From the COLUMBIA UNIVERSITY SCHOOL OF ENGINEERING AND APPLIED SCIENCE and the "learn garbage in, get garbage out" department. New York, NY–June 19, 2018–A major challenge in current climate prediction models is how to accurately represent clouds and their atmospheric heating and moistening. This challenge is behind the wide spread in climate prediction. Yet accurate predictions of global warming in response to increased greenhouse gas concentrations are essential for policy-makers (e.g. the Paris climate agreement). In a paper recently published online in Geophysical Research Letters (May 23), researchers led by Pierre Gentine, associate professor of earth and environmental engineering at Columbia Engineering, demonstrate that machine learning techniques can be used to tackle this issue and better represent clouds in coarse resolution ( 100km) climate models, with the potential to narrow the range of prediction.

Fast food, real estate, military operations, even home improvement -- many large industries will have to shift their strategies in the wake of driverless cars. It's all but a certainty that autonomous or driverless vehicles will be widely used in the United States at some point over the next two decades. Already, over two dozen major corporates including Google, Apple and Mercedes Benz are hard at work building their own self-driving vehicles. Tesla's Model S already includes an autopilot mode where the car drives itself on highways. Car ownership and driving habits are being completely reinvented. We'll explore the growing number of mobility technologies that are set to transform the current transportation ecosystem. Clearly tech and auto companies stand to gain, but many other industries could face serious upheavals unless they are able to adapt to the many changes self-driving cars will bring to the market. Below, we dive into 33 industries, from the obvious (professional driving & trucking) to the more surprising (fitness?), that will be shaken up by the advent of autonomous vehicles.

A Danish software company has developed an artificial intelligence (AI) programme that can detect heart attacks, according to a report in Bloomberg. The report said that the Corti SA's AI employs machine learning based on neural networks to analyse the words used in a panic call describing the incident, the tone of voice, and background noises. It then issues an alert about the likelihood of a heart attack. The software accurately detected cardiac arrests in 93% of cases versus 73% for human dispatchers, according to a study by the University of Copenhagen, the Danish National Institute of Public Health, and Copenhagen Emergency Medical Services. In addition, the software was able to make a decision in 48 seconds on an average, more than half a minute faster than humans.

Watson, an artificial intelligence system built by International Business Machines (NYSE:IBM), made headlines in 2011 by beating two champions on the game show Jeopardy! This initial version of Watson was built for answering Jeopardy!-style questions, backed by a vast database of information. Since then, Watson has been adapted to a wide variety of business applications, in industries such as healthcare and financial services. This article originally appeared in the Motley Fool. Soon after Watson's debut, IBM began work on another AI project.

Kraken Robotics, Inc. (OTCQB: KRKNF) (TSXV: PNG) is engaged as a marine technology company that develops underwater robotic systems and software-centric sensors. Shares of the underwater robotics company are rallying 35%, through early trading on Wednesday, June 20, 2018. Over the past month, Kraken Robotics, Inc. has seen average daily volume of 78,235 shares. However, volume of 155,625 shares or dollar volume of $24,121, has already exchanged hands on the day. Shares of Kraken Robotics, Inc. are climbing today after the company announced that it has received a non-brokered private placement offering with Ocean Infinity, Ltd., an offshore ocean survey and ocean exploration company.

An international team of scientists from Eindhoven University of Technology, University of Texas at Austin, and University of Derby, has developed a revolutionary method that quadratically accelerates artificial intelligence (AI) training algorithms. This gives full AI capability to inexpensive computers, and would make it possible in one to two years for supercomputers to utilize Artificial Neural Networks that quadratically exceed the possibilities of today's artificial neural networks. The scientists presented their method on June 19 in the journal Nature Communications. Artificial Neural Networks (or ANN) are at the very heart of the AI revolution that is shaping every aspect of society and technology. But the ANNs that we have been able to handle so far are nowhere near solving very complex problems.

Nations such as China, Finland, France, the UK and India, plus the European Union, have all released artificial intelligence strategies of sorts over the past year, hoping to ready their economies and societies for a wave of upheaval and opportunity afforded by increasingly smart machines. Researchers and universities are seen as key: announcing France's strategy in March, president Emmanuel Macron earmarked €400 million (£349 million) for AI research. The strategies include a wealth of suggestions – and dilemmas – as policymakers grapple with how best to support research into AI, link it with other disciplines and feed the results through into the economy. Perhaps the most pressing problem for AI research, particularly in Europe, is that universities cannot match the lucrative salaries on offer at tech giants in Silicon Valley. The French approach, set out in a report called For a Meaningful Artificial Intelligence, suggests doubling the salaries of AI graduates who work in public research institutions, otherwise the flow into universities could "dry up completely". Marc Schoenauer, a former president of the French Association for Artificial Intelligence and part of the team that drew up the report, admitted that this was unrealistic.

Cylance, an Irvine-based cybersecurity firm, continues to secure big bucks from investors, this time raising $120 million to fund global expansion, sales and development efforts. Blackstone Tactical Opportunities led the funding round with other investors, according to Cylance's announcement Tuesday, June 19. Cylance uses artificial intelligence to predict cyberattacks on computer networks. Since its debut in 2012, the company has secured millions from investors who believe in the company's algorithmic technology. In 2017, the company reported $100 million in revenue, a first for the startup.

Apple Inc.'s next breakthrough may be powered by Augmented Reality (AR). A recent report by Bloomberg outlines Apple's'big step' towards the AR space through talented hires and acquisitions in the related field. According to the report, with the goal of making smart glasses, in the short term, Apple's AR features may first show up on the iPhone. Bloomberg's report comes after its November story published last year, which highlighted Apple's wearable expansion into'digital glasses'. The AR industry is gaining momentum and could be a huge global market worth $90 million by 2020.

To deliver pertinent results, AI must rely on large data sets and extensive databases, from which programs can learn and make correlations.