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Artificial intelligence algorithm can determine a neighborhood’s political leanings by its cars

From the understated opulence of a Bentley to the stalwart family minivan to the utilitarian pickup, Americans know that the car you drive is an outward statement of personality. You are what you drive, as the saying goes, and researchers at Stanford have just taken that maxim to a new level.

Using computer algorithms that can see and learn, they have analyzed millions of publicly available images on Google Street View. The researchers say they can use that knowledge to determine the political leanings of a given neighborhood just by looking at the cars on the streets.

“Using easily obtainable visual data, we can learn so much about our communities, on par with some information that takes billions of dollars to obtain via census surveys. More importantly, this research opens up more possibilities of virtually continuous study of our society using sometimes cheaply available visual data,” said Fei-Fei Li, an associate professor of computer science at Stanford and director of the Stanford Artificial Intelligence Lab and the Stanford Vision Lab, where the work was done.

Teaching evolutionary theory to artificial intelligence reveals cancer’s life history

Scientists have developed the most accurate computing method to date to reconstruct the patchwork of genetic faults within tumors and their history during disease development, in new research funded by Cancer Research UK and published in Nature Genetics.

Their powerful approach combines with the mathematical models of Charles Darwin’s theory of evolution to analyze genetic data more accurately than ever before, paving the way for a fundamental shift in how ’s genetic diversity is used to deliver tailored treatments to patients.

Applying these to DNA data taken from patient samples revealed that tumors had a simpler genetic structure than previously thought. The algorithms showed that tumors had fewer distinct subpopulations of cells, called “subclones,” than previously suggested. The scientists, based at The Institute of Cancer Research, London, and Queen Mary University of London, could also tell how old each subclone was and how fast it was growing.

Germany tells Elon Musk he can have whatever he needs for new Berlin plant

Tesla boss Elon Musk has been told by Germany’s economy minister that he can have whatever he needs for his new electric vehicle manufacturing plant in Berlin.

Musk and Germany economy minister Peter Altmaier had an hour long meeting in Berlin on Wednesday, according to a source familiar with the matter. “The main topics were Tesla’s billions of euros worth of investment in Germany,” the source said.

The duo, who first met six years ago, also spoke about Musk’s projects in areas like space flight and autonomous driving.

Exploring the Implications of AI with Mastercard’s AI Garage

Amanda Christensen, ideaXme guest contributor, fake news and deep fake researcher, and Marketing Manager at Cubaka, interviews Nitendra Rajput, VP and Head of Mastercard’s AI Garage.

Amanda Christensen Comments:

Artificial intelligence has become a technological buzzword, often solely referred to AI rather than depicting the possibly infinite amount of practical applications that artificial intelligence can actually provide, or the intricacies involved from industry to industry, and region to region.

To discuss some of the many applications for artificial intelligence, as well as some of the considerations to be taken into account to create more accurate and less biased machine learning systems, I had the pleasure of speaking with Nitendra Rajput, VP and Head of Mastercard’s AI Garage.

Nitendra rajput head of mastercard’s AI garage:

Nitendra Rajput is the Vice President and Head of Mastercard’s AI Garage, setting up the centre to enable it to solve problems across various business verticals globally with machine learning processes, increasing efficiencies across the business as well as mitigating instances of fraud.

Optimising the Everyday with The Spatial Web

Amanda Christensen, ideaXme guest contributor, fake news and deepfake researcher and Marketing Manager at Cubaka, interviews Dan Mapes, PhD, MBA co-founder of VERSES.io and co-author of The Spatial Web: How Web 3.0 Will Connect Humans, Machines, and AI to Transform the World.

Amanda Christensen Comments:

We’ve come a long way since the invention of the internet, and even further since the invention of the first computer, which together have undeniably significantly facilitated everyday life. We have never had access to more information at the touch of our fingers, or been more connected than we are now.

However, the exponential advancement of the internet has brought along with it a whole host of problems, such as the rampant spread of fake news, deep fake technology, significant data breaches, and hacking, to name a few.

The further advancement of the internet, and particularly AI, is inevitable, as the full potential of their capabilities are far from being reached. But how do we advance in a way that both further optimises our lives but simultaneously protects us from further misuse?

