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Jul 17, 2020

AI 50 Founders Predict What Artificial Intelligence Will Look Like After Covid-19

Posted by in categories: biotech/medical, business, robotics/AI, security

Do you agree with these predictions?


The first few months of 2020 have radically reshaped the way we work and how the world gets things done. While the wide use of robotaxis or self-driving freight trucks isn’t yet in place, the Covid-19 pandemic has hurried the introduction of artificial intelligence across all industries. Whether through outbreak tracing or contactless customer pay interactions, the impact has been immediate, but it also provides a window into what’s to come. The second annual ForbesAI 50, which highlights the most promising U.S.-based artificial intelligence companies, features a group of founders who are already pondering what their space will look like in the future, though all agree that Covid-19 has permanently accelerated or altered the spread of AI.

“We have seen two years of digital transformation in the course of the last two months,” Abnormal Security CEO Evan Reiser told Forbes in May. As more parts of a company are forced to move online, Reiser expects to see AI being put to use to help businesses analyze the newly available data or to increase efficiency.

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Jul 17, 2020

Scientists accidentally create unlikely fish hybrid

Posted by in category: futurism

The two parental species diverged more than 184 million years ago.

Jul 17, 2020

ARCHIVE — Trailer

Posted by in category: futurism

How far would you go to bring back the one you love? Theo James and Stacy Martin star in #ArchiveMovie — on digital July 10.

Jul 17, 2020

Amazon, Google, Microsoft sued over photos in facial recognition database

Posted by in category: robotics/AI

The plaintiffs allege that the tech giants used people’s pictures obtained without permission to train their technologies.

Jul 17, 2020

Africa is splitting in two here is why

Posted by in category: transportation

(MENAFN — The Conversation) A large crack, stretching several kilometres, made a sudden appearance recently in south-western Kenya. The tear, which continues to grow, caused part of the Nairobi-Narok highway to collapse. Initially, the appearance of the crack was linked to tectonic activity along the East African Rift. But although geologists now think that this feature is most likely an erosional gully, questions remain as to why it has formed in the location that it did and whether its appearance is at all connected to the ongoing East African Rift. For example, the crack could be the result of the erosion of soft soils infilling an old rift-related fault.

The Earth is an ever-changing planet, even though in some respects change might be almost unnoticeable to us. Plate tectonics is a good example of this. But every now and again something dramatic happens and leads to renewed questions about the African continent splitting in two.

The Earth’s lithosphere (formed by the crust and the upper part of the mantle) is broken up into a number of tectonic plates. These plates are not static, but move relative to each other at varying speeds, ‘gliding’ over a viscous asthenosphere. Exactly what mechanism or mechanisms are behind their movement is still debated, but are likely to include convection currents within the asthenosphere and the forces generated at the boundaries between plates.

Jul 17, 2020

Google’s Fabricius uses machine learning to decode hieroglyphs

Posted by in category: robotics/AI

Google’s Arts and Culture vertical has been known to release fun apps and tools to help people engage with art and history. In 2018, it launched a feature to let you find your fine art doppelganger by taking a selfie, and more recently it added ways for you to apply filters to your photos to take on the style of masters like Van Gogh or Da Vinci. Now, the company is launching a web-based AI tool to let users interact with ancient Egyptian hieroglyphs and also help researchers decode the symbols with machine learning. It’s called Fabricius, named after the “father of epigraphy, the study of ancient inscriptions,” according to Google, and will let you send roughly translated messages in hieroglyphs to your friends.

Fabricius has three sections: Learn, Play and Work. In the first part, you go through a quick six-stage course that introduces you to the history and study of hieroglyphs. There are activities here that include tracing and drawing a symbol, with machine learning analyzing your drawings to see how accurate you were. For example, my drawing of an Ankh symbol after having seen it for five seconds was determined to be 100 percent correct, while my attempt at a sceptre was deemed 98 percent accurate.

Jul 17, 2020

New learning algorithm should significantly expand the possible applications of AI

Posted by in categories: information science, robotics/AI, supercomputing

The high energy consumption of artificial neural networks’ learning activities is one of the biggest hurdles for the broad use of Artificial Intelligence (AI), especially in mobile applications. One approach to solving this problem can be gleaned from knowledge about the human brain.

Although it has the computing power of a supercomputer, it only needs 20 watts, which is only a millionth of the of a supercomputer.

One of the reasons for this is the efficient transfer of information between in the brain. Neurons send short electrical impulses (spikes) to other neurons—but, to save energy, only as often as absolutely necessary.

Jul 17, 2020

Powerful AI Can Now Be Trained on a Single Computer

Posted by in category: robotics/AI

New machine learning training approach could help under-resourced academic labs catch up with big tech.

Jul 17, 2020

Atomtronic device could probe boundary between quantum, everyday worlds

Posted by in categories: computing, particle physics, quantum physics

A new device that relies on flowing clouds of ultracold atoms promises potential tests of the intersection between the weirdness of the quantum world and the familiarity of the macroscopic world we experience every day. The atomtronic Superconducting QUantum Interference Device (SQUID) is also potentially useful for ultrasensitive rotation measurements and as a component in quantum computers.

“In a conventional SQUID, the quantum interference in electron currents can be used to make one of the most sensitive detectors,” said Changhyun Ryu, a physicist with the Material Physics and Applications Quantum group at Los Alamos National Laboratory. “We use rather than charged electrons. Instead of responding to magnetic fields, the atomtronic version of a SQUID is sensitive to mechanical rotation.”

Although small, at only about 10 millionths of a meter across, the atomtronic SQUID is thousands of times larger than the molecules and atoms that are typically governed by the laws of quantum mechanics. The relatively large scale of the device lets it test theories of macroscopic realism, which could help explain how the world we are familiar with is compatible with the quantum weirdness that rules the universe on very small scales. On a more pragmatic level, atomtronic SQUIDs could offer highly sensitive rotation sensors or perform calculations as part of quantum computers.

Jul 17, 2020

Researchers realize nanoscale electrometry based on magnetic-field-resistant spin sensors

Posted by in categories: computing, nanotechnology, quantum physics

A team led by Prof. Du Jiangfeng, Prof. Shi Fazhan, and Prof. Wang Ya from University of Science and Technology of China, of the Chinese Academy of Sciences, proposed a robust electrometric method utilizing a continuous dynamic decoupling technique, where the continuous driving fields provide a magnetic-field-resistant dressed frame. The study was published in Physical Review Letters on June 19.

Characterization of electrical properties and comprehension of the dynamics in nanoscale become significant in the development of modern electronic devices, such as semi-conductor transistors and quantum chips, especially when the feature size has shrunk to several nanometers.

The nitrogen-vacancy (NV) center in diamond—an atomic-scale spin sensor—has shown to be an attractive electrometer. Electrometry using the NV center would improve various sensing and imaging applications. However, its natural susceptibility to the magnetic field hinders effective detection of the electric field.