New Delhi, The Railway ministry, Department of Science & Technology and IIT-Kanpur have forged an association on a project on'Industry 4.0', which includes a host of digital technologies like artificial intelligence, Big Data, machine learning and cloud computing. The project will be launched at Modern Coach Factory (MCF), Raebareli. A statement by the ministry of railways said that'Industry 4.0' will be commonly referred as the fourth industrial revolution amid current trend of automation, interconnectivity and data exchange in manufacturing technologies to increase productivity. "Industry 4.0 is a complex Cyber-Physical System which synergises production with digital technologies, the Internet of Things, Artificial Intelligence, Big Data & Analytics, Machine Learning and Cloud Computing," said the statement. MCF, is a state-of-the-art coach manufacturing unit with the capacity to manufacture 1,000 passenger coaches annually.

Parkland Hospital, a Dallas, TX-based hospital and health system has saved over $17 million dollars by reducing their hospital re-admissions and eliminating adverse drug events using a customized artificial intelligence (AI)-driven predictive model. Developed in partnership with affiliate Park Center for Clinical Innovation (PCCI) over the past 2 years, Parkland has been able to prevent more than 2,000 adverse drug events (ADEs) for hospitalized patients. PCCI combines extensive clinical expertise with advanced analytics and artificial intelligence to enable the delivery of patient-centric precision medicine at the point of care. The program, Patients at Risk for Adverse Drug Events (PARADE), is a partnership between PCCI and Parkland Health & Hospital System. PARADE screens all adult patients at the point of hospitalization and flags high-risk individuals who can benefit from pharmacist intervention.

On July 31, 2019, DeepMind published a research letter in Nature (via AI in Healthcare) about a clinically applicable approach to the continuous prediction of acute kidney injury (AKI). The predictive model was developed on a longitudinal dataset comprised of 703,782 adult patients across 172 inpatient and 1,062 outpatient sites. It "predicted more than half (55.8%) of all inpatient episodes of acute kidney injury and 90.2% of all acute kidney injuries that required dialysis. The lead-up time was 48 hours, and the model had a ratio of two false alerts for every true alert." TechCrunch reported on the study in an article titled "DeepMind touts predictive health care AI'breakthrough' trained on heavily skewed data."

The research also found U.S. employees are split on their perception of their readiness to work with AI. In fact, just over half (52%) of the U.S. employees surveyed believe they have the necessary skills to be successful in an AI-enabled workplace. However, almost as many (48%) doubt they have what it takes, with 20% saying they do not possess the right skills and 28% reporting they simply aren't sure. But confident Millennial employees are the most likely age group to feel their current skillset will meet the challenge of AI. "The most successful AI deployments take more than good data and the best technology – people are an equally important part of the equation. We believe that's why employers should be investing in their people to prepare them for a future workplace that will change as a result of this intelligent technology," said Merijn te Booij, chief marketing officer, Genesys.

This article is adapted from GreenBiz's newsletter, VERGE Weekly, running Wednesdays. If you think your organization has a challenging energy consumption profile, try running a network of cold storage facilities -- with most sites in not-so-cold locations, such as California and Georgia. One of the more intriguing examples of smart power management I've come across in recent months is an initiative under way at Lineage Logistics, which runs more than 200 warehouses across North America, Europe and Asia. It handles food for more than 2,500 customers, which are all businesses themselves, such as grocery stories and food services organizations. Each of the Lineage buildings -- an average of 1 million square feet in size -- basically stores about the same amount of food that you'd find in 770,000 home freezers.

Practical adoption of artificial intelligence (AI) faces a variety of roadblocks--splashy, high-profile deployments of AI have not been received well, with Microsoft's "Tay" bot on Twitter parroting anti-Semetic vitriol just 16 hours after launch. Similarly, Amazon's AI-powered hiring process displayed bias against women and the company marketed unreliable facial recognition technology to municipal law enforcement. AI often reflects the biases--including, and especially, unconscious biases--of the designers, which would make Facebook attempting to build an AI with an "ethical compass" a concerning prospect, given the multitude of other problems the social network has experienced. This is a problem that necessarily requires diversity of thought, according to Northeastern University's Ethics Institute and professional services firm Accenture, which published a guide to building data and AI ethics committees. Such committees are, by definition, not achievable by pooling together people of similar backgrounds to debate the merits of AI design.

SparkCognition, a global artificial intelligence (AI) leader that builds AI technology to advance the most important interests of society, announced the close of its Series C funding of $100 million led by March Capital Partners. With overall funding of $175 million since its inception in 2013, SparkCognition is now one of the most valuable startups in Texas and one of the most valuable AI startups in the United States. "In a short few years, SparkCognition has proven itself to be one of the leading industrial AI companies in the world," said Sumant Mandal, Managing Director and co-founder of March Capital Partners. "We are proud to lead their Series C round, and look forward to working closely with the company to drive its success even further." SparkCognition builds AI technology for industrial applications–revolutionizing the way industries like oil and gas, defense, utilities, aviation, and financial services manage such critical functions as efficiency and safety.

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AI and machine learning are the driving forces for innovations in the field of precision medicine.

If you've never seen or been near (or inside) a self-driving car, the concept can seem a bit much. But the thing is, autonomous vehicle technology is already all over: in many of our human-controlled cars, on the road in driverless shuttles and vans, and coming from self-driving companies like Alphabet's Waymo, GM-funded Cruise, Amazon-backed Aurora, and Uber. Even if it sounds like a far-off, far-fetched, futuristic proposition, self-driving cars aren't sci-fi. Engineering simulation software company Ansys surveyed more than 22,000 adults from the U.S., UK, France, Italy, Spain, Sweden, Japan, China, India, and other regions, about self-driving perceptions. The survey, out last week, found that older adults are less optimistic than younger adults about ever riding in a robocar.