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Imagine this: You're walking in San Francisco, California, USA, when you spot an out-of-control trolley car headed toward a group of five people working on the track. You yell for them to get out of the way, but they don't hear or see you. You're standing next to a switch, which would send the trolley on a different track. But there's one worker on the alternate track who, like the five other workers, doesn't hear you or see the trolley. You have a choice: Do you flip the switch?

Another popular face-swapping app is generating backlash after many users called attention to potential privacy concerns. The app, Zao, recently skyrocketed to the top of China's iOS app store by offering users the chance to insert their faces into film and TV by simply uploading a series of pictures. Despite its popularity, patrons quickly turned on Zao due to a strongly-worded user agreement that gave'free, irrevocable, permanent, transferable and relicense-able' rights over use of its their content, reports Bloomberg. The company has since rolled back those terms, but many have voiced their outrage with the idea that their content was now owned by the company -- a relatively unknown entity. The deepfake app, Zao, was download widely across China over the weekend, but quickly became the center of controversy when users found out that it was claiming to own pictures uploaded to its platform.

According to a release issued earlier this month by the Los Alamos National Laboratory (LANL), researchers have developed a machine learning approach called transfer learning that lets them model novel materials by learning from data collected about millions of other compounds. The new approach can be applied to new molecules in milliseconds, enabling research into a far greater number of compounds over much longer timescales. The new technique, called ANI-1ccx potential, promises to advance the capabilities of researchers in many fields and improve the accuracy of machine learning-based potentials in future studies of metal alloys and detonation physics. "Our quantum mechanical calculations to create ANI-1ccx potential were conducted over two years with time split on the Comet supercomputer at the San Diego Supercomputer Center and the Badger supercomputer at LANL," said Olexandr Isayev, paper author and a pharmacy professor at the University of North Carolina at Chapel Hill. "We chose these two supercomputers to train our neural networks as there are few machines that can run these – due to the high memory and core requirements."

You've got them written up on the wall, on your mousepad, emblazoned across your screen or maybe even in your reception. They are, of course, your brand values, and they provide the basis for your marketing efforts – hence their importance. Brand values and personality define what your brand stands for and the response you want it to evoke. Communications from your brand might not always convey the intended personality or be consistent across even a small selection of brand touchpoints. We're often asked to test communications and assess brand perceptions, addressing things like their relevance, distinctiveness, alignment and consistency across different touchpoints like websites, promotions, ads, products and services.

Let's think differently and use IoT to solve local problems says Jack Ngaare, MD of Microsoft Africa Development Center, Kenya site. He was sharing insights on Artificial Intelligence(AI) and Internet of Things(IoT) during keynote address at the third East Africa IoT and AI Summit. Speaking to delegates at the conference he emphasized the need to focus on the problems Africa has and be more deliberate about solving these problems using such emerging technologies. Let's think differently and use IoT to solve local[Africa] problems He asked "What problems do we have? What are the focus areas and what are the simple solutions?

Reinforcement learning and deep learning arose as separate disciplines within AI, but researchers are increasingly finding that pairing the two can deliver promising applications. Deep learning has excelled at tasks like training classifiers for image and speech recognition. Reinforcement learning techniques have excelled at creating AI systems that improve through trial and error to produce game-playing bots and recommendation engines. At the Re•Work Deep Reinforcement Learning Summit in San Francisco, researchers explored how the two approaches are being combined to craft more automated and optimized reinforcement learning algorithms. "In the last six years, we've been really focusing on getting this combination of deep networks and reinforcement learning to be more stable, more reliable, more predictable," said Marc Bellemare, research scientist at Google Brain, in an interview.

Peggy digs into how AI (artificial intelligence) is changing the nature of work, saying that it will yield high economic benefits for the United States. She also highlights a new plan from NIST that identifies how the government needs to bolster AI standards. However, while it is a solid plan, she cautions that we need to make sure that we are creating AI standards that are flexible enough and to not forget that AI is only as good as the algorithms built by people.

"As you ramble through Life, Brother, Whatever be your goal. Keep your eye upon the doughnut, And not upon the hole." Advice for those who drink coffee and eat "sinkers." Artificial Intelligence is not new. Another thing that is not new is people over-promising and under-delivering results around AI.

Facial recognition technology will not be deployed at the King's Cross development in the future, following a backlash prompted by the site owner's admission last month that the software had been used in its CCTV systems. The developer behind the prestigious central London site said the surveillance software had been used between May 2016 and March 2018 in two cameras on a busy pedestrian street running through its heart. It said it had abandoned plans for a wider deployment across the 67-acre, 50-building site and had "no plans to reintroduce any form of facial recognition technology at the King's Cross Estate". The site became embroiled in the debate about the ethics of facial recognition three weeks ago after releasing a short statement saying its cameras "use a number of detection and tracking methods, including facial recognition". That made it one of the first landowners to acknowledge it was deploying the software, described by human rights groups as authoritarian, partly because it captures and analyses images of people without their consent.