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Category: robotics/AI – Page 1,682

Proteins are essential to cells, carrying out complex tasks and catalyzing chemical reactions. Scientists and engineers have long sought to harness this power by designing artificial proteins that can perform new tasks, like treat disease, capture carbon or harvest energy, but many of the processes designed to create such proteins are slow and complex, with a high failure rate.

In a breakthrough that could have implications across the healthcare, agriculture, and energy sectors, a team lead by researchers in the Pritzker School of Molecular Engineering at the University of Chicago has developed an artificial intelligence-led process that uses big data to design new proteins.

By developing machine-learning models that can review protein information culled from genome databases, the researchers found relatively simple design rules for building artificial proteins. When the team constructed these artificial proteins in the lab, they found that they performed chemical processes so well that they rivaled those found in nature.

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Unmanned Aerial Vehicles (UAV), commonly referred to as drones, may prove to be a valuable tool in the battle against pandemics like COVID-19. Researchers at the University of Calgary, the Southern Alberta Institute of Technology (SAIT), Alberta Health Services (AHS) and Alberta Precision Laboratories (APL) are partnering with the Stoney Nakoda Nations (SNN) to deliver medical equipment and test kits for COVID-19 to remote areas, and to connect these communities to laboratories more quickly using these remotely piloted aircraft.

Access for all

“We know that testing for COVID-19 is one of our most effective tools against its spread. Many remote communities in Canada do not have easy access to testing centres and medical supplies to support rapid testing and containment. Drones can help us respond to that need,” says Dr. John Conly, MD, medical director of the W21C Research and Innovation Centre at the Cumming School of Medicine (CSM) and co-principal investigator on the project.

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Before the century is out, advances in nanotechnology, nanomedicine, AI, and computation will result in the development of a “Human Brain/Cloud Interface” (B/CI), that connects neurons and synapses in the brain to vast cloud-computing networks in real time.

That’s the prediction of a large international team of neurosurgeons, roboticists, and nanotechnologists, writing in the journal Frontiers in Neuroscience.

A Human Brain/Cloud Interface, sometimes dubbed the “internet of thoughts”, theoretically links brains and cloud-based data storage through the intercession of nanobots positioned at strategically useful neuronal junctions.

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To test its experimental X-43A — an unmanned, single-use, scramjet-powered, hypersonic aircraft of which three were built — NASA piggybacked it on two other aircraft.

First was the Boeing B-52 Stratofortress, which carried under its wing the other two vehicles to an altitude at which they could be ‘drop-launched’.

Then there was the booster rocket, a modified version of a Pegasus rocket, which would accelerate the X-43A after the drop launch to a speed at which its scramjet engine could operate.

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The tiny house we’re going to discuss today won’t buy you freedom like trailer-based models, but it compensates for that with its own AI assistant. It’s smart, it’s tiny, it can be solar powered if you want, and it’s still very chic. It’s dubbed the next-generation tiny house: the Cube Two from Nestron.

You don’t have to actually live large in order to live large. Tiny houses are a good option when it comes to minimizing your footprint, downsizing costs and not sacrificing anything but space you probably wouldn’t be using either way.

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Scientists at Freie Universität Berlin develop a deep learning method to solve a fundamental problem in quantum chemistry.

A team of scientists at Freie Universität Berlin has developed an artificial intelligence (AI) method for calculating the ground state of the Schrödinger equation in quantum chemistry. The goal of quantum chemistry is to predict chemical and physical properties of molecules based solely on the arrangement of their atoms in space, avoiding the need for resource-intensive and time-consuming laboratory experiments. In principle, this can be achieved by solving the Schrödinger equation, but in practice this is extremely difficult.

Up to now, it has been impossible to find an exact solution for arbitrary molecules that can be efficiently computed. But the team at Freie Universität has developed a deep learning method that can achieve an unprecedented combination of accuracy and computational efficiency. AI has transformed many technological and scientific areas, from computer vision to materials science. “We believe that our approach may significantly impact the future of quantum chemistry,” says Professor Frank Noé, who led the team effort. The results were published in the reputed journal Nature Chemistry.

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