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A material that mimics human skin in strength, stretchability and sensitivity could be used to collect biological data in real time. Electronic skin, or e-skin, may play an important role in next-generation prosthetics, personalized medicine, soft robotics and artificial intelligence.
“The ideal e-skin will mimic the many natural functions of human skin, such as sensing temperature and touch, accurately and in real time,” says KAUST postdoc Yichen Cai. However, making suitably flexible electronics that can perform such delicate tasks while also enduring the bumps and scrapes of everyday life is challenging, and each material involved must be carefully engineered.
Most e-skins are made by layering an active nanomaterial (the sensor) on a stretchy surface that attaches to human skin. However, the connection between these layers is often too weak, which reduces the durability and sensitivity of the material; alternatively, if it is too strong, flexibility becomes limited, making it more likely to crack and break the circuit.
Artificial intelligence is being applied to virtually every aspect of our work and recreational lives. From determining calculations for the construction of towering skyscrapers to designing and building cruise ships the size of football fields, AI is increasingly playing a key role in the most massive projects.
But sometimes, all we want to do is move a can of beans.
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They can check you in and deliver orange juice to your hotel room, answer your questions about a missing package, whip up sushi and pack up thousands of subscription boxes. And, perhaps most importantly, they are completely immune to Covid-19. While people have had a hard time in the coronavirus pandemic, robots are having a moment.
The Covid-19 pandemic has left millions of Americans unemployed – disproportionately those in the service industries where women and people of color make up the largest share of the labor force. In October, 11 million people were unemployed in the US, compared with about 6 million people who were without a job during the same time last year.
This time, from his home in Manchester, Daniel visits Michael in Sheffield Robotics lab in a Pepper robot. Hilarity ensues.
Over the past few decades, artificial intelligence (AI) tools have been used to analyze data or complete basic tasks in an increasing number of fields, ranging from computer science to manufacturing, medicine, physics, biology and even artistic disciplines. Researchers at University of Michigan have recently been investigating the use of artificial intelligence (AI) in architecture. Their most recent paper, published in the International Journal of Architectural Computing, specifically explores the potential of AI as a tool to create new architectural designs.
“My partner, Sandra Manninger, and myself, have a long-standing obsession with the idea to cross pollinate the fields of architecture and AI,” Matias del Campo, one of the researchers who carried out the study, told Tech Xplore. “We first got in touch with AI research in 1998, when we were introduced to the OFAI (The Austrian Institute of Artificial Intelligence) through a mutual friend, Dr. Arthur Flexer and we held the first course in Machine Learning for Architecture at the University of Applied Arts in Vienna, in 2006.”
Several years after they first became interested in the potential uses of AI in architecture, del Campo and Manninger started collaborating with the Robotics Department at University of Michigan. Working with Jessy Grizzle, the department’s director, and Alexandra Carlson, one of her Ph.D. students, they were able to significantly expand their research. Their study featured in the International Journal of Architectural Computing is the latest of a series of research efforts in which they investigated the use of AI techniques for designing architectural solutions.
Methylation definition at 5:05, 27:20 a lil about reprogramming, 32:00 q&a, 47:44 Aubrey chimes in, 57:00 Keith Comito(and other throughout)
Zoom transcription: https://otter.ai/u/AIIhn4i_p4DIXHAJx0ZaG0HUnAU
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AI, Genetics, and Health-Tech / Wearables — 21st Century Technologies For Healthy Companion Animals.
Ira Pastor ideaXme life sciences ambassador interviews Dr. Angela Hughes, the Global Scientific Advocacy Relations Senior Manager and Veterinary Geneticist at Mars Petcare.
Continue reading “Mars Personalised Petcare: High Tech, Genetics and Wearables” »
Computational molecular physics (CMP) aims to leverage the laws of physics to understand not just static structures but also the motions and actions of biomolecules. Applying CMP to proteins has required either simplifying the physical models or running simulations that are shorter than the time scale of the biological activity. Brini et al. reviewed advances that are moving CMP to time scales that match biological events such as protein folding, ligand unbinding, and some conformational changes. They also highlight the role of blind competitions in driving the field forward. New methods such as deep learning approaches are likely to make CMP an increasingly powerful tool in describing proteins in action.
Science, this issue p.
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