Combining AI and robotics technology, researchers have identified new cellular characteristics of Parkinson’s disease in skin cell samples from patients.
#ai #parkinsons #neuroscience #science #robotics
Summary: Combining AI and robotics technology, researchers have identified new cellular characteristics of Parkinson’s disease in skin cell samples from patients.
Source: New York Stem Cell Foundation
AI and neuroscience have too many similarities. While Artificial neural networks mimic the human brain, the human behaviour holds generous data for Artificial intelligence to train itself into human mind.
The future of autonomous vehicle deployment requires a smart transportation infrastructure that uses AI-traffic cameras and LiDAR sensors.
Technique allows researchers to toggle on individual genes that regulate cell growth, development, and function.
By combining CRISPR technology with a protein designed with artificial intelligence, it is possible to awaken individual dormant genes by disabling the chemical “off switches” that silence them. Researchers from the University of Washington School of Medicine in Seattle describe this finding in the journal Cell Reports.
The approach will allow researchers to understand the role individual genes play in normal cell growth and development, in aging, and in such diseases as cancer, said Shiri Levy, a postdoctoral fellow in UW Institute for Stem Cell and Regenerative Medicine (ISCRM) and the lead author of the paper.
NVIDIA today introduced Clara Holoscan MGX™, a platform for the medical device industry to develop and deploy real-time AI applications at the edge, specifically designed to meet required regulatory standards.
Mind-body philosophy | solving the hard problem of consciousness.
Recent advances in science and technology have allowed us to reveal — and in some cases even alter — the innermost workings of the human body. With electron microscopes, we can see our DNA, the source code of life itself. With nanobots, we can send cameras throughout our bodies and deliver drugs directly into the areas where they are most needed. We are even using artificially intelligent robots to perform surgeries on ourselves with unprecedented precision and accuracy.
Materialism says that the cosmos, and all that is contains, is an objective physical reality. As a result, philosophers who subscribe to this school of thought assert that consciousness, and all that it entails, arises from material interactions. As such, the material world (our flesh, neurons, synapse, etc.) is what creates consciousness.
Idealism says that the universe is entirely subjective and that reality is something that is mentally constructed. In other words, consciousness is something that is immaterial and cannot be observed or measured empirically. Since consciousness is what creates the material world, according to this school of thought, it is unclear if we can ever truly know anything that is mind-independent and beyond our subjective experience.
In recent decades, machine learning and deep learning algorithms have become increasingly advanced, so much so that they are now being introduced in a variety of real-world settings. In recent years, some computer scientists and electronics engineers have been exploring the development of an alternative type of artificial intelligence (AI) tools, known as diffractive optical neural networks.
Diffractive optical neural networks are deep neural networks based on diffractive optical technology (i.e., lenses or other components that can alter the phase of light propagating through them). While these networks have been found to achieve ultra-fast computing speeds and high energy efficiencies, typically they are very difficult to program and adapt to different use cases.
Researchers at Southeast University, Peking University and Pazhou Laboratory in China have recently developed a diffractive deep neural network that can be easily programmed to complete different tasks. Their network, introduced in a paper published in Nature Electronics, is based on a flexible and multi-layer metasurface array.
Atomic clocks are the best sensors mankind has ever built. Today, they can be found in national standards institutes or satellites of navigation systems. Scientists all over the world are working to further optimize the precision of these clocks. Now, a research group led by Peter Zoller, a theorist from Innsbruck, Austria, has developed a new concept that can be used to operate sensors with even greater precision irrespective of which technical platform is used to make the sensor. “We answer the question of how precise a sensor can be with existing control capabilities, and give a recipe for how this can be achieved,” explain Denis Vasilyev and Raphael Kaubrügger from Peter Zoller’s group at the Institute of Quantum Optics and Quantum Information at the Austrian Academy of Sciences in Innsbruck.
For this purpose, the physicists use a method from quantum information processing: Variational quantum algorithms describe a circuit of quantum gates that depends on free parameters. Through optimization routines, the sensor autonomously finds the best settings for an optimal result. “We applied this technique to a problem from metrology—the science of measurement,” Vasilyev and Kaubrügger explain. “This is exciting because historically advances in atomic physics were motivated by metrology, and in turn quantum information processing emerged from that. So, we’ve come full circle here,” Peter Zoller says. With the new approach, scientists can optimize quantum sensors to the point where they achieve the best possible precision technically permissible.
Your appliances, car and home are designed to make your life easier and automate tasks you perform daily: switch lights on and off when you enter and exit a room, remind you that your tomatoes are about to go bad, personalize the temperature of the house depending on the weather and preferences of each person in the household.
To do their magic, they need the internet to reach out for help and correlate data. Without internet access, your smart thermostat can collect data about you, but it doesn’t know what the weather forecast is, and it isn’t powerful enough to process all of the information to decide what to do.
But it’s not just the things in your home that are communicating over the internet. Workplaces, malls and cities are also becoming smarter, and the smart devices in those places have similar requirements. In fact, the Internet of Things (IoT) is already widely used in transport and logistics, agriculture and farming, and industry automation. There were around 22 billion internet-connected devices in use around the world in 2018, and the number is projected to grow to over 50 billion by 2030.
How to robotically build a human habitat in space…
Happening now.
Accelerate the accessibility and commercialization of cislunar space through cost-effective, habitable, scalable Infrastructure.
A talk with Sebastian Asprella CEO at ThinkOrbital: a commercial space-platform developer with a mission to accelerate the commercialization of cislunar space, focusing on On-orbit servicing, assembly and manufacturing technologies. Their flagship space-platform, the Orb2, is designed for a single-launch on-orbit assembly model, capable of delivering an internal spherical volume of up to 4000m3.
