Lifeboat Foundation

Artificial intelligence can create jobs, too. How else do we manage the robots?

Engineering and construction is behind the curve in implementing artificial intelligence solutions. Based on extensive research, we survey applications and algorithms to help bridge the technology gap.

The engineering and construction (E&C) sector is worth more than $10 trillion a year. And while its customers are increasingly sophisticated, it remains severely underdigitized. To lay out the landscape of technology, we conducted a comprehensive study of current and potential use cases in every stage of E&C, from design to preconstruction to construction to operations and asset management. Our research revealed a growing focus on technological solutions that incorporate artificial intelligence (AI)-powered algorithms. These emerging technologies focus on helping players overcome some of the E&C industry’s greatest challenges, including cost and schedule overruns and safety concerns.

Neural networks have started to take off since AlexNet in 2012. We don’t have to call it a software war, but there’s a competition for mindshare and community contributors in neural networks.

Of course, AI needs more than a neural network library, it needs the configuration hyperparameters, training datasets, trained models, test environments, and more.

Most people have heard of Google’s Tensorflow which was released at the end of 2015, but there’s an active codebase called PyTorch which is easier to understand, less of a black box, and more dynamic. Tensorflow does have solutions for some of those limitations (such as Tensorflow-fold, and Tensorflow-Eager) but these new capabilities remove the need for other features and complexity of Tensorflow. Google built a high-performance system for doing static computation graphs before realizing that most people want dynamic graphs. Doh!

Continue reading “PyTorch Should Be Copyleft” »

Nanobots could provide cancer treatment free from side effects.

The Robots are Coming!

After taking over deliveries for 20 percent of rural Rwanda’s blood supply, Zipline is introducing its drone fleet to the rural United States.

Continue reading “Zipline’s Bigger, Faster Drones Will Deliver Blood in the United States This Year” »

New developments require new materials. Until recently, these have been developed mostly by tedious experiments in the laboratory. Researchers at the Fraunhofer Institute for Algorithms and Scientific Computing SCAI in Sankt Augustin are now significantly shortening this time-consuming and cost-intensive process with their “Virtual Material Design” approach and the specially developed Tremolo-X software. By combining multi-scale models, data analysis and machine learning, it is possible to develop improved materials much more quickly. At the Hanover Trade Fair from April 23 to 27, 2018, Fraunhofer will be demonstrating how the virtual material design of the future looks.

In almost every industry, new materials are needed for new developments. Let’s take the automotive industry: while an automobile used to consist of just a handful of materials, modern cars are assembled from thousands of different materials – and demand is increasing. Whether it’s making a car lighter, getting better fuel economy or developing electric motor batteries, every new development requires finding or developing the material that has exactly the right properties. The search for the right material has often been like a guessing game, though. The candidates have usually been selected from huge material databases and then tested. Although these databases provide insight into specific performance characteristics, they usually do not go far enough into depth to allow meaningful judgments about whether a material has exactly the desired properties. To find that out, numerous laboratory tests have to be performed.

It’s small enough to fit inside a shoebox, yet this robot on four wheels has a big mission: keeping factories and other large facilities safe from hackers.

Meet the HoneyBot.

Continue reading “Robot designed to defend factories against cyberthreats” »

I might bump my post for an armed low flying mini UAV. Seeing as this what they are tip toeing around now.

The focus of this swarm sprint is on enabling improved swarm autonomy through enhancements of swarm platforms and/or autonomy elements, with the operational backdrop of utilizing a diverse swarm of 50 air and ground robots to isolate an urban objective within an area of two square city blocks over a mission duration of 15 to 30 minutes. Swarm Sprinters will leverage existing or develop new hardware components, swarm algorithms, and/or swarm primitives to enable novel capabilities that specifically showcase the advantages of a swarm when leveraging and operating in complex urban environments.

Continue reading “Defense Advanced Research Projects Agency” »

Chinese AI-powered robot Xiaoyi took the country’s medical licensing examinations and passed.