Apex Motors won’t begin to make the production version of its new AP-0 electric supercar until 2022, but plans to sell the car for nearly $200,000.
Over the last decade, artificial intelligence (AI) and its applications such as machine learning have gained pace to revolutionize many industries. As the world gathers more data, the computing power of hardware systems needs to grow in tandem. Unfortunately, we are facing a future where we will not be able to generate enough energy to power our computational needs.
“We hear a lot of predictions about AI ushering in the fourth industrial revolution. It is important for us to understand that the computing platforms of today will not be able to sustain at-scale implementations of AI algorithms on massive datasets. It is clear that we will have to rethink our approaches to computation on all levels: materials, devices and architecture. We are proud to present an update on two fronts in this work: materials and devices. Fundamentally, the devices we are demonstrating are a million times more power efficient than what exists today,” shared Professor Thirumalai Venky Venkatesan, the lead Principal Investigator of this project who is from the National University of Singapore (NUS).
In a paper published in Nature Nanotechnology on 23 March 2020, the researchers from the NUS Nanoscience and Nanotechnology Initiative (NUSNNI) reported the invention of a nanoscale device based on a unique material platform that can achieve optimal digital in-memory computing while being extremely energy efficient. The invention is also highly reproducable and durable, unlike conventional organic electronic devices.
What is interaction, and when does it occur? Intuition suggests that the necessary condition for the interaction of independently created particles is their direct touch or contact through physical force carriers. In quantum mechanics, the result of the interaction is entanglement—the appearance of non-classical correlations in the system. It seems that quantum theory allows entanglement of independent particles without any contact. The fundamental identity of particles of the same kind is responsible for this phenomenon.
Quantum mechanics is currently the best and most accurate theory used by physicists to describe the world around us. Its characteristic feature, however, is the abstract mathematical language of quantum mechanics, notoriously leading to serious interpretational problems. The view of reality proposed by this theory is still a subject of scientific dispute that, over time, is only becoming hotter and more interesting. New research motivation and intriguing questions are brought forth by a fresh perspective resulting from the standpoint of quantum information and the enormous progress of experimental techniques. These allow verification of the conclusions drawn from subtle thought experiments directly related to the problem of interpretation. Moreover, researchers are now making enormous progress in the field of quantum communication and quantum computer technology, which significantly draws on non-classical resources offered by quantum mechanics.
Pawel Blasiak from the Institute of Nuclear Physics of the Polish Academy of Sciences in Krakow and Marcin Markiewicz from the University of Gdansk focus on analyzing widely accepted paradigms and theoretical concepts regarding the basics and interpretation of quantum mechanics. The researchers are trying to determine to what extent the intuitions used to describe quantum mechanical processes are justified in a realistic view of the world. For this purpose, they try to clarify specific theoretical ideas, often functioning in the form of vague intuitions, using the language of mathematics. This approach often results in the appearance of inspiring paradoxes. Of course, the more basic the concept to which a given paradox relates, the better, because it opens up new doors to deeper understanding a given problem.
Elon Musk praised Tesla’s team for the Model Y’s heat pump — a feature that could make the electric SUV much more efficient in colder climates.
Last week, Tesla started deliveries of the Model Y, its fourth vehicle in the current lineup and fifth model ever.
By Bill D’Zio March 25, 2020
SpaceX Crew Dragon on approach Credit NASA
Part 2 of the Life in Space with COVID19 we will delve into Crew demo-2 where NASA and SpaceX are planning a launch within two months. There are a lot of pre-launch milestones and activities to cover to ensure a safe flight for the Astronauts. If anything goes wrong, there are lives at stake. Now NASA and SpaceX have to contend with another potential setback, COVID19 pandemic. (Click here for part I)
The SpaceX Crew Dragon spacecraft for Demo-2 arrived at the launch site on Feb. 13, 2020. Photo credit: SpaceX
In Part I of why COVID19 pandemic is bad timing for the Space industry, we covered that issues happen because the relationship between complexity, risk, schedule and cost for space missions was not balanced.
Continue reading “COVID19 Impact Part II – SpaceX , SLS and NASA” »
;-; They say now it could be a bioweapon possibly like the chimera virus that is why it spread so fast. Many weird reports from god having a battle with the borg to even an alien entity in London but rationally this was a bioweapon as it spread so fast and evolved so fast. Still undecided the origin bit it seems patient zero was in china originally from a bat.
The COVID-19 coronavirus may be a chimera created from the presence of two pre-existing distinct viruses.
For the first time, scientists have reprogrammed the stem cells of a 114-year-old woman, the oldest donor to date.
After first transforming cells from her blood sample into induced pluripotent stem cells (iPSCs), the researchers then generated mesenchymal stem cells, which help to maintain and repair tissues like bone, cartilage and fat.
“We set out to answer a big question: Can you reprogram cells this old?” says stem cell biologist Evan Snyder at Sanford Burnham Prebys Medical Discovery Institute in California.
A Nobel Prize winning biology professor has provided a bit of good news amidst the coronavirus gloom; the US may see a downturn in new cases sooner than some models have predicted.
Michael Levitt, a Stanford University biology professor and a 2013 Nobel Prize winner in chemistry, said his models predict the virus is not likely to dwindle on for months or years and – most importantly – is not likely to cause millions of deaths.
Mr Levitt previously predicted – correctly – when China would experience and endure the worst of its coronavirus crisis.
