glitch in the cameras that slightly shifts an image by a few pixels? If the car blindly trusted so-called'adversarial inputs,' it might take unnecessary and potentially dangerous action.

More technology companies want to get into the video game business. Just within the past week Netflix, Peloton, Zoom and Amazon have added games to their business plans. The potential promise of video games makes the medium attractive. The global video games market, estimated at $177.8 billion in 2020, is expected to surpass $200 billion by 2023, forecasts Tom Wijman at research firm Newzoo. But there's no guarantee these big names will succeed.

Self-driving features have been creeping into automobiles for years, and Tesla (TSLA) even calls its autonomous system "full self-driving." That's hype, not reality: There's still no car on the market that can drive itself under all conditions with no human input. But researchers are getting close, and automotive supplier Mobileye just announced it's deploying a fleet of self-driving prototypes in New York City, to test its technology against hostile drivers, unrepentant jaywalkers, double parkers, omnipresent construction and horse-drawn carriages. The company, a division of Intel (INTC), describes NYC as "one of the world's most challenging driving environments" and says the data from the trial will push full self-driving capability closer to prime time. In an interview, Mobileye CEO Amnon Shashua said fully autonomous cars could be in showrooms by the end of President Biden's first term.