Lifeboat Foundation

Compared to standard machine learning models, deep learning models are largely superior at discerning patterns and discriminative features in brain imaging, despite being more complex in their architecture, according to a new study in Nature Communications led by Georgia State University.

Advanced biomedical technologies such as structural and functional magnetic resonance imaging (MRI and fMRI) or genomic sequencing have produced an enormous volume of data about the human body. By extracting patterns from this information, scientists can glean new insights into health and disease. This is a challenging task, however, given the complexity of the data and the fact that the relationships among types of data are poorly understood.

Deep learning, built on advanced neural networks, can characterize these relationships by combining and analyzing data from many sources. At the Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State researchers are using deep learning to learn more about how mental illness and other disorders affect the brain.

Symbiosis by combining humans with artificial intelligence is Elon Musk’s #Neuralink corporate goal and I agree that is a great strategy for the future and why he is the richest person in the world now. 🌎

Some smart robots can perform complex tasks on their own, without the programmers understanding how they learned them.

As the story goes, the Greek mathematician and tinkerer Archimedes came across an invention while traveling through ancient Egypt that would later bear his name. It was a machine consisting of a screw housed inside a hollow tube that trapped and drew water upon rotation. Now, researchers led by Stanford University physicist Benjamin Lev have developed a quantum version of Archimedes’ screw that, instead of water, hauls fragile collections of gas atoms to higher and higher energy states without collapsing. Their discovery is detailed in a paper published Jan. 14 in Science.

“My expectation for our system was that the stability of the gas would only shift a little,” said Lev, who is an associate professor of applied physics and of physics in the School of Humanities and Sciences at Stanford. “I did not expect that I would see a dramatic, complete stabilization of it. That was beyond my wildest conception.”

Along the way, the researchers also observed the development of scar states—extremely rare trajectories of particles in an otherwise chaotic quantum system in which the particles repeatedly retrace their steps like tracks overlapping in the woods. Scar states are of particular interest because they may offer a protected refuge for information encoded in a quantum system. The existence of scar states within a quantum system with many interacting particles—known as a quantum many-body system—has only recently been confirmed. The Stanford experiment is the first example of the scar state in a many-body quantum gas and only the second ever real-world sighting of the phenomenon.

https://youtube.com/watch?v=YUNdEWoUs8Y

Welcome to the Siim Land Podcast I’m your host Siim Land and our guest today is Liz Parish. Liz is the founder and CEO of BioViva. Which is a company committed to extending human lifespan using techniques such as gene and cell technologies. Liz Parrish became the first person worldwide to take dual gene therapies for treating aging.

The many things you should know about the field of cryonics. The Cryonics Symposium International takes place Saturday in Hollywood, Fla.

The maker of a defunct cloud photo storage app that pivoted to selling facial recognition services has been ordered to delete user data and any algorithms trained on it, under the terms of an FTC settlement.

The regulator investigated complaints the Ever app — which gained earlier notoriety for using dark patterns to spam users’ contacts — had applied facial recognition to users’ photographs without properly informing them what it was doing with their selfies.

Under the proposed settlement, Ever must delete photos and videos of users who deactivated their accounts and also delete all face embeddings (i.e. data related to facial features which can be used for facial recognition purposes) that it derived from photos of users who did not give express consent to such a use.

Flying by yourself in a single-seater flying car is the lavish lifestyle vision of the future we deserve.

WASHINGTON — SpaceX secured contracts Jan. 13 for the launches of a commercial lunar lander mission backed by NASA as well as a privately funded satellite to track methane emissions.

Intuitive Machines announced that it selected SpaceX for the launch of its IM-2 lunar lander mission on a Falcon 9 rocket no earlier than 2022. IM-2 will land in the south polar region of the moon carrying payloads arranged through the agency’s Commercial Lunar Payload Services (CLPS) program in October.

The IM-2 mission will fly a drilling experiment called Polar Resources Ice Mining Experiment 1 (PRIME-1), which will look for water ice below the lunar surface. Intuitive Machines said that, besides the PRIME-1 drill, two other NASA technology payloads will fly on the lander.