Optical components play a key role in the optimal performance of today's cobots, allowing them to see and respond to their environment in real-time and ensuring that they operate safely and effectively. As we reflect on history, we can observe numerous systems with resemblances to robots. In fact, some concepts of robotics and artificial intelligence (AI) are speculated to date back to ancient times. The resourceful Ancient Greeks, for instance, created sophisticated automated puppet theatres1, while the Ancient Egyptians devised ingenious mechanical operating systems embodied in figurines2. Fast-forwarding to the present era, significant progress has been made since the days of Ancient Greece and Egypt.

What do you think of when you hear the word automation? None of this is wrong, per se, but we like to add another word when we think about automation: productive. For us, automation is all about giving humans superhero capes. We think about it as a way for productive automated work technologies to amplify humanness and economic productivity. Or, instead of focusing on how automation replaces humans, honing in on how it can improve our work.

While our facial expressions play a huge role in building trust, most robots still sport the blank and static visage of a professional poker player. With the increasing use of robots in locations where robots and humans need to work closely together, from nursing homes to warehouses and factories, the need for a more responsive, facially realistic robot is growing more urgent. Long interested in the interactions between robots and humans, researchers in the Creative Machines Lab at Columbia Engineering have been working for five years to create EVA, a new autonomous robot with a soft and expressive face that responds to match the expressions of nearby humans. The research will be presented at the ICRA conference on May 30, 2021, and the robot blueprints are open-sourced on Hardware-X (April 2021). "The idea for EVA took shape a few years ago, when my students and I began to notice that the robots in our lab were staring back at us through plastic, googly eyes," said Hod Lipson, James and Sally Scapa Professor of Innovation (Mechanical Engineering) and director of the Creative Machines Lab. Lipson observed a similar trend in the grocery store, where he encountered restocking robots wearing name badges, and in one case, decked out in a cozy, hand-knit cap.

A new book co-authored by MIT engineers Julie Shah and Laura Major SM '05 explores a future populated with robot helpers. Book co-authored by MIT Associate Professor Julie Shah and Laura Major SM '05 explores a future populated with robot helpers. As Covid-19 has made it necessary for people to keep their distance from each other, robots are stepping in to fill essential roles, such as sanitizing warehouses and hospitals, ferrying test samples to laboratories, and serving as telemedicine avatars. There are signs that people may be increasingly receptive to robotic help, preferring, at least hypothetically, to be picked up by a self-driving taxi or have their food delivered via robot, to reduce their risk of catching the virus. As more intelligent, independent machines make their way into the public sphere, engineers Julie Shah and Laura Major are urging designers to rethink not just how robots fit in with society, but also how society can change to accommodate these new, "working" robots.

Energy Star was launched in 1992 by the US Environmental Protection Agency as a voluntary labelling programme recognising the value of energy-efficiency in a broad range of computer-related products, from personal computers to air-conditioning systems. The programme's major success was the widespread adoption of the energy-saving "sleep mode" in consumer electronic devices. Energy Star's innovative breakthrough represents an important platform from which today's concept of computational sustainability was launched. Computational sustainability is defined as a field of interdisciplinary research that attempts to optimise societal, economic and environmental resources using advanced decision-making algorithms supported by the ever-increasing processing power of today's evolving computer systems. Computational sustainability's key goals include the development of computational models, methods and tools to assist in the management of the delicate balance between environmental, economic and societal needs. Advancements in AI and HCI have enabled combinations of robots and humans to carry out critical functions in the most hostile of environments.

I expected my summer engineering internship to include things like updating old 3-D models, creating part designs, and learning the ins and outs of how a company works. I didn't expect it to involve learning to make my colleagues obsolete. It was the summer after my sophomore year of college, at a company in Southern California. At the beginning of the internship, my manager asked me to implement 3-D printing to streamline a complicated mold-making process. I have long been obsessed with 3-D printing (I own two machines myself), so I was thrilled to introduce it into the business.

You don't need to have been victimized by the WannaCry ransomware--or worried about hack attacks on presidential elections--to understand that cybersecurity is the most pressing technology problem of our time and may soon become the biggest problem, period. Fending off the onslaught of attacks is a nearly insurmountable task for security professionals. But it's a perfect job for machines that can parse thousands of logs a second and identify potential threats a human might not even see. That's why artificial intelligence (AI) has become a key weapon in the fight against cyber crooks, rogue hackers, and aggressive nation states. But experts also warn that AI is not a magic fix.

For decades we've been told robots were to blame for the dearth of manufacturing jobs in the US, but that's about to change. Veo Robotics has a counter-intuitive vision for the future: If you improve the robots, manufacturers will be able to hire more people for better jobs. I am proud to share that Lux Capital is partnering with Patrick, Clara and Scott to help them achieve their mission to create more collaborative industrial robots. We, along with our partners at GV, are leading a $12 million Series A venture investment in Veo Robotics. As part of the investment, I will be joining the board of directors.

One perk of working for Melonee Wise's startup Fetch is that if your feet are tired you can glide around the office on the back of a squat wheeled robot. More usually, she and her roughly 50 employees keep themselves busy designing, building, and selling the machines to work in warehouses or factories across the globe. The San Jose company's machines are canny enough to work safely alongside people without requiring any changes to a facility--all they need is a map. Wise, one of MIT Technology Review's 2015 Innovators Under 35, built her first robot, Zippy, in college, out of plywood and scavenged computer parts. She spoke with San Francisco bureau chief Tom Simonite.

You don't need to have been victimized by the WannaCry ransomware--or worried about hack attacks on presidential elections--to understand that cybersecurity is the most pressing technology problem of our time and may soon become the biggest problem, period. Fending off the onslaught of attacks is a nearly insurmountable task for security professionals. But it's a perfect job for machines that can parse thousands of logs a second and identify potential threats a human might not even see. That's why artificial intelligence (AI) has become a key weapon in the fight against cyber crooks, rogue hackers, and aggressive nation states. But experts also warn that AI is not a magic fix.