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Archive for the ‘robotics/AI’ category: Page 1020

Oct 22, 2022

How retail AI is helping sellers keep up this holiday shopping season (and beyond)

Posted by in category: robotics/AI

Register now for your free virtual pass to the Low-Code/No-Code Summit this November 9. Hear from executives from Service Now, Credit Karma, Stitch Fix, Appian, and more. Learn more.

Retail AI is everywhere this holiday season — even if you don’t realize it.

Say you’re a fashion retailer. You’ve always had to try to predict trends — but now with a slowed supply chain, you have to look 12 months out instead of six.

Oct 22, 2022

Machine Learning’s New Math

Posted by in categories: mathematics, robotics/AI

“We got a thousand times improvement [in training performance per chip] over the last 10 years, and a lot of it has been due to number representation,” Bill Dally, chief scientist and senior vice president of research at Nvidia said at the recent IEEE Symposium on Computer Arithmetic.

Oct 22, 2022

Fake News Detection with Model Selection and Hyperparameter Optimization in Python

Posted by in category: robotics/AI

Originally published on Towards AI the World’s Leading AI and Technology News and Media Company. If you are building an AI-related product or service, we invite you to consider becoming an AI sponsor. At Towards AI, we help scale AI and technology startups. Let us help you unleash your technology to the masses.

Oct 21, 2022

How drones could determine the direction of gravity without accelerometers

Posted by in categories: drones, robotics/AI

For proper operation, drones usually use accelerometers to determine the direction of gravity. In a new study published in Nature on October 19, 2022, a team of scientists from Delft University of Technology, the CNRS and Aix-Marseille University has shown that drones can estimate the direction of gravity by combining visual detection of movement with a model of how they move. These results may explain how flying insects determine the direction of gravity and are a major step toward the creation of tiny autonomous drones.

While drones typically use accelerometers to estimate the direction of , the way flying achieve this has been shrouded in mystery until now, as they have no specific sense of acceleration. In this study, a European team of scientists led by the Delft University of Technology in the Netherlands and involving a CNRS researcher has shown that drones can assess gravity using visual motion detection and motion modeling together.

Continue reading “How drones could determine the direction of gravity without accelerometers” »

Oct 21, 2022

Robotics researchers turn the public’s ideas into ‘robo-fish’ reality

Posted by in category: robotics/AI

A robot fish that filters microplastics has been brought to life after it won the University of Surrey’s public competition—The Natural Robotics Contest.

The robot fish design, which was designed by a student named Eleanor Mackintosh, was selected by an international panel of judges because it could be part of a solution to minimize plastic pollution in our waterways.

Continue reading “Robotics researchers turn the public’s ideas into ‘robo-fish’ reality” »

Oct 21, 2022

Japan starts operations with SeaGuardian drone, receives two Hawkeyes

Posted by in categories: drones, law enforcement, robotics/AI

MELBOURNE, Australia — The Japanese Coast Guard has started operations with a newly delivered MQ-9B SeaGuardian drone, while more airborne early warning aircraft have arrived in the country by ship.

The UAV’s manufacturer, General Atomics Aeronautical Systems, said in a news release that the Coast Guard commenced flight operations with a SeaGuardian from the Japan Maritime Self-Defense Force Air Station Hachinohe on Oct. 19.

The American company said the high-altitude, long-endurance unmanned aircraft “will primarily perform Maritime Wide Area Search (MWAS) over the Sea of Japan and the Pacific Ocean. Other missions will include search and rescue, disaster response, and maritime law enforcement.”

Oct 21, 2022

Will Machines Replace Human Creativity?

Posted by in category: robotics/AI

Prof. Aleks Farseev is an entrepreneur, research professor, keynote speaker, and the CEO of SoMin.ai, a long-tail ad optimization platform.

Not too long ago, I was asked to present a tool to some of my clients. It was a simple prototype, where a person would type in a few things (i.e., advertising channel, product and occasion), and in turn, the machine would give a number of sample ads. When I clicked the button, in just a few seconds, the machine spat out several ads complete with images and text. The first comment was, “Wow, that was really fast.” What would take a person a few hours to do, this machine did in but a fraction. There were a lot of other interesting comments, some even pointing out that this machine was really creative. Then one person spoke out, a comment that put the room into an uncomfortable silence, “This thing is going to take my job.”

We are in a time of uncertainty. As AI applications become more visible and popular, many will start wondering how they will impact our society. There are the “doomsayers” who think AI will take over the world. Then there are the more “sane” people who think that AI will never be able to replicate humans. After all, how can a machine copy something so intricate and complex? But then again, day by day, the advancements in AI continue to surprise us, as if to challenge our very humanity.

Oct 21, 2022

Dr. Ezinne Uzo-Okoro, Ph.D. — Space Policy — Office of Science & Technology Policy, White House

Posted by in categories: food, physics, policy, robotics/AI, satellites, science, space

Advancing Space For Humanity — Dr. Ezinne Uzo-Okoro, Ph.D. — Assistant Director for Space Policy, Office of Science and Technology Policy, The White House.


Dr. Ezinne Uzo-Okoro, Ph.D. is Assistant Director for Space Policy, Office of Science and Technology Policy, at the White House (https://www.whitehouse.gov/ostp/) where she focuses on determining civil and commercial space priorities for the President’s science advisor, and her portfolio includes a wide range of disciplines including Orbital Debris, On-orbit Servicing, Assembly, and Manufacturing (OSAM), Earth Observations, Space Weather, and Planetary Protection.

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Oct 20, 2022

Reprogrammable materials selectively self-assemble

Posted by in categories: materials, robotics/AI

While automated manufacturing is ubiquitous today, it was once a nascent field birthed by inventors such as Oliver Evans, who is credited with creating the first fully automated industrial process, in flour mill he built and gradually automated in the late 1700s. The processes for creating automated structures or machines are still very top-down, requiring humans, factories, or robots to do the assembling and making.

However, the way nature does assembly is ubiquitously bottom-up; animals and plants are self-assembled at a cellular level, relying on proteins to self-fold into target geometries that encode all the different functions that keep us ticking. For a more bio-inspired, bottom-up approach to assembly, then, human-architected materials need to do better on their own. Making them scalable, selective, and reprogrammable in a way that could mimic nature’s versatility means some teething problems, though.

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Oct 20, 2022

Deep learning with light: Components of machine learning model encoded onto light waves

Posted by in category: robotics/AI

Ask a smart home device for the weather forecast, and it takes several seconds for the device to respond. One reason this latency occurs is because connected devices don’t have enough memory or power to store and run the enormous machine-learning models needed for the device to understand what a user is asking of it. The model is stored in a data center that may be hundreds of miles away, where the answer is computed and sent to the device.

MIT researchers have created a new method for computing directly on these devices, which drastically reduces this latency. Their technique shifts the memory-intensive steps of running a machine-learning model to a central server where components of the model are encoded onto light waves.

The waves are transmitted to a connected device using , which enables tons of data to be sent lightning-fast through a network. The receiver then employs a simple optical device that rapidly performs computations using the parts of a model carried by those light waves.