Change is hard, and, in some cases, it can be downright scary. Technology is driving a lot of change in the 21st century, and it's possible that the biggest, most "intimidating" changes are yet to come. For instance, robotics, AI (artificial intelligence), and automation are huge, important technology trends that are taking the world by storm. Artificially intelligent systems and machines are automating tasks that used to be reserved for humans, and this will affect the future of work in both expected and unforeseen ways. Similarly, AVs (autonomous vehicles) will create incredible changes in society--some predictable and some unpredictable--and for some people, a sense of fear accompanies these changes.

AI is helping companies coordinate their workflows to achieve great efficiency and more synchronization. This article is part of an MIT SMR initiative exploring how technology is reshaping the practice of management. Anyone who has ever worked for a large organization knows that information silos are a challenging fact of life. They're evident internally: The left hand doesn't always know what the right hand is doing, and employees who are supposed to be working in concert are out of sync. Companies that are in business together often don't have full information or a clear picture of their partnership.

If you thought that heart disease or cancer might be the leading causes of death in England and Wales, you'd be wrong. Dementia has become the leading cause of death and accounted for 12.8% of all deaths in the UK in 2018. It is the biggest health crisis in the UK and has huge financial implications: NHS England and Dementia UK have estimated that the cost associated with the disease is a staggering £23bn per year1. Dementia is an umbrella term used to describe symptoms that occur when the brain cells stop working. This happens when cells die or blood flow in the brain is restricted.

In the year that Stanley Kubrick's film 2001: A Space Odyssey turns 50, you could be forgiven for asking where is the space-age future we were promised? Many still choose to travel to meetings in favour of using videophones and we don't have a permanent colony on the Moon, let alone Jupiter. Teleconferencing technology is improving though as just a few weeks ago Canadian researchers unveiled the TeleHuman 2, a 3D holographic projection system that smacks of the Star Trek holodeck. The system is based on a ring of intelligent projectors mounted above and around a reflective, human-sized cylindrical pod. The display projects a light field composed of many images, one for every degree of angle, so users need not wear a headset or 3D glasses to see each other.

A team of scientists led by researchers at the University of Georgia Center for Food Safety in Griffin has developed a machine-learning approach that could lead to quicker identification of the animal source of certain Salmonella outbreaks. In the research, published in the January 2019 issue of Emerging Infectious Diseases, Xiangyu Deng and his colleagues used more than a thousand genomes to predict the animal sources, especially livestock, of Salmonella Typhimurium. Deng, an assistant professor of food microbiology at the center, and Shaokang Zhang, a postdoctoral associate with the center, led the project, which also included experts from the Centers for Disease Control and Prevention, the U.S. Food and Drug Administration, the Minnesota Department of Health and the Translational Genomics Research Institute. According to the Foodborne Disease Outbreak Surveillance System, close to 3,000 outbreaks of foodborne illness were reported in the U.S. from 2009 to 2015. Of those, 900 -- or 30 percent -- were caused by different serotypes of Salmonella, including Typhimurium, Deng said.

Agbiotech newcomer Inari has raised $89 million to pursue an ambitious goal: to challenge the status quo in agriculture. Plants edited with the new genome editing tools will incorporate useful traits and will not be classed as GMOs.Credit: reHAWKEYE / Alamy Stock Photo Inari is one of a several small companies with similarly lofty goals who are capitalizing on new editing technologies, such as CRISPR, and computational methods for predictive modeling. Such tools make crop development faster and less expensive, and potentially could give startups a shot at competing with the big players by sidestepping onerous and expensive regulatory oversight. Just a few years ago, a seed developer could plan on spending a decade and up to $100 million on bringing one new crop trait to market (Nat. That's not only because the old tools for altering the genetics of these crops, such as Agrobacterium-mediated transformation, were slower, more expensive and more unpredictable than CRISPR, but also because of regulations, both in the United States and especially in Europe.

Scientists from the University of Oxford, in collaboration with University of Basel and Lancaster University, have developed an algorithm that can be used to measure quantum dots automatically. The electron spin of individual electrons in quantum dots could serve as the smallest information unit of a quantum computer. Writing in npj Quantum Information, the scientists describe how they can massively speed up this hugely time-consuming process with the help of machine learning. Their approach to the automatic measurement and control of qubits represents a key step toward their large-scale application. Dr. Natalia Ares from the University of Oxford's Department of Materials, said: 'For the first time, we've applied machine learning to perform efficient measurements in gallium arsenide quantum dots, thereby allowing for the characterization of large arrays of quantum devices.'

Scientist Suzanne Gildert's dream is to create robots that are indistinguishable from humans. She's already taken the first steps towards achieving it. After completing her PhD in quantum physics, Gildert took a job at Burnaby's D-Wave Systems, one of the world's premier quantum-computing companies. Much of her work was in machine learning and AI--a field that spurred her long-standing fascination with untangling the mysteries of the human mind. Four years later, Gildert--who had spent much of her free time building her own robots--decided to try something previously relegated to the pages of science fiction.

A technician took X-rays of Gura's chest but couldn't make heads or tails of the resulting images. "We had to wait a few days for the radiologist to come from the big city to diagnose what I had," delaying his treatment, Gura says. "I asked: How come we don't have a centralized reference database of all the X-rays for people like me so that I can just run a computer vision comparison against it and get my own sense of what's going on in my body? That was the seed of the idea." The idea became Zebra Medical Vision, which transforms vast amounts of medical imaging data into actionable insights, allowing doctors to better detect diseases, tumors and fractures while giving patients more information about their health.

With the number of cameras drastically increasing in our world, facial recognition is rapidly taking flight. Facial recognition is a biometric faceprint, where artificial intelligence maps an individual's face mathematically. This faceprint is then stored in data. Later, the stored data can be compared with a live or digital image using deep learning to verify someone's identity. Facial recognition can be integrated anywhere there is a camera. As a result, the number of applications for facial recognition is growing rapidly, from security to retail and consumer electronics to government services.