Researchers in Switzerland have figured out how to use AI to predict when and where lightning will strike. Researchers from École Polytechnique Fédérale de Lausanne used standard meteorological data and machine learning to build a simple system that can predict lightning strike to the nearest 10 to 30 minutes inside a radius of about 18.6 miles, according to an account in Popular Mechanics. "We have used machine learning techniques to successfully hindcast nearby and distant lightning hazards by looking at single-site observations of meteorological parameters," wrote the authors in a new paper published recently in the journal Climate and Atmospheric Science. The researchers used data about past lightning strikes to build an algorithm that can make predictions about new lightning strikes, in a process called hindcasting, as opposed for forecasting. Estimates based on past events are fed into a model to see how well the output matches known results.

ANN ARBOR--With a shortage of new tuberculosis drugs in the pipeline, a software tool from the University of Michigan can predict how current drugs--including unlikely candidates--can be combined in new ways to create more effective treatments. "This could replace our traditional trial-and-error system for drug development that is comparatively slow and expensive," said Sriram Chandrasekaran, U-M assistant professor of biomedical engineering, who leads the research. Dubbed INDIGO, short for INferring Drug Interactions using chemoGenomics and Orthology, the software tool has shown that the potency of tuberculosis drugs can be amplified when they are teamed with antipsychotics or antimalarials. "This tool can accurately predict the activity of drug combinations, including synergy--where the activity of the combination is greater than the sum of the individual drugs," said Shuyi Ma, a research scientist at the University of Washington and a first author of the study. "It also accurately predicts antagonism between drugs, where the activity of the combination is lesser. In addition, it also identifies the genes that control these drug responses."

Lying has never looked so good, literally. Concern over increasingly sophisticated technology able to create convincingly faked videos and audio, so-called'deepfakes', is rising around the world. But at the same time they're being developed, technologists are also fighting back against the falsehoods. "The concern is that there will be a growing movement globally to undermine the quality of the information sphere and undermine the quality of discourse necessary in a democracy," Eileen Donahoe, a member of the Transatlantic Commission on Election Integrity, told CNBC in December 2018. She said deepfakes are potentially the next generation of disinformation.

"This (AI) is about augmenting human intelligence. When you step back and look at AI, yes there is hype, it will replace all jobs. We say look that's not the right way to approach it. The correct way to say is that this set of artificial intelligence technologies will augment and assist humans to do their work better," Ashvin Vellody, Partner, Deloitte India told indianexpress.com during an interaction. According to a new report by Deloitte and the Confederation of Indian Industry (CII), AI could prove to be most beneficial in areas like agriculture, manufacturing, education and health care services in India.

Imagine that you have been convicted of a crime and an algorithm is to help the judge by proposing the sentence. When computers are programmed, discrimination is built into the algorithms, so if you look a certain way you get a harder sentence. This example is not fiction. It comes from the USA where AI is being used in the legal system to propose sentencing for criminal offences, and it proposes harder sentences for black people. It might be chance, a prejudiced system developer or perhaps distorted data that the system had to practice on.

What is a data scientist? If you ask the Harvard Business Review, it's the "sexiest job of the 21st century." If you ask a technologist interested in crunching data, they'll tell you it's a potentially lucrative, intellectually fulfilling career. And if you ask a CEO, they'll probably say that data scientists mean the difference between strategic success and failure. But how do you actually become one? At the most basic level, data scientists analyze massive datasets for insights that can change how companies operate and strategize. As terms, "data scientist" and "data science" are relatively new, first appearing a little over a decade ago (roughly around the time that "Big Data" emerged into the mainstream as a buzzword, which isn't a coincidence).

Masayoshi Son stood on stage in Tokyo this month and told skeptical SoftBank Group Corp. investors that making WeWork Cos. Inc. profitable is not only possible, but will be "simple." Driving that confidence is WeWork's Japanese unit, which is already in the black and will be the springboard for a new service that could help the embattled office-sharing company. While WeWork's board was still deciding in late October between SoftBank's $9.5 billion rescue package and an alternative from JPMorgan Chase & Co., Son spent two full days at the unit's head office in Tokyo, pouring over the books, according to people familiar with the matter. Even before the deal was approved on Oct. 22, SoftBank was working with WeWork Japan on a subscription service called Passport that it plans to introduce worldwide, the people said asking not to be identified because the details aren't public. "Why do we think that WeWork is neither a quagmire nor a sinking business?"

On 17 November, the first edition of the Mint Visionaries series, which seeks to delve into the minds of people inspiring a new future, was kicked off with entrepreneur-philanthropist Bill Gates, who is also the co-chair of the Bill and Melinda Gates Foundation, sharing his thoughts with Wipro Ltd chairman Rishad Premji. The two discussed the challenges of mitigating climate change, eliminating malnutrition, and improving the health and education infrastructure, besides the role of technology, such as artificial intelligence, for social inclusion, something Gates considers a mission statement. Rishad Premji: Climate change will be one of the defining challenges of the 21st century--the impact of weather events, rising sea level, islands getting flooded. It will affect the way people live and potentially impact health and mortality. There is a huge implication of climate change. I know you personally and the Gates Foundation is spending a lot on mitigation--on how to reduce carbon emission. I know you are spending time on breakthrough energy ventures in your personal capacity, investing in technology that can pay off, as well as around adaptation. What are you personally, and through Gates Foundation, doing in these areas? And, what can we do to learn how to leverage science and technology, as governments and as citizens, to be more informed about climate change and its impact, considering that we often have this debate on whether it is real. And, what can come out of it? Bill Gates: I am actually writing a book about climate change.

This PyTorch implementation follow the structure of Neural Style Pt Github Link by Justin Johnson where the network is first build and feature map is captured after the architrcture is build. In the original code Official Code Github Link, the feature map is captured during the build of architecture which cause waist of computation. Also, the loss in different layer back prop by simply adding them up and call loss_total.backward() For more information on how to specify training process, check main.py - get_args()

There is a problem with artificial intelligence. It can be amazing at churning through gigantic amounts of data to solve challenges that humans struggle with. But understanding how it makes its decisions is often very difficult to do, if not impossible. That means when an AI model works it is not as easy as it should be to make further refinements, and when it exhibits odd behaviour it can be hard to fix. But at an event in London this week, Google's cloud computing division pitched a new facility that it hopes will give it the edge on Microsoft and Amazon, which dominate the sector.