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The story of humanity is progress, from the origins of humanity with slow disjointed progress to the agricultural revolution with linear progress and furthermore to the industrial revolution with exponential almost unfathomable progress.

This accelerating rate of change of progress is due to the compounding effect of technology, in which it enables countless more from 3D printing, autonomous vehicles, blockchain, batteries, remote surgeries, virtual and augmented reality, robotics – the list can go on and on. These devices in turn will lead to mass changes in society from energy generation, monetary systems, space colonization, automation and much more!

This is only the Beginning.


Quantum physicist Mario Krenn remembers sitting in a café in Vienna in early 2016, poring over computer printouts, trying to make sense of what MELVIN had found. MELVIN was a machine-learning algorithm Krenn had built, a kind of artificial intelligence. Its job was to mix and match the building blocks of standard quantum experiments and find solutions to new problems. And it did find many interesting ones. But there was one that made no sense.

“The first thing I thought was, ‘My program has a bug, because the solution cannot exist,’” Krenn says. MELVIN had seemingly solved the problem of creating highly complex entangled states involving multiple photons (entangled states being those that once made Albert Einstein invoke the specter of “spooky action at a distance”). Krenn and his colleagues had not explicitly provided MELVIN the rules needed to generate such complex states, yet it had found a way. Eventually, he realized that the algorithm had rediscovered a type of experimental arrangement that had been devised in the early 1990s. But those experiments had been much simpler. MELVIN had cracked a far more complex puzzle.

“When we understood what was going on, we were immediately able to generalize [the solution],” says Krenn, who is now at the University of Toronto. Since then, other teams have started performing the experiments identified by MELVIN, allowing them to test the conceptual underpinnings of quantum mechanics in new ways. Meanwhile Krenn, Anton Zeilinger of the University of Vienna and their colleagues have refined their machine-learning algorithms. Their latest effort, an AI called THESEUS, has upped the ante: it is orders of magnitude faster than MELVIN, and humans can readily parse its output. While it would take Krenn and his colleagues days or even weeks to understand MELVIN’s meanderings, they can almost immediately figure out what THESEUS is saying.

Below is my Answer.

“There is big confluence between AI & Social Media. It is a two way thing, AI not only affects Social Media, Social Media also plays a great role in the development of AI.

The way AI is developed is through data, large data (big data) and one of the easiest ways to generate and source for data at this scale is from the contents and interactions on social media.

Most social media platforms operate at scale, so for issues such as monitoring or censorship of what is being posted, the admin of these platforms have to use automation and AI for its management and policing.

AI algorithms such as sentiment analysis or recommendation engines (used by Facebook & Youtube to recommend posts based on the AI understanding of what you will like) are very much an integral part of any social platform architecture.

Nathan Seiberg, 64, still does a lot of the electrical work and even some of the plumbing around his house in Princeton, New Jersey. It’s an interest he developed as a kid growing up in Israel, where he tinkered with his car and built a radio.

“I was always fascinated by solving problems and understanding how things work,” he said.

Seiberg’s professional career has been about problem solving, too, though nothing as straightforward as fixing radios. He’s a physicist at the Institute for Advanced Study, and over the course of a long and decorated career he has made many contributions to the development of quantum field theory, or QFT.

After the program was first revealed in 2019, the Air Force’s then-Assistant Secretary of the Air Force for Acquisition, Technology and Logistics Will Roper stated he wanted to see operational demonstrations within two years. The latest test flight of the Skyborg-equipped Avenger shows the service has clearly hit that benchmark.

The General Atomics Avenger was used in experiments with another autonomy system in 2020, developed as part of the Defense Advanced Research Projects Agency’s (DARPA) Collaborative Operations in Denied Environment (CODE) program that sought to develop drones that could demonstrate “collaborative autonomy,” or the ability to work cooperatively.

The new carbon-based material could be a basis for lighter, tougher alternatives to Kevlar and steel.

A new study by engineers at MIT, Caltech, and ETH Zürich shows that “nanoarchitected” materials — materials designed from precisely patterned nanoscale structures — may be a promising route to lightweight armor, protective coatings, blast shields, and other impact-resistant materials.

The researchers have fabricated an ultralight material made from nanometer-scale carbon struts that give the material toughness and mechanical robustness. The team tested the material’s resilience by shooting it with microparticles at supersonic speeds, and found that the material, which is thinner than the width of a human hair, prevented the miniature projectiles from tearing through it.

We know less about the planet’s seabed than we do about the surface of the Moon or Mars. By the end of the decade, scientists are hoping to create a detailed map of these unexplored, submerged territories. They’ve already uncovered some spectacular features.

#Oceans #Moonshot #BloombergQuicktake.
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Stem cells for teeth repair.


Teeth exhibit limited repair in response to damage, and dental pulp stem cells probably provide a source of cells to replace those damaged and to facilitate repair. Stem cells in other parts of the tooth, such as the periodontal ligament and growing roots, play more dynamic roles in tooth function and development. Dental stem cells can be obtained with ease, making them an attractive source of autologous stem cells for use in restoring vital pulp tissue removed because of infection, in regeneration of periodontal ligament lost in periodontal disease, and for generation of complete or partial tooth structures to form biological implants. As dental stem cells share properties with mesenchymal stem cells, there is also considerable interest in their wider potential to treat disorders involving mesenchymal (or indeed non-mesenchymal) cell derivatives, such as in Parkinson’s disease.

Teeth are complex organs containing two separate specialized hard tissues, dentine and enamel, which form an integrated attachment complex with bone via a specialized (periodontal) ligament. Embryologically, teeth are ectodermal organs that form from sequential reciprocal interactions between oral epithelial cells (ectoderm) and cranial neural crest derived mesenchymal cells. The epithelial cells give rise to enamel forming ameloblasts, and the mesenchymal cells form all other differentiated cells (e.g., dentine forming odontoblasts, pulp, periodontal ligament) (Box 1). Teeth continue developing postnatally; the outer covering of enamel gradually becomes harder, and root formation, which is essential for tooth function, only starts to occur as part of tooth eruption in children.

Tooth development is traditionally considered a series of stages that reflect key processes ( Figure I ). The first step is induction, in which signals from the epithelium to the mesenchyme initiate the developmental process. As localized proliferation of the dental epithelial cells takes place, the cells form a bud around which the mesenchymal cells condense. Differentiation and localized proliferation of the epithelial cells in the bud leads to the cap stage. It is at this stage that crown morphogenesis is initiated by the epithelial signalling centre, an enamel knot regulating the folding of the epithelium. By the bell stage, the precursors of the specialized tooth cells, ameloblasts, coordinate enamel deposition, and odontoblasts, which produce dentine, are formed. Tooth eruption involves the coordination of bone resorption and root development, and occurs postnatally.