The Spatial Web

Tom Lawry Talks of Machine Learning and Microsoft AI For Good in Healthcare

Deploying “AI for Good” In The Life Sciences — Tom Lawry, National Director for Artificial Intelligence, Health & Life Sciences, Microsoft, joins me on ideaXme to discuss how they are deploying artificial intelligence “at scale”, across the major organizations responsible for delivery quality, next generation healthcare to millions of patients and customers — #Ideaxme #Microsoft #ArtificialIntelligence #MachineLearning #DeepLearning #Health #Healthcare #Wellness #Medicine #Pharmacy #Hospitals #Nursing #Insurance #Diagnostics #Data #Moonshots #Biotechnology #Longevity #LifeExtension #Aging #IraPastor #Bioquark #Regenerage


Ira Pastor, ideaXme life sciences ambassador, interviews Tom Lawry, National Director for Artificial Intelligence — Health & Life Sciences at Microsoft.

Ira Pastor Comments:

A set of tools that we have been hearing quite a bit about (and discussed a bit on the show) in recent years is the triad of artificial intelligence, machine learning, and deep learning and their respective applications (primarily in the drug discovery and development processes), in terms how university labs and startups are using some of these tools to better guide the rational drug design process, or more appropriately select patients for a clinical trial, per the field of personalized medicine.

Today we are going to go to the far end of the spectrum, to a view of the potential of these tools at “scale”, when they need to be deployed across the mega enterprises responsible for delivery quality, next generation healthcare to millions of customers.

Artificial Emotional Intelligence (Emotion AI) – What It Is and Why It Matters

A pioneer in Emotion AI, Rana el Kaliouby, Ph.D., is on a mission to humanize technology before it dehumanizes us.

At LiveWorx 2020, Rana joined us to share insights from years of research and collaboration with MIT’s Advanced Vehicle Technology group.

Part demo and part presentation, Rana breaks down the facial patterns that cameras can pick up from a tired or rested driver, and observations from the first ever large-scale study looking at driver behavior over time.

Learn how these inferences can be used to change the driving experience ➡️ https://archive.liveworx.com/sessions/artificial-emotional-i…it-matters


Today’s devices work hand-in-hand with humans –at work, home, school and play. Dr. Rana el Kaliouby believes they can do much more. An expert in artificial emotional intelligence, or “Emotion AI,” Dr. el Kaliouby explores the valuable applications of humanized technology in media and advertising, gaming, automotive, robotics, health, education and more. She explains how machine learning works, explores the potential for the development of emotion chips, and addresses the ethics and privacy issues of Emotion AI. In her talks, Dr. el Kaliouby gives participants an inside look at the world’s largest emotion data repositoryresults from her research studying more than 5 million faces around the world, and reveals that the emoji mindset may soon be a thing of the past.

Memory in a metal, enabled by quantum geometry

The emergence of artificial intelligence and machine learning techniques is changing the world dramatically with novel applications such as internet of things, autonomous vehicles, real-time imaging processing and big data analytics in healthcare. In 2020, the global data volume is estimated to reach 44 Zettabytes, and it will continue to grow beyond the current capacity of computing and storage devices. At the same time, the related electricity consumption will increase 15 times by 2030, swallowing 8% of the global energy demand. Therefore, reducing energy consumption and increasing speed of information storage technology is in urgent need.

Berkeley researchers led by HKU President Professor Xiang Zhang when he was in Berkeley, in collaboration with Professor Aaron Lindenberg’s team at Stanford University, invented a new data storage method: They make odd numbered layers slide relative to even-number layers in tungsten ditelluride, which is only 3nm thick. The arrangement of these atomic layers represents 0 and 1 for data storage. These researchers creatively make use of quantum geometry: Berry curvature, to read information out. Therefore, this material platform works ideally for memory, with independent ‘write’ and ‘read’ operation. The using this novel data storage method can be over 100 times less than the traditional method.

This work is a conceptual innovation for non-volatile storage types and can potentially bring technological revolution. For the first time, the researchers prove that two-dimensional semi-metals, going beyond traditional silicon material, can be used for information storage and reading. This work was published in the latest issue of the journal Nature Physics. Compared with the existing non-volatile (NVW) memory, this new material platform is expected to increase speed by two orders and decrease energy cost by three orders, and it can greatly facilitate the realization of emerging in-memory computing and neural network computing.

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